for Journals by Title or ISSN
for Articles by Keywords
  Subjects -> ENGINEERING (Total: 2383 journals)
    - CHEMICAL ENGINEERING (204 journals)
    - CIVIL ENGINEERING (199 journals)
    - ELECTRICAL ENGINEERING (109 journals)
    - ENGINEERING (1248 journals)
    - HYDRAULIC ENGINEERING (56 journals)
    - INDUSTRIAL ENGINEERING (74 journals)
    - MECHANICAL ENGINEERING (97 journals)

CHEMICAL ENGINEERING (204 journals)                  1 2 | Last

Showing 1 - 200 of 204 Journals sorted alphabetically
AATCC Journal of Research     Full-text available via subscription   (Followers: 8)
ACS Sustainable Chemistry & Engineering     Hybrid Journal   (Followers: 6)
Acta Crystallographica Section B: Structural Science, Crystal Engineering and Materials     Hybrid Journal   (Followers: 6)
Acta Polymerica     Hybrid Journal   (Followers: 10)
Additives for Polymers     Full-text available via subscription   (Followers: 22)
Adhesion Adhesives & Sealants     Hybrid Journal   (Followers: 9)
Advanced Chemical Engineering Research     Open Access   (Followers: 38)
Advanced Powder Technology     Hybrid Journal   (Followers: 16)
Advances in Applied Ceramics     Hybrid Journal   (Followers: 5)
Advances in Chemical Engineering     Full-text available via subscription   (Followers: 27)
Advances in Chemical Engineering and Science     Open Access   (Followers: 66)
Advances in Polymer Technology     Hybrid Journal   (Followers: 14)
African Journal of Pure and Applied Chemistry     Open Access   (Followers: 7)
American Journal of Polymer Science & Engineering     Open Access  
Annual Review of Analytical Chemistry     Full-text available via subscription   (Followers: 10)
Annual Review of Chemical and Biomolecular Engineering     Full-text available via subscription   (Followers: 12)
Anti-Corrosion Methods and Materials     Hybrid Journal   (Followers: 11)
Applied Petrochemical Research     Open Access   (Followers: 3)
Asia-Pacific Journal of Chemical Engineering     Hybrid Journal   (Followers: 8)
Biochemical Engineering Journal     Hybrid Journal   (Followers: 15)
Biofuel Research Journal     Open Access   (Followers: 4)
Biomass Conversion and Biorefinery     Partially Free   (Followers: 10)
Brazilian Journal of Chemical Engineering     Open Access   (Followers: 4)
Bulletin of Chemical Reaction Engineering & Catalysis     Open Access   (Followers: 2)
Bulletin of the Chemical Society of Ethiopia     Open Access   (Followers: 2)
Carbohydrate Polymers     Hybrid Journal   (Followers: 8)
Catalysts     Open Access   (Followers: 9)
ChemBioEng Reviews     Full-text available via subscription   (Followers: 1)
ChemEngineering     Open Access  
Chemical and Engineering News     Free   (Followers: 18)
Chemical and Materials Engineering     Open Access   (Followers: 18)
Chemical and Petroleum Engineering     Hybrid Journal   (Followers: 13)
Chemical and Process Engineering     Open Access   (Followers: 33)
Chemical and Process Engineering Research     Open Access   (Followers: 30)
Chemical Engineering & Technology     Hybrid Journal   (Followers: 31)
Chemical Engineering and Processing: Process Intensification     Hybrid Journal   (Followers: 16)
Chemical Engineering and Science     Open Access   (Followers: 26)
Chemical Engineering Communications     Hybrid Journal   (Followers: 14)
Chemical Engineering Education     Full-text available via subscription   (Followers: 1)
Chemical Engineering Journal     Hybrid Journal   (Followers: 54)
Chemical Engineering Research and Design     Hybrid Journal   (Followers: 26)
Chemical Engineering Research Bulletin     Open Access   (Followers: 17)
Chemical Engineering Science     Hybrid Journal   (Followers: 28)
Chemical Geology     Hybrid Journal   (Followers: 24)
Chemical Papers     Hybrid Journal   (Followers: 2)
Chemical Product and Process Modeling     Hybrid Journal   (Followers: 4)
Chemical Reviews     Full-text available via subscription   (Followers: 185)
Chemical Society Reviews     Full-text available via subscription   (Followers: 43)
Chemical Technology     Open Access   (Followers: 22)
ChemInform     Hybrid Journal   (Followers: 8)
Chemistry & Industry     Hybrid Journal   (Followers: 6)
Chemistry Central Journal     Open Access   (Followers: 4)
Chemistry of Materials     Full-text available via subscription   (Followers: 252)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 14)
ChemSusChem     Hybrid Journal   (Followers: 7)
Chinese Chemical Letters     Full-text available via subscription   (Followers: 2)
Chinese Journal of Chemical Engineering     Full-text available via subscription   (Followers: 4)
Chinese Journal of Chemical Physics     Hybrid Journal   (Followers: 1)
Coke and Chemistry     Hybrid Journal   (Followers: 1)
Coloration Technology     Hybrid Journal   (Followers: 1)
Computational Biology and Chemistry     Hybrid Journal   (Followers: 11)
Computer Aided Chemical Engineering     Full-text available via subscription   (Followers: 1)
Computers & Chemical Engineering     Hybrid Journal   (Followers: 10)
CORROSION     Full-text available via subscription   (Followers: 21)
Corrosion Engineering, Science and Technology     Hybrid Journal   (Followers: 37)
Corrosion Reviews     Hybrid Journal   (Followers: 6)
Crystal Research and Technology     Hybrid Journal   (Followers: 6)
Current Applied Polymer Science     Hybrid Journal   (Followers: 1)
Current Environmental Engineering     Hybrid Journal  
Current Opinion in Chemical Engineering     Open Access   (Followers: 7)
Designed Monomers and Polymers     Open Access   (Followers: 2)
Education for Chemical Engineers     Hybrid Journal   (Followers: 5)
Eksergi     Open Access  
Emerging Trends in Chemical Engineering     Full-text available via subscription   (Followers: 3)
European Polymer Journal     Hybrid Journal   (Followers: 43)
Fibers and Polymers     Full-text available via subscription   (Followers: 6)
Fluorescent Materials     Open Access   (Followers: 1)
Focusing on Modern Food Industry     Open Access   (Followers: 2)
Food and Environment Safety     Open Access  
Frontiers of Chemical Science and Engineering     Hybrid Journal   (Followers: 3)
Gels     Open Access  
Geochemistry International     Hybrid Journal   (Followers: 2)
Handbook of Powder Technology     Full-text available via subscription   (Followers: 6)
Heat Exchangers     Open Access   (Followers: 3)
Hemijska Industrija     Open Access  
High Performance Polymers     Hybrid Journal   (Followers: 1)
Hungarian Journal of Industry and Chemistry     Open Access  
Indian Chemical Engineer     Hybrid Journal   (Followers: 5)
Indian Journal of Chemical Technology (IJCT)     Open Access   (Followers: 9)
Indonesian Journal of Chemical Science     Open Access   (Followers: 1)
Industrial & Engineering Chemistry     Full-text available via subscription   (Followers: 11)
Industrial & Engineering Chemistry Research     Full-text available via subscription   (Followers: 21)
Industrial Chemistry Library     Full-text available via subscription   (Followers: 3)
Industrial Gases     Open Access  
Info Chimie Magazine     Full-text available via subscription   (Followers: 3)
International Journal of Chemical Engineering     Open Access   (Followers: 7)
International Journal of Chemical Reactor Engineering     Hybrid Journal   (Followers: 2)
International Journal of Chemical Technology     Open Access   (Followers: 5)
International Journal of Chemoinformatics and Chemical Engineering     Full-text available via subscription   (Followers: 2)
International Journal of Food Science     Open Access   (Followers: 3)
International Journal of Industrial Chemistry     Open Access   (Followers: 1)
International Journal of Polymeric Materials     Hybrid Journal   (Followers: 6)
International Journal of Waste Resources     Open Access   (Followers: 4)
Iranian Journal of Polymer Science and Technology     Open Access   (Followers: 1)
Journal of Chemical Engineering & Process Technology     Open Access   (Followers: 5)
Journal of Applied Crystallography     Hybrid Journal   (Followers: 7)
Journal of Applied Electrochemistry     Hybrid Journal   (Followers: 13)
Journal of Applied Polymer Science     Hybrid Journal   (Followers: 137)
Journal of Applied Science & Process Engineering     Open Access  
Journal of Biomaterials Science, Polymer Edition     Hybrid Journal   (Followers: 9)
Journal of Bioprocess Engineering and Biorefinery     Full-text available via subscription  
Journal of Chemical & Engineering Data     Full-text available via subscription   (Followers: 11)
Journal of Chemical and Biological Interfaces     Full-text available via subscription   (Followers: 1)
Journal of Chemical Ecology     Hybrid Journal   (Followers: 7)
Journal of Chemical Engineering     Open Access   (Followers: 27)
Journal of Chemical Engineering and Materials Science     Open Access   (Followers: 4)
Journal of Chemical Science and Technology     Open Access   (Followers: 6)
Journal of Chemical Sciences     Partially Free   (Followers: 22)
Journal of Chemical Technology & Biotechnology     Hybrid Journal   (Followers: 9)
Journal of Chemical Theory and Computation     Full-text available via subscription   (Followers: 17)
Journal of CO2 Utilization     Hybrid Journal   (Followers: 2)
Journal of Combinatorial Chemistry     Full-text available via subscription   (Followers: 1)
Journal of Crystallization Process and Technology     Open Access   (Followers: 8)
Journal of Environmental Chemical Engineering     Hybrid Journal   (Followers: 7)
Journal of Food Measurement and Characterization     Hybrid Journal  
Journal of Food Processing & Technology     Open Access   (Followers: 1)
Journal of Fuel Chemistry and Technology     Full-text available via subscription   (Followers: 4)
Journal of Geochemical Exploration     Hybrid Journal   (Followers: 1)
Journal of Industrial and Engineering Chemistry     Hybrid Journal   (Followers: 1)
Journal of Information Display     Open Access   (Followers: 1)
Journal of Inorganic and Organometallic Polymers and Materials     Partially Free   (Followers: 10)
Journal of Materials Science and Chemical Engineering     Open Access   (Followers: 1)
Journal of Modern Chemistry & Chemical Technology     Open Access   (Followers: 3)
Journal of Molecular Catalysis A: Chemical     Hybrid Journal   (Followers: 7)
Journal of Non-Crystalline Solids     Hybrid Journal   (Followers: 8)
Journal of Organic Semiconductors     Open Access   (Followers: 5)
Journal of Physics and Chemistry of Solids     Hybrid Journal   (Followers: 4)
Journal of Polymer and Biopolymer Physics Chemistry     Open Access   (Followers: 7)
Journal of Polymer Engineering     Hybrid Journal   (Followers: 11)
Journal of Polymer Research     Hybrid Journal   (Followers: 7)
Journal of Polymer Science Part C : Polymer Letters     Hybrid Journal   (Followers: 6)
Journal of Polymers     Open Access   (Followers: 6)
Journal of Polymers and the Environment     Hybrid Journal   (Followers: 1)
Journal of Pure and Applied Chemistry Research     Open Access   (Followers: 2)
Journal of the American Chemical Society     Full-text available via subscription   (Followers: 332)
Journal of the Bangladesh Chemical Society     Open Access  
Journal of the Brazilian Chemical Society     Open Access   (Followers: 3)
Journal of The Institution of Engineers (India) : Series E     Hybrid Journal   (Followers: 2)
Journal of the Taiwan Institute of Chemical Engineers     Hybrid Journal   (Followers: 2)
Journal of Water Chemistry and Technology     Hybrid Journal   (Followers: 9)
Jurnal Bahan Alam Terbarukan     Open Access  
Jurnal Inovasi Pendidikan Kimia     Open Access   (Followers: 5)
Jurnal Reaktor     Open Access  
Jurnal Rekayasa Kimia & Lingkungan     Open Access  
Jurnal Teknologi Dan Industri Pangan     Open Access   (Followers: 1)
Konversi     Open Access  
Korean Journal of Chemical Engineering     Hybrid Journal   (Followers: 3)
Main Group Metal Chemistry     Hybrid Journal   (Followers: 2)
Materials Chemistry and Physics     Full-text available via subscription   (Followers: 17)
Materials Science and Applied Chemistry     Open Access  
Materials Sciences and Applied Chemistry     Full-text available via subscription  
Modern Chemistry & Applications     Open Access  
Molecular Imprinting     Open Access  
MRS Communications     Hybrid Journal  
Nanochemistry Research     Open Access  
Nanocontainers     Open Access   (Followers: 1)
Nanofabrication     Open Access  
Noise Control Engineering Journal     Full-text available via subscription   (Followers: 4)
Ochrona Srodowiska i Zasobów Naturalnych : Environmental Protection and Natural Resources     Open Access  
Petroleum Chemistry     Hybrid Journal   (Followers: 1)
Physics and Chemistry of Glasses - European Journal of Glass Science and Technology Part B     Full-text available via subscription   (Followers: 4)
Plasma     Open Access   (Followers: 1)
Plasma Processes and Polymers     Hybrid Journal   (Followers: 3)
Plasmas and Polymers     Hybrid Journal  
Polymer     Hybrid Journal   (Followers: 138)
Polymer Bulletin     Hybrid Journal   (Followers: 8)
Polymer Composites     Hybrid Journal   (Followers: 17)
Polyolefins Journal     Open Access  
Powder Metallurgy Progress     Unknown   (Followers: 1)
Powder Technology     Hybrid Journal   (Followers: 13)
Recent Innovations in Chemical Engineering     Hybrid Journal  
Recyclable Catalysis     Open Access   (Followers: 1)
Research on Chemical Intermediates     Hybrid Journal  
Reviews in Chemical Engineering     Hybrid Journal   (Followers: 5)
Revista Cubana de Química     Open Access  
Revista ION     Open Access  
Revista Mexicana de Ingeniería Química     Open Access  
Rubber Chemistry and Technology     Full-text available via subscription   (Followers: 2)
Russian Chemical Bulletin     Hybrid Journal   (Followers: 2)
Russian Journal of Applied Chemistry     Hybrid Journal   (Followers: 1)
Science and Engineering of Composite Materials     Hybrid Journal   (Followers: 61)
Solid Fuel Chemistry     Hybrid Journal  
South African Journal of Chemical Engineering     Open Access   (Followers: 2)
South African Journal of Chemistry     Open Access   (Followers: 2)
Surface Engineering and Applied Electrochemistry     Hybrid Journal   (Followers: 5)
Sustainable Chemical Processes     Open Access   (Followers: 2)
Synthesis Lectures on Chemical Engineering and Biochemical Engineering     Full-text available via subscription  
The Canadian Journal of Chemical Engineering     Hybrid Journal   (Followers: 4)
The Chemical Record     Hybrid Journal   (Followers: 1)
Theoretical Foundations of Chemical Engineering     Hybrid Journal   (Followers: 3)

        1 2 | Last

Journal Cover Computational Biology and Chemistry
  [SJR: 0.491]   [H-I: 47]   [11 followers]  Follow
   Hybrid Journal Hybrid journal (It can contain Open Access articles)
   ISSN (Print) 1476-9271
   Published by Elsevier Homepage  [3177 journals]
  • Discovery of novel drug candidates for inhibition of soluble epoxide
           hydrolase of arachidonic acid cascade pathway implicated in
    • Authors: Arun Bahadur Gurung; Bishwarjit Mayengbam; Atanu Bhattacharjee
      Pages: 1 - 11
      Abstract: Publication date: June 2018
      Source:Computational Biology and Chemistry, Volume 74
      Author(s): Arun Bahadur Gurung, Bishwarjit Mayengbam, Atanu Bhattacharjee
      Soluble epoxide hydrolase (sEH), a key enzyme belonging to cytochrome P450 pathway of arachidonic acid cascade is a novel therapeutic drug target against atherosclerosis. The enzyme breaks down epoxyeicosatrienoic acid (EETs) to dihydroxy-eicosatrienoic acids (DHETs) and reduces beneficial cardiovascular properties of EETs. Thus, the present work is aimed at identification of potential leads as sEH inhibitors which will sustain the beneficial properties of EETs in vivo. PubChem and ZINC databases were screened for drug-like compounds based on Lipinski’s rule of five and in silico toxicity filters. The binding potential of the drug-like compounds with sEH was explored using molecular docking. The top ranked lead (ZINC23099069) showed higher GOLD score compared with that of the control, 12-(3-adamantan-1-yl-ureido)-dodecanoic acid butyl ester (AUDA-BE) and displayed two hydrogen bonds with Tyr383 and His420 and eleven residues involved in hydrophobic interactions with sEH. The apo_sEH and sEH_ZINC23099069 complex showed stable trajectories during 20 ns time scale of molecular dynamics (MD) simulation. Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) binding free energy analysis showed that electrostatic energy is the driving energy component for interaction of the lead with sEH. These results demonstrate ZINC23099069 to be a promising drug candidate as sEH inhibitor against atherosclerosis instead of the present urea-based inhibitors.
      Graphical abstract image

      PubDate: 2018-03-08T13:10:32Z
      DOI: 10.1016/j.compbiolchem.2018.02.019
      Issue No: Vol. 74 (2018)
  • Computational analysis for the determination of deleterious nsSNPs in
           human MTHFR gene
    • Authors: Mansi Desai; J.B. Chauhan
      Pages: 20 - 30
      Abstract: Publication date: June 2018
      Source:Computational Biology and Chemistry, Volume 74
      Author(s): Mansi Desai, J.B. Chauhan
      Methylenetetrahydrofolate reductase (MTHFR) is a key enzyme involved in folate metabolism and plays a central role in DNA methylation and biosynthesis. MTHFR mutations may alter the cellular folate supply which in turn affects nucleic acid synthesis, DNA methylation and chromosomal damage. The identification of number of SNPs in the human genome growing nowadays and hence, the evaluation of functional & structural consequences of these SNPs is very laborious by means of experimental analysis. Therefore, in the present study, recently developed various computational algorithms have been used which can predict the functional and structural consequences of the SNPs. Various computational tools like SIFT, PolyPhen2, PROVEAN, SNAP2, nsSNPAnalyzer, SNPs&GO, PhD-SNP, PMut, I-Mutant, iPTREE-STAB and MUpro were used to predict most deleterious SNPs. Additionally, ConSurf was used to find amino acids conservation and NCBI conserved domain search tool to find conserved domains in MTHFR. Post translational modification sites were predicted using ModPred. SPARKS-X was used to generate 3D structure of the native and mutant MTHFR protein, ModRefiner for further refinement, Varify3D and RAMPAGE to validate structure. Ligand binding sites were predicted using FTsite, RaptorX binding and COACH. Three SNPs i.e. R157Q, L323P and W500C predicted the most deleterious in all the tools used for functional and stability analysis. Moreover, both residues R157, L323 and W500 were predicted highly conserved, buried and structural residues by ConSurf. Post translational modification sites were also predicted at R157 and W500. The ligand binding sites were predicted at R157, L323 and W500.
      Graphical abstract image

      PubDate: 2018-03-08T13:10:32Z
      DOI: 10.1016/j.compbiolchem.2018.02.022
      Issue No: Vol. 74 (2018)
  • QM/MM reveals the sequence of substrate binding during OPRT action
    • Authors: N.N. Subrahmanyeswara Rao; Parag A. Deshpande
      Pages: 31 - 38
      Abstract: Publication date: Available online 24 February 2018
      Source:Computational Biology and Chemistry
      Author(s): N.N. Subrahmanyeswara Rao, Parag A. Deshpande
      Computational investigation of orotate phosphoribosyltransferase (OPRT) action, an enzymatic reaction between phosphoribosyl pyrophosphate (PRPP) and orotic acid (OA) to yield orotidine 5’-monophosphate (OMP), was carried out. Insights into the pathways of the substrate attack step of the reaction were developed under the quantum mechanics/molecular mechanics framework with S. cerevisiae strain as the representative enzyme bearer. Four pathways were proposed for PRPP and OA binding differing in the sequence of PRPP, OA and Mg2+ ion complexation with OPRT. The formation of Mg2+-OPRT complex was accompanied by a small energy change while the largest stabilization was observed for the formation of Mg2+-PRPP complex supporting the experimental observation of Mg2+-PRPP complex as the true substrate for the reaction. Formation of PRPP-OPRT complex was found to be energetically not probable rendering the pathway requiring Mg2+-OA complex not probable. Further, PRPP migration towards the active site was found to be energetically not favoured rendering the pathway involving Mg2+-OA complexation improbable. Migration of OA and Mg2+-PRPP complex towards the active site was found to be energetically probable with a large stabilization of the system when Mg2+-PRPP complex bound to the OA-OPRT complex. This conclusively proved the sequential binding of OA and Mg2+-PRPP complexes during OPRT action.
      Graphical abstract image Highlights

      PubDate: 2018-02-26T09:16:25Z
      DOI: 10.1016/j.compbiolchem.2018.02.020
      Issue No: Vol. 74 (2018)
  • POAP: A GNU Parallel based multithreaded pipeline of Open Babel and
           AutoDock suite for boosted High Throughput Virtual Screening
    • Authors: A. Samdani; Umashankar Vetrivel
      Pages: 39 - 48
      Abstract: Publication date: Available online 1 March 2018
      Source:Computational Biology and Chemistry
      Author(s): A. Samdani, Umashankar Vetrivel
      High throughput virtual screening plays a crucial role in hit identification during the drug discovery process. With the rapid increase in the chemical libraries, virtual screening process becomes computationally challenging, thereby posing a demand for efficiently parallelized software pipelines. Here we present a GNU Parallel based pipeline-POAP that is programmed to run Open Babel and AutoDock suite under highly optimized parallelization. The ligand preparation module is a unique feature in POAP, as it offers extensive options for geometry optimization, conformer generation, parallelization and also quarantines erroneous datasets for seamless operation. POAP also features multi receptor docking that can be utilized for comparative virtual screening and drug repurposing studies. As demonstrated using different structural datasets, POAP proves to be an efficient pipeline that enables high scalability, seamless operability, dynamic file handling and optimal utilization of CPU’s for computationally demanding tasks. POAP is distributed freely under GNU GPL license and can be downloaded at
      Graphical abstract image

      PubDate: 2018-03-08T13:10:32Z
      DOI: 10.1016/j.compbiolchem.2018.02.012
      Issue No: Vol. 74 (2018)
  • Design and screening of syringic acid analogues as BAX activators-An in
           silico approach to discover “BH3 mimetics”
    • Authors: Srinivasulu Cheemanapalli; Anuradha C.M.; Suresh Babu Pakala; Suresh Kumar Chitta
      Pages: 49 - 62
      Abstract: Publication date: June 2018
      Source:Computational Biology and Chemistry, Volume 74
      Author(s): Srinivasulu Cheemanapalli, Anuradha C.M., Suresh Babu Pakala, Suresh Kumar Chitta
      Although BAX, which is a molecular hit squad that incentive apoptosis was found to be an attractive emerging target for anticancer agents. The molecular mechanism of small molecules/peptides involved in the BAX activation was remain unknown. The present focus of the study is to identification and development of novel molecules which are precisely activates BAX mediated apoptosis. In this process we identified some syringic acid analogues associated with the BAX hydrophobic groove by a virtual-screen approach. Results from the docking studies revealed that, SA1, SA9, SA10, SA14 and SA21 analogues have shown good interaction with BAX trigger site, of which SA10 and SA14 bound specifically with Lys21 at α1 helix of BAX, a critical residue involved in BAX activation. All docking calculations of SA analogues were compared with clinically tested BH3 mimetics. In this entire in silico study, SA analogous have performed an ideal binding interactions with BAX compared to BH3 mimetics. Further, in silico point mutation of BAX-Lys21 to Glu21 resulted in structural change in BAX and showed reduced binding energy and hydrogen bond interactions of the selected ligands. Based on these findings, we propose that virtual screening and mutation analysis of BAX is found to be the critical advance method towards the discovery of novel anticancer therapeutics.
      Graphical abstract image

      PubDate: 2018-03-20T11:08:48Z
      DOI: 10.1016/j.compbiolchem.2018.03.003
      Issue No: Vol. 74 (2018)
  • Elucidation of Chemosensitization Effect of Acridones in Cancer Cell
           lines: Combined Pharmacophore Modeling, 3D QSAR, and Molecular Dynamics
    • Authors: Deepak Reddy Gade; Amareswararao Makkapati; Rajesh Babu Yarlagadda; Godefridus J. Peters; B.S. Sastry; V.V.S. Rajendra Prasad
      Pages: 63 - 75
      Abstract: Publication date: Available online 24 February 2018
      Source:Computational Biology and Chemistry
      Author(s): Deepak Reddy Gade, Amareswararao Makkapati, Rajesh Babu Yarlagadda, Godefridus J. Peters, B.S. Sastry, V.V.S. Rajendra Prasad
      Overexpression of P-glycoprotein (P-gp) leads to the emergence of multidrug resistance (MDR) in cancer treatment. Acridones have the potential to reverse MDR and sensitize cells. In the present study, we aimed to elucidate the chemosensitization potential of acridones by employing various molecular modelling techniques. Pharmacophore modeling was performed for the dataset of chemosensitizing acridones earlier proved for cytotoxic activity against MCF7 breast cancer cell line. Gaussian-based QSAR studies also performed to predict the favored and disfavored region of the acridone molecules. Molecular dynamics simulations were performed for compound 10 and human P-glycoprotein (obtained from Homology modeling). An efficient pharmacophore containing 2 hydrogen bond acceptors and 3 aromatic rings (AARRR.14) was identified. NCI 2012 chemical database was screened against AARRR.14 CPH and identified 25 best-fit molecules. Potential regions of the compound were identified through Field (Gaussian) based QSAR. Regression analysis of atom-based QSAR resulted in r2 of 0.95 and q2 of 0.72, whereas, regression analysis of field-based QSAR resulted in r2 of 0.92 and q2 of 0.87 along with r2 cv as 0.71. The fate of the acridone molecule (compound 10) in the P-glycoprotein environment is analyzed through analyzing the conformational changes occurring during the molecular dynamics simulations. Combined data of different in silico techniques provided basis for deeper understanding of structural and mechanistic insights of interaction phenomenon of acridones with P-glycoprotein and also as strategic basis for designing more potent molecules for anti-cancer and multidrug resistance reversal activities.
      Graphical abstract image

      PubDate: 2018-02-26T09:16:25Z
      DOI: 10.1016/j.compbiolchem.2018.02.014
      Issue No: Vol. 74 (2018)
  • Statistical methods to detect novel genetic variants using publicly
           available GWAS summary data
    • Authors: Bin Guo; Baolin Wu
      Pages: 76 - 79
      Abstract: Publication date: Available online 1 March 2018
      Source:Computational Biology and Chemistry
      Author(s): Bin Guo, Baolin Wu
      We propose statistical methods to detect novel genetic variants using only genome-wide association studies (GWAS) summary data without access to raw genotype and phenotype data. With more and more summary data being posted for public access in the post GWAS era, the proposed methods are practically very useful to identify additional interesting genetic variants and shed lights on the underlying disease mechanism. We illustrate the utility of our proposed methods with application to GWAS meta-analysis results of fasting glucose from the international MAGIC consortium. We found several novel genome-wide significant loci that are worth further study.

      PubDate: 2018-03-08T13:10:32Z
      DOI: 10.1016/j.compbiolchem.2018.02.016
      Issue No: Vol. 74 (2018)
  • QM/MM Analysis of Effect of Divalent Metal Ions on OPRT Action
    • Authors: N.N. Subrahmanyeswara Rao; Parag A. Deshpande
      Pages: 80 - 85
      Abstract: Publication date: Available online 8 March 2018
      Source:Computational Biology and Chemistry
      Author(s): N.N. Subrahmanyeswara Rao, Parag A. Deshpande
      The role of Mg2+ cofactor in orotate phosphoribosyltransferase (OPRT) catalyzed synthesis of orotidine monophosphate (OMP) from phosphoribosyl pyrophosphate (PRPP) and orotate (OA) in substrate binding and the influence of the identity of the divalent metal ion on the reaction mechanism were addressed in this study using quantum mechanics/molecular mechanics framework. Energetics of migration and binding of different substrate complexes in the active site cavity was established. A quantitative analysis of various processes indicated the reaction pathway to consist of complexation of Mg2+ with PRPP, migration of Mg2+-PRPP and OA towards the active site, binding of OA to OPRT, and binding of Mg2+-PRPP complex to OA-OPRT complex. The mechanism of the reaction was unaltered by the change in the identity of divalent metal ion. Experimentally reported inhibiting character of Co2+ was explained on the basis of large Co2+-PRPP binding and migration energies. Mg2+, Ca2+, Mn2+, Co2+ and Zn2+ ions were screened computationally to assess their inhibiting/activating characteristics. Trends obtained by our computational investigations were in correspondence with experimentally reported trends.
      Graphical abstract image Highlights

      PubDate: 2018-03-08T13:10:32Z
      DOI: 10.1016/j.compbiolchem.2018.03.004
      Issue No: Vol. 74 (2018)
  • Temperature effect on the structure and conformational fluctuations in two
           zinc knuckles from the mouse mammary tumor virus
    • Authors: Nedjoua Drici; Abdelghani Mohamed Krallafa
      Pages: 86 - 93
      Abstract: Publication date: June 2018
      Source:Computational Biology and Chemistry, Volume 74
      Author(s): Nedjoua Drici, Abdelghani Mohamed Krallafa
      Zinc fingers are small protein domains in which zinc plays a structural role, contributing to the stability of the zinc–peptide complex. Zinc fingers are structurally diverse and are present in proteins that perform a broad range of functions in various cellular processes, such as replication and repair, transcription and translation, metabolism and signaling, cell proliferation, and apoptosis. Zinc fingers typically function as interaction modules and bind to a wide variety of compounds, such as nucleic acids, proteins, and small molecules. In this study, we investigated the structural properties, in solution, of the proximal and distal zinc knuckles of the nucleocapsid (NC) protein from the mouse mammary tumor virus (MMTV) (MMTV NC). For this purpose, we performed a series of molecular dynamics simulations in aqueous solution at 300 K, 333 K, and 348 K. The temperature effect was evaluated in terms of root mean square deviation of the backbone atoms and root mean square fluctuation of the coordinating residue atoms. The stability of the zinc coordination sphere was analyzed based upon the time profile of the interatomic distances between the zinc ions and the chelator atoms. The results indicate that the hydrophobic character of the proximal zinc finger is dominant at 333 K. The low mobility of the coordinating residues suggests that the strong electrostatic effect exerted by the zinc ion on its coordinating residues is not influenced by the increase in temperature. The evolution of the structural parameters of the coordination sphere of the distal zinc finger at 300 K gives us a reasonable picture of the unfolding pathway, as proposed by Bombarda and coworkers (Bombarda et al., 2005), which can predict the binding order of the four conserved ligand-binding residues. Our results support the conclusion that the structural features can vary significantly between the two zinc knuckles of MMTV NC.
      Graphical abstract image

      PubDate: 2018-03-20T11:08:48Z
      DOI: 10.1016/j.compbiolchem.2018.03.005
      Issue No: Vol. 74 (2018)
  • A Ternary Complex Model of Sirtuin4-NAD+-Glutamate Dehydrogenase
    • Authors: Yusuke Kato; Hiroshi Kihara; Kiyoshi Fukui; Masaki Kojima
      Pages: 94 - 104
      Abstract: Publication date: Available online 10 March 2018
      Source:Computational Biology and Chemistry
      Author(s): Yusuke Kato, Hiroshi Kihara, Kiyoshi Fukui, Masaki Kojima
      Sirtuin4 (Sirt4) is one of the mammalian homologues of Silent information regulator 2 (Sir2), which promotes the longevity of yeast, C. elegans, fruit flies and mice. Sirt4 is localized in the mitochondria, where it contributes to preventing the development of cancers and ischemic heart disease through regulating energy metabolism. The ADP-ribosylation of glutamate dehydrogenase (GDH), which is catalyzed by Sirt4, downregulates the TCA cycle. However, this reaction mechanism is obscure, because the structure of Sirt4 is unknown. We here constructed structural models of Sirt4 by homology modeling and threading, and docked nicotinamide adenine dinucleotide+ (NAD+) to Sirt4. In addition, a partial GDH structure was docked to the Sirt4-NAD+ complex model. In the ternary complex model of Sirt4-NAD+-GDH, the acetylated lysine 171 of GDH is located close to NAD+. This suggests a possible mechanism underlying the ADP-ribosylation at cysteine 172, which may occur through a transient intermediate with ADP-ribosylation at the acetylated lysine 171. These results may be useful in designing drugs for the treatment of cancers and ischemic heart disease.
      Graphical abstract image

      PubDate: 2018-03-20T11:08:48Z
      DOI: 10.1016/j.compbiolchem.2018.03.006
      Issue No: Vol. 74 (2018)
  • In silico modelling of azole derivatives with tyrosinase inhibition
           ability: Application of the models for activity prediction of new
    • Authors: Biplab De; Indrani Adhikari; Ashis Nandy; Achintya Saha; Binoy Behari Goswami
      Pages: 105 - 114
      Abstract: Publication date: Available online 10 March 2018
      Source:Computational Biology and Chemistry
      Author(s): Biplab De, Indrani Adhikari, Ashis Nandy, Achintya Saha, Binoy Behari Goswami
      Tyrosinase is a metal containing multifunctional enzymes found in animals, fruits and vegetables and constitutes the primary cause for diseases resulting from overproduction of melanin as well as for browning of fruits. Inhibitors of the enzyme have thus gained increased importance in food and cosmetic industry. In the present work, a group of azole derivatives with tyrosinase inhibitory activity were explored to analyse the prime structural attributes of the potent inhibitors. In silico models have been developed in order to have a close insight regarding features of the molecular fragments that may affect the activity of the molecules conducively. The biological pharmacophore of the inhibitors that accounts for their interaction with the tyrosinase enzyme has been ascertained based on the development of a 3D pharmacophore model. The models thus developed were subsequently utilised for screening a set of compounds that were previously synthesised in-house and were reported to possess antioxidant activity. The final selection of active molecules in the screening process was done based on the docking interactions of the molecules with the tyrosinase enzyme and assessment of their degree of binding to the protein. Thus the developed models have been successfully utilised for identifying active compounds from a series of untested molecules.
      Graphical abstract image

      PubDate: 2018-03-20T11:08:48Z
      DOI: 10.1016/j.compbiolchem.2018.03.007
      Issue No: Vol. 74 (2018)
  • LQTA-R: A new 3D-QSAR methodology applied to a set of DGAT1 inhibitors
    • Authors: Rajesh B. Patil; Euzebio G. Barbosa; Jaiprakash N. Sangshetti; Sanjay D. Sawant; Vishal P. Zambre
      Pages: 123 - 131
      Abstract: Publication date: Available online 1 March 2018
      Source:Computational Biology and Chemistry
      Author(s): Rajesh B. Patil, Euzebio G. Barbosa, Jayprakash N. Sangshetti, Sanjay D. Sawant, Vishal P. Zambre
      The rapid advances in computational methods for the drug design have resulted in the accurate predictions of biological activities of ligands with or without the availability of enzyme structures. 3D-QSAR is one of the computational methods used for such purpose. Currently, freely available 3D-QSAR methods suffer the limitations like complex methodologies, difficulty in the analysis of results, applying the statistical methods and validations of models built. Present work describes simple and novel 3D-QSAR methodology, which uses bash scripts LQTA_R_LJ, LQTA_R_QQ and LQTA_R_HB using freely available R statistical program. These scripts then generate Leenard-Jones, Coulomb and Hydrogen bond descriptors. These descriptors provide the steric 3D property, electrostatic property and hydrogen bond formation capacity respectively. These scripts have been tested for the set of DGAT1 inhibitors and results showed that the 3D-QSAR models built have better predictive abilities in terms of R2 0.735, Q2loo 0.635 and R2ext 0.715. The 3D-QSAR model suggested that the substitutions of the alkyl group at the oxadiazolyl ring at the 6th position of the pyrrolo-pyridazine ring is undesirable, on the contrary, substituted phenyl ring at 7th position is responsible for the improved DGAT1 inhibitory activity. The analysis also suggested that 6th position could be substituted with the oxadiazolyl ring or analogous heterocyclic rings, where the 3rd position of such heterocyclic rings substituted with rigid hydrophobic substitute can improve DGAT1 activity.
      Graphical abstract image

      PubDate: 2018-03-08T13:10:32Z
      DOI: 10.1016/j.compbiolchem.2018.02.021
      Issue No: Vol. 74 (2018)
  • A survey of recently emerged genome-wide computational enhancer predictor
    • Authors: Leonard Whye Kit Lim; Hung Hui Chung; Yee Ling Chong; Nung Kion Lee
      Pages: 132 - 141
      Abstract: Publication date: Available online 16 March 2018
      Source:Computational Biology and Chemistry
      Author(s): Leonard Whye Kit Lim, Hung Hui Chung, Yee Ling Chong, Nung Kion Lee
      The race for the discovery of enhancers at a genome-wide scale has been on since the commencement of next generation sequencing decades after the discovery of the first enhancer, SV40. A few enhancer-predicting features such as chromatin feature, histone modifications and sequence feature had been implemented with varying success rates. However, to date, there is no consensus yet on the single enhancer marker that can be employed to ultimately distinguish and uncover enhancers from the enormous genomic regions. Many supervised, unsupervised and semi-supervised computational approaches had emerged to complement and facilitate experimental approaches in enhancer discovery. In this review, we placed our focus on the recently emerged enhancer predictor tools that work on general enhancer features such as sequences, chromatin states and histone modifications, eRNA and of multiple feature approach. Comparisons of their prediction methods and outcomes were done across their functionally similar counterparts. We provide some recommendations and insights for future development of more comprehensive and robust tools.
      Graphical abstract image

      PubDate: 2018-03-20T11:08:48Z
      DOI: 10.1016/j.compbiolchem.2018.03.019
      Issue No: Vol. 74 (2018)
  • An efficient strategy for identifying cancer-related key genes based on
           graph entropy
    • Authors: Wei Zhang; Shu-Lin Wang
      Pages: 142 - 148
      Abstract: Publication date: June 2018
      Source:Computational Biology and Chemistry, Volume 74
      Author(s): Wei Zhang, Shu-Lin Wang
      Gene networks are beneficial to identify functional genes that are highly relevant to clinical outcomes. Most of the current methods require information about the interaction of genes or proteins to construct genetic network connection. However, the conclusion of these methods may be bias because of the current incompleteness of human interactome. In this paper, we propose an efficient strategy to use gene expression data and gene mutation data for identifying cancer-related key genes based on graph entropy (iKGGE). Firstly, we construct a gene network using only gene expression data based on the sparse inverse covariance matrix, then, cluster genes use the algorithm of parallel maximal cliques for quickly obtaining a series of subgraphs, and at last, we introduce a novel metric that combine graph entropy and the influence of upstream gene mutations information to measure the impact factors of genes. Testing of the three available cancer datasets shows that our strategy can effectively extract key genes that may play distinct roles in tumorigenesis, and the cancer patient risk groups are well predicted based on key genes.
      Graphical abstract image

      PubDate: 2018-04-15T06:22:49Z
      DOI: 10.1016/j.compbiolchem.2018.03.022
      Issue No: Vol. 74 (2018)
  • Multi-Dimensional Scaling based grouping of known complexes and
           intelligent protein complex detection
    • Authors: Zia ur Rehman; Adnan Idris; Asifullah Khan
      Pages: 149 - 156
      Abstract: Publication date: June 2018
      Source:Computational Biology and Chemistry, Volume 74
      Author(s): Zia ur Rehman, Adnan Idris, Asifullah Khan
      Protein–Protein Interactions (PPI) play a vital role in cellular processes and are formed because of thousands of interactions among proteins. Advancements in proteomics technologies have resulted in huge PPI datasets that need to be systematically analyzed. Protein complexes are the locally dense regions in PPI networks, which extend important role in metabolic pathways and gene regulation. In this work, a novel two-phase protein complex detection and grouping mechanism is proposed. In the first phase, topological and biological features are extracted for each complex, and prediction performance is investigated using Bagging based Ensemble classifier (PCD-BEns). Performance evaluation through cross validation shows improvement in comparison to CDIP, MCode, CFinder and PLSMC methods Second phase employs Multi-Dimensional Scaling (MDS) for the grouping of known complexes by exploring inter complex relations. It is experimentally observed that the combination of topological and biological features in the proposed approach has greatly enhanced prediction performance for protein complex detection, which may help to understand various biological processes, whereas application of MDS based exploration may assist in grouping potentially similar complexes.

      PubDate: 2018-04-15T06:22:49Z
      DOI: 10.1016/j.compbiolchem.2018.03.023
      Issue No: Vol. 74 (2018)
  • Haemostatic effects of latex from Croton sparsiflorus Morang, in vitro, in
           vivo, in silico approaches
    • Authors: M.C. Kamaraj; S. Mohan Raj; D. Palani Selvam; S. Subashchandrabose; A. Kalaiselvan
      Pages: 157 - 166
      Abstract: Publication date: June 2018
      Source:Computational Biology and Chemistry, Volume 74
      Author(s): M.C. Kamaraj, S. Mohan Raj, D. Palani Selvam, S. Subashchandrabose, A. Kalaiselvan
      The present investigations are phytochemical screening of Latex aqueous (Laq) extract of C. sparsiflorus and study its role in homeostasis. It is being traditionally used for fresh cuts to stop bleeding immediately. To know the contents of extract, the quantitative phytochemical analysis were performed it showed the contents such as saponins (15.2%), alkaloids (7.61%), phenols (0.62%), tannins (1.1%), and flavonoids (0.224%). The in vitro and in vivo blood clotting mechanism was observed in Wister albino rats to understand the blood clotting activity. The in vitro cytotoxicity assay was performed by 3T3L1 cell lines evaluated by Laq extract of C. sparsiflorus to determine the toxic effects of the extract. The gas chromatographic and liquid chromatographic mass spectra (GCMS and LCMS) were observed there were three compounds obtained namely, 1) methyl-hexafuranoside, 2) cumarandione, and 3) crotonosine, in addition to that the NMR (1H and 13C) elemental analysis, FT-IR (4000–400 cm−1) and UV–vis (800–200 nm) spectra were also recorded in aqueous solution. The molecular docking studies performed, in which the blood clotting factors have a potential interaction with crotonosine. This in-silico study demonstrates the interactions of active components of C. sparsiflorus with blood clotting factors. Furthermore, since the crotonosine compound has more blood clotting factor the molecular structure was treated with density functional theory calculation (DFT) to understand the optimized geometry, vibrational behaviour and electronic excitation states.
      Graphical abstract image

      PubDate: 2018-04-15T06:22:49Z
      DOI: 10.1016/j.compbiolchem.2018.03.025
      Issue No: Vol. 74 (2018)
  • In-silico evidences for binding of Glucokinase activators to EGFR C797S to
           overcome EGFR resistance obstacle with mutant-selective allosteric
    • Authors: Harun Patel; Rahul Pawara; Sanjay Surana
      Pages: 167 - 189
      Abstract: Publication date: June 2018
      Source:Computational Biology and Chemistry, Volume 74
      Author(s): Harun Patel, Rahul Pawara, Sanjay Surana
      The tyrosine kinase inhibitors (TKI) against epidermal growth factor receptor (EGFR) are generally utilized as a part of patients with non-small cell lung carcinoma (NSCLC). However, EGFR T790M mutation results in resistance to most clinically available EGFR TKIs. Third-generation EGFR TKIs against the T790M mutation has been in active clinical development to triumph the resistance problem; they covalently bind with conserved Cys797 inside the EGFR active site, offering both potency and kinase-selectivity. Third generation drugs target C797, which makes the C797S resistance mutation more subtle. EGFR C797S mutation was accounted to be a main mechanism of resistance to the third-generation inhibitors. The C797S mutation gives off an impression of being an ideal target for conquering the acquired resistance to the third generation inhibitors. We have performed structure based-virtual screening strategies for binding of glucokinase activator to EGFR C797S, which can overcome EGFR resistance impediment with mutant-selective allosteric inhibition towards all kinds of mutant EGFR (T790M, L858R, TMLR) and WT EGFR. The final filter of Lipinski’s Rule of Five, Jargan’s Rule of Three and in silico ADME predictions gave 23 hits, which conform to Lipinski’s rule and Jorgensen’s rule and all their pharmacokinetic parameters are inside the appropriate range characterized for human use, in this manner demonstrating their potential as a drug-like molecule.
      Graphical abstract image

      PubDate: 2018-04-15T06:22:49Z
      DOI: 10.1016/j.compbiolchem.2018.03.026
      Issue No: Vol. 74 (2018)
  • In-vitro evaluation and in-silico studies applied on newly synthesized
           amide derivatives of N-phthaloylglycine as Butyrylcholinesterase (BChE)
    • Authors: Samreen Begum; Shaikh Sirajuddin Nizami; Uzma Mahmood; Summyia Masood; Sahar Iftikhar; Summayya Saied
      Pages: 212 - 217
      Abstract: Publication date: June 2018
      Source:Computational Biology and Chemistry, Volume 74
      Author(s): Samreen Begum, Shaikh Sirajuddin Nizami, Uzma Mahmood, Summyia Masood, Sahar Iftikhar, Summayya Saied
      Amide derivatives of N-phthaloylglycine were synthesized under Schotten Baumann reaction condition. The structures of synthesized compounds (4a–d) were characterized by using FTIR, 1HNMR and EI-MS. The compounds were evaluated for their in-vitro Butyrylcholinesterase inhibition and all of them exhibited good activity against this enzyme. Compound 4a (IC50  = 6.5 ± 0.1) was found to be most potent compared with the reference compound Galantamine (IC50  = 6.6 ± 0.00038) and the other compounds (4b,4c,4d) were also possess that activity and hence can be employed for the discovery of lead compounds against Alzheimer’s disease. The depth analysis of the binding mechanism of these newly synthesized compounds inside the binding gorge of BChE, an in silico technique, molecular docking was performed. All the compounds were found to be well accommodated within the binding pocket of BChE. Compounds 4a, 4b and 4c showed hydrogen bonding interaction with binding site residue TYR332. Moreover, hydrophobic and π–π interaction assisted the compounds to attain their enzyme inhibitory activity. These theoretical studies showed significant correlation with experimental results.
      Graphical abstract image

      PubDate: 2018-04-15T06:22:49Z
      DOI: 10.1016/j.compbiolchem.2018.04.003
      Issue No: Vol. 74 (2018)
  • Computational study of molecular electrostatic potential, docking and
           dynamics simulations of gallic acid derivatives as ABL inhibitors
    • Authors: K.R. Raghi; D.R. Sherin; M.J. Saumya; P.S. Arun; V.N. Sobha; T.K. Manojkumar
      Pages: 239 - 246
      Abstract: Publication date: June 2018
      Source:Computational Biology and Chemistry, Volume 74
      Author(s): K.R. Raghi, D.R. Sherin, M.J. Saumya, P.S. Arun, V.N. Sobha, T.K. Manojkumar
      Chronic myeloid leukemia (CML), a hematological malignancy arises due to the spontaneous fusion of the BCR and ABL gene, resulting in a constitutively active tyrosine kinase (BCR-ABL). Pharmacological activity of Gallic acid and 1,3,4-Oxadiazole as potential inhibitors of ABL kinase has already been reported. Objective of this study is to evaluate the ABL kinase inhibitory activity of derivatives of Gallic acid fused with 1,3,4-Oxadiazole moieties. Attempts have been made to identify the key structural features responsible for drug likeness of the Gallic acid and the 1,3,4-Oxadiazole ring using molecular electrostatic potential maps (MESP). To investigate the inhibitory activity of Gallic acid derivatives towards the ABL receptor, we have applied molecular docking and molecular dynamics (MD) simulation approaches. A comparative study was performed using Bosutinib as the standard which is an approved CML drug acting on the same receptor. Furthermore, the novel compounds designed and reported here in were evaluated for ADME properties and the results indicate that they show acceptable pharmacokinetic properties. Accordingly these compounds are predicted to be drug like with low toxicity potential.
      Graphical abstract image

      PubDate: 2018-04-15T06:22:49Z
      DOI: 10.1016/j.compbiolchem.2018.04.001
      Issue No: Vol. 74 (2018)
  • The role of the arginine residue in site RC for the analgesic activity of
           the recombinant Chinese scorpion Buthus martensii Karsch, BmK AGP-SYPU1
    • Authors: Yong Cui; Yao Wang; Xuelin Wang; Zhengwei Zhang; Jinghai Zhang; Yongshan Zhao
      Pages: 247 - 252
      Abstract: Publication date: June 2018
      Source:Computational Biology and Chemistry, Volume 74
      Author(s): Yong Cui, Yao Wang, Xuelin Wang, Zhengwei Zhang, Jinghai Zhang, Yongshan Zhao
      Scorpion venom is composed of a large number of bioactive peptides which display important pharmacological activities. In this study we have carried out a study of the functional role of the arginine residue at position 58 in the site RC comprising the reverse turn (8–12) and C-terminal residues 58–64. A polymerase chain reaction was used to substitute this arginine residue with a single amino acid such as alanine, glycine and lysine. The mutants were expressed in soluble form in E. coli, and purified by affinity chromatography. After target peptide purity identification, the recombinant peptides underwent a circular dichroism analysis and a study of their analgesic activity in mice. The results indicated that a single residue modification can affect the pharmacological activity. Our efforts establish a sound basis for further study of the structure-function determinants of the analgesic effect.
      Graphical abstract image

      PubDate: 2018-04-15T06:22:49Z
      DOI: 10.1016/j.compbiolchem.2018.04.007
      Issue No: Vol. 74 (2018)
  • Interactions of 2-phenyl-benzotriazole xenobiotic compounds with human
           Cytochrome P450-CYP1A1 by means of docking, molecular dynamics simulations
           and MM-GBSA calculations
    • Authors: Karel Mena-Ulecia; Desmond MacLeod-Carey
      Pages: 253 - 262
      Abstract: Publication date: Available online 7 April 2018
      Source:Computational Biology and Chemistry
      Author(s): Karel Mena-Ulecia, Desmond MacLeod-Carey
      2-phenyl-benzotriazole xenobiotic compounds (PBTA-4, PBTA-6, PBTA-7 and PBTA-8) that were previously isolated and identified in waters of the Yodo river, in Japan (Nukaya et al., 2001; Ohe et al., 2004; Watanabe et al., 2001) were characterized as powerful pro-mutagens. In order to predict the activation mechanism of these pro-mutagens, we designed a computational biochemistry protocol, which includes, docking experiments, molecular dynamics simulations and free energy decomposition calculations to obtain information about the interaction of 2-phenyl-benzotriazole molecules into the active center of cytochrome P450-CYP1A1 (CYP1A1). Molecular docking calculations using AutoDock Vina software shows that PBTAs are proportionally oriented in the pocket of CYP1A1, establishing π-π stacking attractive interactions between the triazole group and the Phe224, as well as, the hydrogen bonds of the terminal NH2 over the benzotriazole units with the Asn255 and Ser116 amino acids. Molecular dynamics simulations using NAMD package showed that these interactions are stable along 100.0 ns of trajectories. Into this context, free binding energy calculations employing the MM-GBSA approach, shows that some differences exists among the interaction of PBTAs with CYP1A1, regarding the solvation, electrostatic and van der Waals interaction energy components. These results suggest that PBTA molecules might be activated by CYP1A1. Thus, enhancing their mutagenicity when compared with the pro-mutagen parent species.
      Graphical abstract image

      PubDate: 2018-04-15T06:22:49Z
      DOI: 10.1016/j.compbiolchem.2018.04.004
      Issue No: Vol. 74 (2018)
  • Computational insights into β-site amyloid precursor protein enzyme 1
           (BACE1) inhibition by tanshinones and salvianolic acids from Salvia
           miltiorrhiza via molecular docking simulations
    • Authors: Ting Yu; Pradeep Paudel; Su Hui Seong; Jeong Ah Kim; Hyun Ah Jung; Jae Sue Choi
      Pages: 273 - 285
      Abstract: Publication date: Available online 13 April 2018
      Source:Computational Biology and Chemistry
      Author(s): Ting Yu, Pradeep Paudel, Su Hui Seong, Jeong Ah Kim, Hyun Ah Jung, Jae Sue Choi
      The rhizome of Salvia miltiorrhiza has emerged as a rich source of natural therapeutic agents, and its several compounds are supposed to exhibit favorable effects on Alzheimer’s disease (AD). The present work investigate the anti-AD potentials of 12 tanshinones, three salvianolic acids and three caffeic acid derivatives from S. miltiorrhiza via the inhibition of β-site amyloid precursor protein cleaving enzyme 1 (BACE1). Among the tested compounds, deoxyneocryptotanshinone (1), salvianolic acid A (13) and salvianolic acid C (15) displayed good inhibitory effect on BACE1 with IC50 values of 11.53 ± 1.13, 13.01 ± 0.32 and 9.18 ± 0.03 μM, respectively. Besides this, enzyme kinetic analysis on BACE1 revealed 13, a competitive type inhibitor while 1 and 15 showed mixed-type inhibition. Furthermore, molecular docking simulation displayed negative binding energies (AutoDock 4.2.6 = −10.0 to −7.1 kcal/mol) of 1, 13, and 15 for BACE1, indicating these compounds bound tightly to the active site of the enzyme with low energy and high affinity. The results of the present study clearly demonstrate that S. miltiorrhiza and its constituents have potential anti-AD activity and can be used as a therapeutic agent for the treatment of AD.
      Graphical abstract image

      PubDate: 2018-04-15T06:22:49Z
      DOI: 10.1016/j.compbiolchem.2018.04.008
      Issue No: Vol. 74 (2018)
    • Authors: GW McElfresh; Christos Deligkaris
      Pages: 286 - 293
      Abstract: Publication date: Available online 5 April 2018
      Source:Computational Biology and Chemistry
      Author(s): GW McElfresh, Christos Deligkaris
      DNA interacts with small molecules, from water to endogenous reactive oxygen and nitrogen species, environmental mutagens and carcinogens, and pharmaceutical anticancer molecules. Understanding and predicting the physical interactions of small molecules with DNA via docking is key not only for the comprehension of molecular-level events that lead to carcinogenesis and other diseases, but also for the rational design of drugs that target DNA. We recently validated AutoDock, a popular docking method that includes a physics-based scoring function and a Lamarckian Genetic Algorithm, for the prediction of small molecule geometries upon physical binding to DNA. In this work, we added a vibrational entropy term based on the docking frequency to the scoring function in order to improve the accuracy of the best (lowest) score geometry. We found that in four small molecule-DNA systems the inclusion of the vibrational entropy term decreased the root-mean-square-deviation from the experimental crystallographic structure. Including the entropy term also preserved the successful prediction of the binding geometry compared to the crystallographic structure for the rest of the small molecule-DNA systems. We also improved the method of creating clusters of docking geometries and emphasized the importance of the length of the search process for similar vibrational entropy terms.
      Graphical abstract image Highlights Figure 1: Histogram of RMSD [Å] distributions as predicted by AutoDock4 (AD4) and this work (AD4 + VIB). The addition of a vibrational entropy term improves the docking site predictions.

      PubDate: 2018-04-15T06:22:49Z
      DOI: 10.1016/j.compbiolchem.2018.03.027
      Issue No: Vol. 74 (2018)
  • Design, synthesis and evaluation of novel sulfonamides as potential
           anticancer agents
    • Authors: Maryna V. Kachaeva; Diana M. Hodyna; Ivan V. Semenyuta; Stepan G. Pilyo; Volodymyr M. Prokopenko; Vasyl V. Kovalishyn; Larysa O. Metelytsia; Volodymyr S. Brovarets
      Pages: 294 - 303
      Abstract: Publication date: Available online 10 April 2018
      Source:Computational Biology and Chemistry
      Author(s): Maryna V. Kachaeva, Diana M. Hodyna, Ivan V. Semenyuta, Stepan G. Pilyo, Volodymyr M. Prokopenko, Vasyl V. Kovalishyn, Larysa O. Metelytsia, Volodymyr S. Brovarets
      Based on modern literature data about biological activity of E7010 derivatives, a series of new sulfonamides as potential anticancer drugs were rationally designed by QSAR modeling methods Сlassification learning QSAR models to predict the tubulin polymerization inhibition activity of novel sulfonamides as potential anticancer agents were created using the Online Chemical Modeling Environment (OCHEM) and are freely available online on OCHEM server at A series of sulfonamides with predicted activity were synthesized and tested against 60 human cancer cell lines with growth inhibition percent values. The highest antiproliferative activity against leukemia (cell lines K-562 and MOLT-4), non-small cell lung cancer (cell line NCI-H522), colon cancer (cell lines NT29 and SW-620), melanoma (cell lines MALME-3M and UACC-257), ovarian cancer (cell lines IGROV1 and OVCAR-3), renal cancer (cell lines ACHN and UO-31), breast cancer (cell line T-47D) was found for compounds 4–9. According to the docking results the compounds 4–9 induce cytotoxicity by the disruption of the microtubule dynamics by inhibiting tubulin polymerization via effective binding into colchicine domain, similar the E7010.
      Graphical abstract image

      PubDate: 2018-04-15T06:22:49Z
      DOI: 10.1016/j.compbiolchem.2018.04.006
      Issue No: Vol. 74 (2018)
  • 3D QSAR Pharmacophore Based Virtual Screening for Identification of
           Potential Inhibitors for CDC25B
    • Authors: Ying Ma; Hong-Lian Li; Xiu-Bo Chen; Wen-Yan Jin; Hui Zhou; Ying Ma; Run-Ling Wang
      Pages: 1 - 12
      Abstract: Publication date: April 2018
      Source:Computational Biology and Chemistry, Volume 73
      Author(s): Ying Ma, Hong-Lian Li, Xiu-Bo Chen, Wen-Yan Jin, Hui Zhou, Ying Ma, Run-Ling Wang
      Owing to its fundamental roles in cell cycle phases, the cell division cycle 25B (CDC25B) was broadly considered as potent clinical drug target for cancers. In this study, 3D QSAR pharmacophore models for CDC25B inhibitors were developed by the module of Hypogen. Three methods (cost analysis, test set prediction, and Fisher’s test) were applied to validate that the models could be used to predict the biological activities of compounds. Subsequently, 26 compounds satisfied Lipinski’s rule of five were obtained by the virtual screening of the Hypo-1-CDC25B against ZINC databases. It was then discovered that 9 identified molecules had better binding affinity than a known CDC25B inhibitors-compound 1 using docking studies. The molecular dynamics simulations showed that the compound had favorable conformations for binding to the CDC25B. Thus, our findings here would be helpful to discover potent lead compounds for the treatment of cancers.
      Graphical abstract image

      PubDate: 2018-02-16T08:59:44Z
      DOI: 10.1016/j.compbiolchem.2018.01.005
      Issue No: Vol. 73 (2018)
  • Molecular dynamics studies show solvation structure of type III antifreeze
           protein is disrupted at low pH
    • Authors: Antonio Peramo
      Pages: 13 - 24
      Abstract: Publication date: April 2018
      Source:Computational Biology and Chemistry, Volume 73
      Author(s): Antonio Peramo
      Antifreeze proteins are a class of biological molecules of interest in many research and industrial applications due to their highly specialized function, but there is little information of their stability and properties under varied pH derived from computational studies. To gain novel insights in this area, we conducted molecular dynamics (MD) simulations with the antifreeze protein 1KDF at varied temperatures and pH. Water solvation and H-bond formation around specific residues – ASN14, THR18 and GLN44 – involved in its antifreeze activity were extensively studied. We found that at pH1 there was a disruption in water solvation around the basal and the ice binding surfaces of the molecule. This was induced by a small change in the secondary structure propensities of some titrable residues, particularly GLU35. This change explains the experimentally observed reduction in antifreeze activity previously reported for this protein at pH1. We also found that THR18 showed extremely low H-bond formation, and that the three antifreeze residues all had very low average H-bond lifetimes. Our results confirm long-standing assumptions that these small, compact molecules can maintain their antifreeze activity in a wide range of pH, while demonstrating the mechanism that may reduce antifreeze activity at low pH. This aspect is useful when considering industrial and commercial use of antifreeze proteins subject to extreme pH environments, in particular in food industrial applications.
      Graphical abstract image

      PubDate: 2018-02-16T08:59:44Z
      DOI: 10.1016/j.compbiolchem.2018.01.006
      Issue No: Vol. 73 (2018)
  • Interferon induced Mx protein from Indian snow trout Schizothorax
           richardsonii (Gray) lacks critical functional features unlike its
           mammalian homologues
    • Authors: Ankur Saxena; Kiran Belwal; Ankita Chauhan; Amit Pande
      Pages: 31 - 40
      Abstract: Publication date: April 2018
      Source:Computational Biology and Chemistry, Volume 73
      Author(s): Ankur Saxena, Kiran Belwal, Ankita Chauhan, Amit Pande
      Viral attack within host cells triggers the production of type I interferons and leads to the induction of interferon stimulated genes (ISGs). One of the ISG Mx, encodes type I interferon inducible GTPase that is responsible for the establishment of an anti-viral state within cells. Intriguingly, several isoforms of Mx have been reported in fish, but the structural analysis of fish Mx proteins remains unexplored. For the first time, we have identified and unraveled the molecular structure of Mx protein from Indian snow trout, Schizothorax richardsonii (Gray) a Coldwater fish that inhabits the water bodies in the sub-Himalayan region. The snow trout Mx coding region consists of 2518 nucleotides with an open reading frame (ORF) of 1854 nucleotides. It codes for a polypeptide of 617 amino acids with a predicted molecular weight of 70 kDa. In silico analysis of snow trout Mx protein revealed signature of dynamin family (LPRGTGIVTR) along with a tripartite GTP-binding domain (GDQSSGKS, DLPG, and TKPD). Homology modelling established that the Mx protein is an elongated structure with a G domain, bundle signaling element (BSE) and a GTPase effector domain (GED). Moreover, the GED of Mx contains two highly conserved leucine zippers at the COOH-terminal of the protein suggesting its structural similarity with human homologues. However, snow trout Mx lacks the essential features of its mammalian homologues questioning its functional characteristics. Further, a ligand binding site in the said protein has also been predicted adjacent to the GTPase switch within the G domain.
      Graphical abstract image

      PubDate: 2018-02-16T08:59:44Z
      DOI: 10.1016/j.compbiolchem.2017.12.011
      Issue No: Vol. 73 (2018)
  • Molecular dynamics simulation studies suggests unconventional roles of
           non-secretary laccases from enteropathogenic gut bacteria and Cryptococcus
           neoformans serotype D
    • Authors: Krishna Kant Sharma; Deepti Singh; Surender Rawat
      Pages: 41 - 48
      Abstract: Publication date: April 2018
      Source:Computational Biology and Chemistry, Volume 73
      Author(s): Krishna Kant Sharma, Deepti Singh, Surender Rawat
      Laccase in Cryptococcus neoformans is covalently linked to the carbohydrate moiety of the cell wall, which allows it to get access to the different substrates for catalyzing their oxidation and therefore plays a vital role in the virulence. The laccase gene (3.0 kb) from C. neoformans serotype D was amplified, cloned and sequenced for protein modeling, docking and simulation studies. The three dimensional homology models of laccase protein from C. neoformans and other pathogenic gut bacteria were docked with selected biomolecules like prostaglandins (PG), membrane phospholipids, neurotransmitters (serotonin) using GOLD software. The GOLDscore values of laccase from C. neoformans docked with prostaglandinH2 (59.76), prostaglandinG2 (59.45), prostaglandinE2 (60.99), phosphatidylinositol (54.95), phosphatidylcholine (46.26), phosphatidylserine (55.26), arachidonic acid (53.08) and serotonin (46.22) were similar to the laccase from enteropathogenic bacteria but showed a better binding affinity as compared to that of the non-pathogenic bacteria (e.g. Bacillus safensis, Bacillus pumilus and Bacillus subtilis). The RMSD of MD simulation study done for 25 ns using laccase protein from C. neoformans complexed with phosphatidylcholine was found to be highly stable, followed by the laccase-PGE2 and laccase-serotonin complexes. Furthermore, the binding free energy results were found to support the docking and MD simulation results. The present study implies that few candidate ligands can be intermediate substrate in the catalysis of microbial laccases, which can further play some crucial role in the cell signaling and pathogenesis of enteropathogenic gut micro flora and C. neoformans.
      Graphical abstract image

      PubDate: 2018-02-16T08:59:44Z
      DOI: 10.1016/j.compbiolchem.2018.01.010
      Issue No: Vol. 73 (2018)
  • Allosteric inhibition abrogates dysregulated LFA-1 activation: Structural
           insight into mechanisms of diminished immunologic disease
    • Authors: Maryam Abdullahi; Fisayo A. Olotu; Mahmoud E. Soliman
      Pages: 49 - 56
      Abstract: Publication date: April 2018
      Source:Computational Biology and Chemistry, Volume 73
      Author(s): Maryam Abdullahi, Fisayo A. Olotu, Mahmoud E. Soliman
      Lymphocyte Function Associated antigen-1(LFA-1) has been implicated severely in the pathophysiology of inflammatory and autoimmune diseases. Its active and inactive conformations correlate with its diseased and non-diseased state respectively. This is determined by its degree of affinity for its intrinsic ligand (ICAM) at the active site and accompanying synergistic coordination at the α7 helix. This potentiates the role of inhibitors in disrupting this interaction allosterically. Herein, we present a first account of the structural dynamics which characterizes the inhibitory effect of a novel LFA-1 antagonist, Lifitegrast (SAR1118), upon binding to the I-domain allosteric site (IDAS) using molecular dynamics simulation. Findings from this study revealed that the inhibitor stabilized the closed conformation and reversed the open conformation to a low ICAM-affinity state (closed) as evidenced by the upward movement of the α7 helix and corresponding transitions at the active site. This in both cases favors the formation of the non-disease inactive form. Upon allosteric modulation, the inhibitor significantly restored protein stability, enhanced compactness and decreased residual fluctuation as crucial to its potency in the amelioration of immunological and inflammatory diseases which agrees with experimental studies. These findings could therefore serve as the basis for the exploration of the allosteric domain and its active site affinity modulation to aid the design of more specific and selective inhibitors.
      Graphical abstract image

      PubDate: 2018-02-16T08:59:44Z
      DOI: 10.1016/j.compbiolchem.2018.02.002
      Issue No: Vol. 73 (2018)
  • A random version of principal component analysis in data clustering
    • Authors: Luigi Leonardo Palese
      Pages: 57 - 64
      Abstract: Publication date: April 2018
      Source:Computational Biology and Chemistry, Volume 73
      Author(s): Luigi Leonardo Palese
      Principal component analysis (PCA) is a widespread technique for data analysis that relies on the covariance/correlation matrix of the analyzed data. However, to properly work with high-dimensional data sets, PCA poses severe mathematical constraints on the minimum number of different replicates, or samples, that must be included in the analysis. Generally, improper sampling is due to a small number of data respect to the number of the degrees of freedom that characterize the ensemble. In the field of life sciences it is often important to have an algorithm that can accept poorly dimensioned data sets, including degenerated ones. Here a new random projection algorithm is proposed, in which a random symmetric matrix surrogates the covariance/correlation matrix of PCA, while maintaining the data clustering capacity. We demonstrate that what is important for clustering efficiency of PCA is not the exact form of the covariance/correlation matrix, but simply its symmetry.
      Graphical abstract image

      PubDate: 2018-02-16T08:59:44Z
      DOI: 10.1016/j.compbiolchem.2018.01.009
      Issue No: Vol. 73 (2018)
  • DFT/TD-DFT calculations, spectroscopic characterizations (FTIR, NMR,
           UV–vis), molecular docking and enzyme inhibition study of
    • Authors: Mahboob Alam; Mohammad Jane Alam; Shaista Azaz; Mehtab Parveen; Soonheum Park; Shabbir Ahmad
      Pages: 65 - 78
      Abstract: Publication date: April 2018
      Source:Computational Biology and Chemistry, Volume 73
      Author(s): Mahboob Alam, Mohammad Jane Alam, Shaista Azaz, Mehtab Parveen, Soonheum Park, Shabbir Ahmad
      The quantum chemical study, spectroscopic characterization and biological activity of the pharmaceutically active 7-benzoyloxycoumarin (2) molecule have been presented. Potential energy surface (PES) scanning has been performed to search for the most stable molecular geometry of the present compound. The stable geometry in the ground state, IR, UV–Vis absorption and NMR (13C, 1H) spectra of the title compound were theoretically obtained and compared with the experimental one. Various theoretical molecular parameters like molecular energy, atomic charges, dipole moment, thermodynamic parameters, donor-acceptor natural bond orbital (NBO) hyperconjugative interaction energies, frontier molecular orbitals energies, HOMO-LUMO gap, molecular electrostatic potential, chemical reactivity descriptors, molecular polarizability and non-linear optical (NLO) properties are presented. Moreover, the 3D Hirshfeld surfaces and the associated 2D fingerprint plots have been explored. The percentages of various non-covalent interactions are studied and pictorialized by fingerprint plots of Hirshfeld surface. 7-Benzoyloxycoumarin has shown promising inhibitory activity against butrylcholinesterase (BuChE) as compared to the reference drug, galantamine. Molecular docking is carried to introduce compound into the X-ray crystal structures of butrylcholinesterase at the active site to find out the probable binding mode. The results of molecular docking indicated that 7-benzoyloxy derivative of coumarin may show enzyme inhibitor activity.
      Graphical abstract image

      PubDate: 2018-02-26T09:16:25Z
      DOI: 10.1016/j.compbiolchem.2018.01.007
      Issue No: Vol. 73 (2018)
  • Predictive models for tyrosinase inhibitors: challenges from heterogeneous
           activity data determined by different experimental protocols
    • Authors: Haifeng Tang; Fengchao Cui; Lunyang Liu; Yunqi Li
      Pages: 79 - 84
      Abstract: Publication date: Available online 13 February 2018
      Source:Computational Biology and Chemistry
      Author(s): Haifeng Tang, Fengchao Cui, Lunyang Liu, Yunqi Li
      Quantitative Structure-Activity Relationship (QSAR) models of tyrosinase inhibitors were built using Random Forest (RF) algorithm and evaluated by the out-of-bag estimation (R2 OOB) and 10-fold cross validation (Q2 CV). We found that the performances of QSAR models were closely correlated with the systematic errors of inhibitory activities of tyrosinase inhibitors arising from the different measuring protocols. By defining ERRsys, outliers with larger errors can be efficiently identified and removed from heterogeneous activity data. A reasonable QSAR model (R2 OOB of 0.74 and Q2 CV of 0.80) was obtained by the exclusion of 13 outliers with larger systematic errors. It is a clear example of the challenge for QSAR model that can overwhelm heterogeneous data from different experimental protocols.
      Graphical abstract image

      PubDate: 2018-02-16T08:59:44Z
      DOI: 10.1016/j.compbiolchem.2018.02.007
      Issue No: Vol. 73 (2018)
  • Collective transcriptomic deregulation of hypertrophic and dilated
           cardiomyopathy – Importance of fibrotic mechanism in heart failure
    • Authors: Beutline Malgija; Nachimuthu Senthil kumar; Shanmughavel Piramanayagam
      Pages: 85 - 94
      Abstract: Publication date: Available online 10 February 2018
      Source:Computational Biology and Chemistry
      Author(s): Beutline Malgija, Nachimuthu Senthil kumar, Shanmughavel Pirmanayagam
      Myocardial fibrosis reside a common pathological feature in hypertrophic and dilated cardiomyopathy that results in ventricular dysfunction leading to heart failure. Though several studies reported the role of fibrosis in cardiac diseases, their pathologic mechanisms leading to heart failure remains unclear. A few studies have proposed integrated analysis of microarray information and protein-protein interaction (PPI) systems to discover subnetwork markers related to diagnosis and prognosis of the disease. In addition to PPI networks, we incorporated miRNAs and transcription factors to find the putative miRNAs and transcription factors that might regulate the pathological process and progression of cardiomyopathy and their further progression to heart failure. The important submodules from network revealed the significance of Small Leucine Rich Proteoglycans (SLRPs), Extracellular matrix (ECM) related proteins and complement system in fibrosis. Sequence analysis of different SLRPs suggest that Keratocan and Fibromodulin possesses the same collagen binding site.
      Graphical abstract image

      PubDate: 2018-02-16T08:59:44Z
      DOI: 10.1016/j.compbiolchem.2018.01.011
      Issue No: Vol. 73 (2018)
  • Guiding Exploration in Conformational Feature Space with Lipschitz
           Underestimation for ab-initio Protein Structure Prediction
    • Authors: Xiaohu Hao; Guijun Zhang; Xiaogen Zhou
      Pages: 105 - 119
      Abstract: Publication date: Available online 6 February 2018
      Source:Computational Biology and Chemistry
      Author(s): Xiaohu Hao, Guijun Zhang, Xiaogen Zhou
      Computing conformations which are essential to associate structural and functional information with gene sequences, is challenging due to the high dimensionality and rugged energy surface of the protein conformational space. Consequently, the dimension of the protein conformational space should be reduced to a proper level, and an effective exploring algorithm should be proposed. In this paper, a plug-in method for guiding exploration in conformational feature space with Lipschitz underestimation (LUE) for ab-initio protein structure prediction is proposed. The conformational space is converted into Ultrafast Shape Recognition (USR) feature space firstly. Based on the USR feature space, the conformational space can be further converted into Underestimation space according to Lipschitz estimation theory for guiding exploration. As a consequence of the use of underestimation model, the tight lower bound estimate information can be used for exploration guidance, the invalid sampling areas can be eliminated in advance, and the number of energy function evaluations can be reduced. The proposed method provides a novel technique to solve the exploring problem of protein conformational space. LUE is applied to Differential Evolution(DE) algorithm, and Metropolis Monte Carlo(MMC) algorithm which is available in the Rosetta; When LUE is applied to DE and MMC, it will be screened by the underestimation method prior to energy calculation and selection. Further, LUE is compared with DE and MMC by testing on 15 small-to-medium structurally diverse proteins. Test results show that near-native protein structures with higher accuracy can be obtained more rapidly and efficiently with the use of LUE.
      Graphical abstract image Highlights

      PubDate: 2018-02-16T08:59:44Z
      DOI: 10.1016/j.compbiolchem.2018.02.003
      Issue No: Vol. 73 (2018)
  • In vitro and in silico evaluation of Centaurea saligna (K.Koch)
           Wagenitz—an endemic folk medicinal plant
    • Authors: Gokhan Zengin; Gizem Bulut; Adriano Mollica; Carene Marie Nancy Picot-Allain; Mohamad Fawzi Mahomoodally
      Pages: 120 - 126
      Abstract: Publication date: Available online 13 February 2018
      Source:Computational Biology and Chemistry
      Author(s): Gokhan Zengin, Gizem Bulut, Adriano Mollica, Carene Marie Nancy Picot-Allain, Mohamad Fawzi Mahomoodally
      Centaurea saligna (K.Koch) Wagenitz is an endemic plant used in Turkish folk medicine as antibacterial, tonic, astringent, choleretic, anti-rheumatic, diuretic, and antipyretic. This study attempts for the first time to assess the possible enzyme inhibitory potential, antioxidant activity, and determine the phytochemical profile of the ethyl acetate, methanol, and water extracts of C. saligna. The water extract had the highest phenolic content (30.18 mg GAE/g extract) and the most potent oxidant scavenging activity (120.53, 111.90, 68.43, and 157.88 mg TE/g extract, for CUPRAC [cupric reducing antioxidant capacity], FRAP [ferric reducing antioxidant power], DPPH [2,2-diphenyl-1-picrylhydrazyl], and ABTS [2,2'-azino-bis(3-ethylbenzothiazoline-6-sulphonic acid] assays respectively). The water extract (4.16 mg KAE/g extract) also inhibited tyrosinase and contained high level of catechin (214 μg/g extract). Ethyl acetate extract showed potent inhibitory capacity against cholinesterases (2.22 and 2.21 mg GALAE/g extract for acetyl and butyryl cholinesterase, respectively) and α-glucosidase (23.80 mmol ACAE/g extract). High concentration of apigenin (2472 μg/g extract) was identified in the ethyl acetate extract. In silico studies showed that apigenin binds to the enzymatic pocket of α-glucosidase and is stabilised by a network of hydrogen bonds and pi-pi stacking. Data collected in the present study advocates the need for further investigation geared towards validation of C. saligna for the management of complications related to the target enzymes, such as diabetes type II, Alzheimer’s disease, and epidermal hyperpigmentation.
      Graphical abstract image

      PubDate: 2018-02-16T08:59:44Z
      DOI: 10.1016/j.compbiolchem.2018.02.010
      Issue No: Vol. 73 (2018)
  • Imidazolium ionic liquids as effective antiseptics and disinfectants
           against drug resistant S. aureus: In silico and in vitro studies
    • Authors: Diana Hodyna; Vasyl Kovalishyn; Ivan Semenyuta; Volodymyr Blagodatnyi; Sergiy Rogalsky; Larisa Metelytsia
      Pages: 127 - 138
      Abstract: Publication date: April 2018
      Source:Computational Biology and Chemistry, Volume 73
      Author(s): Diana Hodyna, Vasyl Kovalishyn, Ivan Semenyuta, Volodymyr Blagodatnyi, Sergiy Rogalsky, Larisa Metelytsia
      This paper describes Quantitative Structure-Activity Relationships (QSAR) studies, molecular docking and in vitro antibacterial activity of several potent imidazolium-based ionic liquids (ILs) against S. aureus ATCC 25923 and its clinical isolate. Small set of 131 ILs was collected from the literature and uploaded in the OCHEM database. QSAR methodologies used Associative Neural Networks and Random Forests (WEKA-RF) methods. The predictive ability of the models was tested through cross-validation, giving cross-validated coefficients q2 = 0.82–0.87 for regression models and overall prediction accuracies of 80–82.1% for classification models. The proposed QSAR models are freely available online on OCHEM server at and can be used for estimation of antibacterial activity of new imidazolium-based ILs. A series of synthesized 1,3-dialkylimidazolium ILs with predicted activity were evaluated in vitro. The high activity of 7 ILs against S. aureus strain and its clinical isolate was measured and thereafter analyzed by the molecular docking to prokaryotic homologue of a eukaryotic tubulin FtsZ.
      Graphical abstract image

      PubDate: 2018-03-08T13:10:32Z
      DOI: 10.1016/j.compbiolchem.2018.01.012
      Issue No: Vol. 73 (2018)
  • Multiple Grid Arrangement Improves Ligand Docking with Unknown Binding
           Sites: Application to the Inverse Docking Problem
    • Authors: Tomohiro Ban; Masahito Ohue; Yutaka Akiyama
      Pages: 139 - 146
      Abstract: Publication date: Available online 15 February 2018
      Source:Computational Biology and Chemistry
      Author(s): Tomohiro Ban, Masahito Ohue, Yutaka Akiyama
      The identification of comprehensive drug–target interactions is important in drug discovery. Although numerous computational methods have been developed over the years, a gold standard technique has not been established. Computational ligand docking and structure-based drug design allow researchers to predict the binding affinity between a compound and a target protein, and thus, they are often used to virtually screen compound libraries. In addition, docking techniques have also been applied to the virtual screening of target proteins (inverse docking) to predict target proteins of a drug candidate. Nevertheless, a more accurate docking method is currently required. In this study, we proposed a method in which a predicted ligand-binding site is covered by multiple grids, termed multiple grid arrangement. Notably, multiple grid arrangement facilitates the conformational search for a grid-based ligand docking software and can be applied to the state-of-the-art commercial docking software Glide (Schrödinger, LLC). We validated the proposed method by re-docking with the Astex diverse benchmark dataset and blind binding site situations, which improved the correct prediction rate of the top scoring docking pose from 27.1% to 34.1%; however, only a slight improvement in target prediction accuracy was observed with inverse docking scenarios. These findings highlight the limitations and challenges of current scoring functions and the need for more accurate docking methods The proposed multiple grid arrangement method was implemented in Glide by modifying a cross-docking script for Glide, The script of our method is freely available online at
      Graphical abstract image

      PubDate: 2018-02-16T08:59:44Z
      DOI: 10.1016/j.compbiolchem.2018.02.008
      Issue No: Vol. 73 (2018)
  • Quantum Molecular Modelling of Hepatitis C Virus Inhibition through
           Non-Structural Protein 5B Polymerase Receptor Binding of C5-Arylidene
    • Authors: Krishnan Balasubramanian; Vaishali M. Patil
      Pages: 147 - 158
      Abstract: Publication date: Available online 31 January 2018
      Source:Computational Biology and Chemistry
      Author(s): Krishnan Balasubramanian, Vaishali M. Patil
      We have carried out high-level quantum chemical computations followed by molecular docking studies on a set of 17C5-arylidene rhodanine isomers to provide insights into the binding modes with different reported binding pockets of the nonstructural protein 5B (NS5B) polymerase that contribute to the hepatitis C virus (HCV) inhibition. We optimized the multi-target profile of the selected rhodanine analogs to investigate potential non-nucleotide inhibitors (NNIs) by quantum chemical optimization of the 18 isomers followed by docking with quantum chemically optimized structures of each isomer with NS5B polymerase at multiple binding pockets. The binding affinities of the PP-I, PP-II and TP-II pockets of NS5B polymerase were analyzed for all the 17 isomers of 2-[(5Z)-5-(2,4-dichlorobenzylidene)-4-oxo-2-thioxo-1,3-thiazolidin-3-yl]-3-phenylpropanoic acid. On the basis of binding propensity at the different pockets and inhibitor constants, we ranked these isomers as potential candidates for the HCV inhibition. We have identified four isomers as promising NNIs of NS5B polymerase with comparable binding and inhibition to the standard (1,3) dichloro substituted isomer that exhibits in vitro activity and several other isomers as candidates in a “multi-targeted drug” approach.
      Graphical abstract image

      PubDate: 2018-02-16T08:59:44Z
      DOI: 10.1016/j.compbiolchem.2018.01.008
      Issue No: Vol. 73 (2018)
  • Markovian Encoding Models in Human splice site recognition using SVM
    • Authors: Elham Pashaei; Nizamettin Aydin
      Pages: 159 - 170
      Abstract: Publication date: Available online 14 February 2018
      Source:Computational Biology and Chemistry
      Author(s): Elham Pashaei, Nizamettin Aydin
      Splice site recognition is among the most significant and challenging tasks in bioinformatics due to its key role in gene annotation. Effective prediction of splice site requires nucleotide encoding methods that reveal the characteristics of DNA sequences to provide appropriate features to serve as input of machine learning classifiers. Markovian models are the most influential encoding methods that highly used for pattern recognition in biological data. However, a direct performance comparison of these methods in splice site domain has not been assessed yet. This study compares various Markovian encoding models for splice site prediction utilizing support vector machine, as the most outstanding learning method in the domain, and conducts a new precise evaluation of Markovian approaches that corrects this limitation. Moreover, a novel sequence encoding approach based on third order Markov model (MM3) is proposed. The experimental results show that the proposed method, namely MM3-SVM, performs significantly better than thirteen best known state-of-the-art algorithms, while tested on HS3D dataset considering several performance criteria. Further, it achieved higher prediction accuracy than several well-known tools like NNsplice, MEM, MM1, WMM, and GeneID, using an independent test set of 50 genes. We also developed MMSVM, a web tool to predict splice sites in any human sequence using the proposed approach. The MMSVM web server can be assessed at

      PubDate: 2018-02-16T08:59:44Z
      DOI: 10.1016/j.compbiolchem.2018.02.005
      Issue No: Vol. 73 (2018)
  • CCFS: A Cooperating Coevolution Technique for Large Scale Feature
           Selection on Microarray Datasets
    • Authors: Mohammad K. Ebrahimpour; Hossein Nezamabadi-pour; Mahdi Eftekhari
      Pages: 171 - 178
      Abstract: Publication date: Available online 17 February 2018
      Source:Computational Biology and Chemistry
      Author(s): Mohammad K. Ebrahimpour, Hossein Nezamabadi-pour, Mahdi Eftekhari
      Recently, advances in bioinformatics leads to microarray high dimensional datasets. These kind of datasets are still challenging for researchers in the area of machine learning since they suffer from small sample size and extremely large number of features. Therefore, feature selection is the problem of interest in the learning process in this area. In this paper, a novel feature selection method based on a global search (by using the main concepts of divide and conquer technique) which is called CCFS, is proposed. The proposed CCFS algorithm divides vertically (on features) the dataset by random manner and utilizes the fundamental concepts of cooperation coevolution by using a filter criterion in the fitness function in order to search the solution space via binary gravitational search algorithm. For determining the effectiveness of the proposed method some experiments are carried out on seven binary microarray high dimensional datasets. The obtained results are compared with nine state-of-the-art feature selection algorithms including Interact (INT), and Maximum Relevancy Minimum Redundancy (MRMR).The average outcomes of the results are analyzed by a statistical non-parametric test and it reveals that the proposed method has a meaningful difference to the others in terms of accuracy, sensitivity, specificity and number of selected features.
      Graphical abstract image Highlights

      PubDate: 2018-02-26T09:16:25Z
      DOI: 10.1016/j.compbiolchem.2018.02.006
      Issue No: Vol. 73 (2018)
  • The anesthetic action of some polyhalogenated ethers − Monte Carlo
           method based QSAR study
    • Authors: Mlađan Golubović; Milan Lazarević; Dragan Zlatanović; Dane Krtinić; Viktor Stoičkov; Bojan Mladenović; Dragan J. Milić; Dušan Sokolović; Aleksandar M. Veselinović
      Abstract: Publication date: Available online 13 April 2018
      Source:Computational Biology and Chemistry
      Author(s): Mlađan Golubović, Milan Lazarević, Dragan Zlatanović, Dane Krtinić, Viktor Stoičkov, Bojan Mladenović, Dragan J. Milić, Dušan Sokolović, Aleksandar M. Veselinović
      Up to this date, there has been an ongoing debate about the mode of action of general anesthetics, which have postulated many biological sites as targets for their action. However, postoperative nausea and vomiting are common problems in which inhalational agents may have a role in their development. When a mode of action is unknown, QSAR modelling is essential in drug development. To investigate the aspects of their anesthetic, QSAR models based on the Monte Carlo method were developed for a set of polyhalogenated ethers. Until now, their anesthetic action has not been completely defined, although some hypotheses have been suggested. Therefore, a QSAR model should be developed on molecular fragments that contribute to anesthetic action. QSAR models were built on the basis of optimal molecular descriptors based on the SMILES notation and local graph invariants, whereas the Monte Carlo optimization method with three random splits into the training and test set was applied for model development. Different methods, including novel Index of ideality correlation, were applied for the determination of the robustness of the model and its predictive potential. The Monte Carlo optimization process was capable of being an efficient in silico tool for building up a robust model of good statistical quality. Molecular fragments which have both positive and negative influence on anesthetic action were determined. The presented study can be useful in the search for novel anesthetics.
      Graphical abstract image

      PubDate: 2018-04-15T06:22:49Z
      DOI: 10.1016/j.compbiolchem.2018.04.009
  • Hardware Acceleration of BWA-MEM Genomic Short Read Mapping for Longer
           Read Lengths
    • Authors: Ernst Joachim Houtgast; Vlad-Mihai Sima; Koen Bertels; Zaid Al-Ars
      Abstract: Publication date: Available online 12 April 2018
      Source:Computational Biology and Chemistry
      Author(s): Ernst Joachim Houtgast, Vlad-Mihai Sima, Koen Bertels, Zaid Al-Ars
      We present our work on hardware accelerated genomics pipelines, using either FPGAs or GPUs to accelerate execution of BWA-MEM, a widely-used algorithm for genomic short read mapping. The mapping stage can take up to 40% of overall processing time for genomics pipelines. Our implementation offloads the Seed Extension function, one of the main BWA-MEM computational functions, onto an accelerator. Typical sequencer output are reads with a length of 150 base pairs. However, read length is expected to increase in the near future. Here, we investigate the influence of read length on BWA-MEM performance using data sets with read length up to 400 base pairs, and introduce methods to ameliorate the impact of longer read length. For the industry-standard 150 base pair read length, our implementation achieves an up to two-fold increase in overall application-level performance for systems with at most twenty-two logical CPU cores. Longer read length requires commensurately bigger data structures, which directly impacts accelerator efficiency. The two-fold performance increase is sustained for read length of at most 250 base pairs. To improve performance, we perform a classification of the inefficiency of the underlying systolic array architecture. By eliminating idle regions as much as possible, efficiency is improved by up to +95%. Moreover, adaptive load balancing intelligently distributes work between host and accelerator to ensure use of an accelerator always results in performance improvement, which in GPU-constrained scenarios provides up to +45% more performance.

      PubDate: 2018-04-15T06:22:49Z
      DOI: 10.1016/j.compbiolchem.2018.03.024
  • The molecular selectivity of UNC3866 inhibitor for Polycomb CBX7 protein
           from molecular dynamics simulation
    • Authors: Zhuomin Li; Liang Li; Hui Liu
      Abstract: Publication date: Available online 10 April 2018
      Source:Computational Biology and Chemistry
      Author(s): Zhuomin Li, Liang Li, Hui Liu
      Polycomb CBX proteins regulate gene expression by targeting Polycomb repressive complex 1 (PRC1) to sites of H3K27me3 via their chromodomains, which plays a key role in the development of numerous cancers. UNC3866, is a recently reported peptide-based inhibitor of the methyllysine (Kme) reading function of CBX chromodomains (CBX2, 4 and 6-8). The previous experiments showed that UNC3866 bound the chromodomains of CBX7 strongly, with ∼20-fold selectivity over other CBX chromodomains. However, the potential mechanism of UNC3866 preferentially binding to CBX7 is still unknown. In this study, we performed two pairs of microsecond molecular dynamic simulations (CBX2 (-UNC3866)) and (CBX7 (-UNC3866)) to study the inhibition and isoform-selective mechanism of UNC3866 to CBX7. The conformational analysis of apo- and holo- CBX2 and CBX7 indicated that the aromatic cage of CBX7 protein was more prone to be induced by UNC3866 relative to CBX2 protein. The results of predicted binding free energy suggested the binding affinity of UNC3866 with CBX7 was stronger than that with CBX2, because of the lower binding free energy of the former. Furthermore, the energetic origin of UNC3866 selective for CBX7 protein mainly came from the higher van der Waals contributions. The binding mode analysis showed that Asn47 of CBX2 formed a hydrogen bond with the OH group of C-terminal cap of UNC3866, inducing the conformational changes of diethyllysine of UNC3866 that is obviously different from that in CBX7. Additionally, His39 in CBX2 chromodomain interrupted the structured aromatic cage, partly explaining the reason for UNC3866 preferring for binding to CBX7. The proposal of this selective mechanism could be helpful for the rational design of novel selective inhibitors of the Polycomb CBX protein.
      Graphical abstract image

      PubDate: 2018-04-15T06:22:49Z
      DOI: 10.1016/j.compbiolchem.2018.04.005
  • Computational elucidation of phylogenetic, structural and functional
           characteristics of Pseudomonas Lipases
    • Authors: Krishnendu Pramanik; Sunayana Saren; Soumik Mitra; Pallab Kumar Ghosh; Tushar Kanti Maiti
      Abstract: Publication date: Available online 19 March 2018
      Source:Computational Biology and Chemistry
      Author(s): Krishnendu Pramanik, Sunayana Saren, Soumik Mitra, Pallab Kumar Ghosh, Tushar Kanti Maiti
      Lipase (triacylglycerol acylhydrolase, EC catalyzes tri-, di-, and monoacyl glycerol of fat into glycerol and fatty acids. It has important roles in digestion of lipids in living organisms and industrially as laundry detergents along with proteases. The microbial lipases are more stable, active and economically feasible compared to plant and animal sources. Hence, much attention was given for maximum production of the enzyme from the microbial sources. The phylogenetic analysis revealed that the amino acid sequence of lipase protein and their corresponding cDNA of Pseudomonas aeruginosa clustered with Pseudomonas stutzeri among different species of Pseudomonas, while P. aeruginosa PA1 clustered with P. aeruginosa SJTD-1 among different strains of P. aeruginosa. The lipase of P. aeruginosa PA1 was monomeric, acidic and thermostable protein having molecular weight ranging in between 32.72 to 34.89 kDa. The protein was abundant with random coils and alpha helices in its secondary structure. Tertiary model showed 96.310 score as overall quality factor. Hence, this in silico study gives some useful information about the lipase protein without performing crystal structure assessment by X-ray Crystallography or NMR study in wet lab experiments which could be helpful for isolation and characterization of the enzyme in vitro.
      Graphical abstract image

      PubDate: 2018-03-20T11:08:48Z
      DOI: 10.1016/j.compbiolchem.2018.03.018
  • 3D QSAR studies, molecular docking and ADMET evaluation, using
           thiazolidine derivatives as template to obtain new inhibitors of PIM1
    • Authors: Adnane Aouidate; Adib Ghaleb; Mounir Ghamali; Abdellah Ousaa; M’barek Choukrad; Abdelouahid Sbai; Mohammed Bouachrine; Tahar Lakhlifi
      Abstract: Publication date: Available online 12 March 2018
      Source:Computational Biology and Chemistry
      Author(s): Adnane Aouidate, Adib Ghaleb, Mounir Ghamali, Abdellah Ousaa, M’barek Choukrad, Abdelouahid Sbai, Mohammed Bouachrine, Tahar Lakhlifi
      Proviral Integration site for Moloney murine leukemia virus-1 (PIM1) belongs to the serine/threonine kinase family of Ca2+-calmodulin-dependent protein kinase (CAMK) group, which is involved in cell survival and proliferation as well as a number of other signal transduction pathways. Thus, it is regarded as a promising target for treatment of cancers. In the present paper, a three-dimensional quantitative structure activity relationship (3D-QSAR) and molecular docking were performed to investigate the binding between PIM1 and thiazolidine inhibitors in order to design potent inhibitors. The comparative molecular similarity indexes analysis (CoMSIA) was developed using twenty-six molecules having pIC50 ranging from 8.854 to 6.011 (IC50 in nM). The best CoMSIA model gave significant statistical quality. The determination coefficient (R2) and Leave-One-Out cross-validation coefficient (Q2) are 0.85 and 0.58, respectively. Furthermore, the predictive ability of this model was evaluated by external validation using a test set of eleven compounds with a predicted determination coefficient R2 test of 0.72. The graphical contour maps could provide structural features to improve inhibitory activity. Furthermore, a good consistency between contour maps and molecular docking strongly demonstrates that the molecular modeling is reliable. Based on these satisfactory results, we designed several new potent PIM1 inhibitors and their inhibitory activities were predicted by the molecular models. Additionally, those newly designed inhibitors, showed promising results in the preliminary in silico ADMET evaluations, compared to the best inhibitor from the studied dataset. This study would be of great help in lead optimization for early drug discovery of highly PIM1 inhibitors.
      Graphical abstract image

      PubDate: 2018-03-20T11:08:48Z
      DOI: 10.1016/j.compbiolchem.2018.03.008
  • Molecular docking and MM/GBSA calculations of novel spiro- and
           pyrazolo[1,5-c]quinazolines as AChE inhibitors
    • Authors: Jaime Gálvez; Stivens Polo; Braulio Insuasty; Margarita Gutiérrez; Daniela Cáceres; Jans H. Alzate-Morales; Pedro De-la-Torre; Jairo Quiroga
      Abstract: Publication date: Available online 7 March 2018
      Source:Computational Biology and Chemistry
      Author(s): Jaime Gálvez, Stivens Polo, Braulio Insuasty, Margarita Gutiérrez, Daniela Cáceres, Jans H. Alzate-Morales, Pedro De-la-Torre, Jairo Quiroga
      Given the wide spectrum of biological uses of pyrazolo[1,5-c]quinazoline and the spiro-quinazoline derivatives as anticancer, anti-inflammatory analgesic agents and their therapeutic applications in neurodegenerative disorders, it is compulsory to find easy, efficient and simple methods to obtain and chemically diversify these families of compounds, thereby improving their biological applications. In this paper, we report the design and eco-friendly two-step synthesis of novel, fused spiro-pyrazolo[1,5-c]quinazoline derivatives as cholinesterase inhibitors. In addition, we studied their protein-ligand interaction via molecular docking and MM/GBSA calculations for a further rational design of more potent inhibitors. In first step, 2-(1H-pyrazol-5-yl)anilines were obtained through microwave (MW) assisted solvent-free/catalyst-free conditions and the second step involved the synthesis of the spiro-pyrazolo[1,5-c]quinazolines by a cyclocondensation reaction between 2-(1H-pyrazol-5-yl)anilines and cyclic ketones, or acetophenones, using stirring at room temperature. The reaction times were considerably shorter, with good yields (> 50%) and high purity of products. The spiro-compounds were evaluated as acetylcholinesterase and butyrylcholinesterase inhibitors (AChEIs/BuChEIs) respectively, and the most potent compound exhibited a moderate AChE inhibitory activity (5f: IC50 = 84 μM). Molecular docking studies indicated that the binding mode of the compound 5f share common characteristics with the galantamine/donepezil-AChE complexes. Moreover, free binding energy (ΔG ) calculations showed a good agreement with the experimental biological activity values. Our theoretical results indicated that halogen bond interactions could be involved with differential potency of these compounds and provide a new starting point to design novel pyrazolo[1,5-c]quinazolines as new anti-Alzheimer agents.
      Graphical abstract image

      PubDate: 2018-03-08T13:10:32Z
      DOI: 10.1016/j.compbiolchem.2018.03.001
  • Rational design of methicillin resistance staphylococcus aureus Inhibitors
           through 3D-QSAR, molecular docking and molecular dynamics simulations
    • Authors: Srilata Ballu; Ramesh Itteboina Sree Kanth Sivan Vijjulatha Manga
      Abstract: Publication date: Available online 20 December 2017
      Source:Computational Biology and Chemistry
      Author(s): Srilata Ballu, Ramesh Itteboina, Sree Kanth Sivan, Vijjulatha Manga
      Staphylococcus aureus is a gram positive bacterium. It is a leading cause of skin and respiratory infections, osteomyelitis, Ritter's disease, endocarditis, and bacteraemia in the developed world. We employed combined studies of 3D QSAR, molecular docking which are cross validated by molecular dynamics simulations and in silico ADME prediction have been performed on Isothiazoloquinolones inhibitors against methicillin resistance Staphylococcus aureus. Three-dimensional quantitative structure-activity relationship (3D-QSAR) study was applied using comparative molecular field analysis (CoMFA)with Q2of0.578, R2of0.988, and comparative molecular similarity indices analysis (CoMSIA) with Q2 of0.554, R2of0.975. The predictive ability of these model was determined using a test set of molecules that gave acceptable predictive correlation (r2 Pred) values 0.55 and 0.57 of CoMFA and CoMSIA respectively. Docking, simulations were employed to position the inhibitors into protein active site to find out the most probable binding mode and most reliable conformations. Developed models and Docking methods provide guidance to design moleculeswith enhanced activity.
      Graphical abstract image

      PubDate: 2017-12-24T19:00:57Z
  • Identification of new antibacterial targets in RNA polymerase of
           Mycobacterium tuberculosis by detecting positive selection sites
    • Authors: QingBiao Wang; Yiqin Zhuoya Nian Liu Jin Yao James Crabbe
      Abstract: Publication date: Available online 21 November 2017
      Source:Computational Biology and Chemistry
      Author(s): QingBiao Wang, Yiqin Xu, Zhuoya Gu, Nian Liu, Ke Jin, Yao Li, M. James C. Crabbe, Yang Zhong
      Bacterial RNA polymerase (RNAP) is an effective target for antibacterial treatment. In order to search new potential targets in RNAP of Mycobacterium, we detected adaptive selections of RNAP related genes in 13 strains of Mycobacterium by phylogenetic analysis. We first collected sequences of 17 genes including rpoA, rpoB, rpoC, rpoZ, and sigma factor A-M. Then maximum likelihood trees were constructed, followed by positive selection detection. We found that sigG shows positive selection along the clade (M. tuberculosis, M. bovis), suggesting its important evolutionary role and its potential to be a new antibacterial target. Moreover, the regions near 933Cys and 935His on the rpoB subunit of M. tuberculosis showed significant positive selection, which could also be a new attractive target for anti-tuberculosis drugs.
      Graphical abstract image

      PubDate: 2017-12-06T15:27:21Z
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
Home (Search)
Subjects A-Z
Publishers A-Z
Your IP address:
About JournalTOCs
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-