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CHEMICAL ENGINEERING (200 journals)                     

Showing 1 - 200 of 200 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: 9)
Additives for Polymers     Full-text available via subscription   (Followers: 22)
Adhesion Adhesives & Sealants     Hybrid Journal   (Followers: 8)
Advanced Chemical Engineering Research     Open Access   (Followers: 38)
Advanced Powder Technology     Hybrid Journal   (Followers: 17)
Advances in Applied Ceramics     Hybrid Journal   (Followers: 5)
Advances in Chemical Engineering     Full-text available via subscription   (Followers: 28)
Advances in Chemical Engineering and Science     Open Access   (Followers: 65)
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: 11)
Annual Review of Chemical and Biomolecular Engineering     Full-text available via subscription   (Followers: 12)
Anti-Corrosion Methods and Materials     Hybrid Journal   (Followers: 10)
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: 17)
Chemical and Materials Engineering     Open Access   (Followers: 17)
Chemical and Petroleum Engineering     Hybrid Journal   (Followers: 13)
Chemical and Process Engineering     Open Access   (Followers: 32)
Chemical and Process Engineering Research     Open Access   (Followers: 29)
Chemical Engineering & Technology     Hybrid Journal   (Followers: 31)
Chemical Engineering and Processing: Process Intensification     Hybrid Journal   (Followers: 16)
Chemical Engineering and Science     Open Access   (Followers: 25)
Chemical Engineering Communications     Hybrid Journal   (Followers: 14)
Chemical Engineering Education     Full-text available via subscription   (Followers: 1)
Chemical Engineering Journal     Hybrid Journal   (Followers: 52)
Chemical Engineering Research and Design     Hybrid Journal   (Followers: 25)
Chemical Engineering Research Bulletin     Open Access   (Followers: 17)
Chemical Engineering Science     Hybrid Journal   (Followers: 28)
Chemical Geology     Hybrid Journal   (Followers: 23)
Chemical Papers     Hybrid Journal   (Followers: 2)
Chemical Product and Process Modeling     Hybrid Journal   (Followers: 4)
Chemical Reviews     Full-text available via subscription   (Followers: 196)
Chemical Society Reviews     Full-text available via subscription   (Followers: 43)
Chemical Technology     Open Access   (Followers: 21)
ChemInform     Hybrid Journal   (Followers: 8)
Chemistry & Industry     Hybrid Journal   (Followers: 5)
Chemistry Central Journal     Open Access   (Followers: 4)
Chemistry of Materials     Full-text available via subscription   (Followers: 251)
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  
European Polymer Journal     Hybrid Journal   (Followers: 42)
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)
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: 10)
Indonesian Journal of Chemical Science     Open Access   (Followers: 1)
Industrial & Engineering Chemistry     Full-text available via subscription   (Followers: 12)
Industrial & Engineering Chemistry Research     Full-text available via subscription   (Followers: 22)
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: 3)
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: 14)
Journal of Applied Polymer Science     Hybrid Journal   (Followers: 145)
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: 12)
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: 25)
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: 23)
Journal of Chemical Technology & Biotechnology     Hybrid Journal   (Followers: 10)
Journal of Chemical Theory and Computation     Full-text available via subscription   (Followers: 18)
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: 5)
Journal of Geochemical Exploration     Hybrid Journal   (Followers: 1)
Journal of Industrial and Engineering Chemistry     Hybrid Journal   (Followers: 1)
Journal of Information Display     Hybrid Journal   (Followers: 1)
Journal of Inorganic and Organometallic Polymers and Materials     Partially Free   (Followers: 9)
Journal of Materials Science and Chemical Engineering     Open Access   (Followers: 1)
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: 5)
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: 7)
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: 333)
Journal of the Bangladesh Chemical Society     Open Access  
Journal of the Brazilian Chemical Society     Open Access   (Followers: 2)
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: 136)
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 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: 6)
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)
Transition Metal Chemistry     Hybrid Journal   (Followers: 4)
Transylvanian Review of Systematical and Ecological Research     Open Access  
Visegrad Journal on Bioeconomy and Sustainable Development     Open Access   (Followers: 2)
Zeitschrift für Naturforschung B : A Journal of Chemical Sciences     Open Access   (Followers: 1)


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
    • 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
  • Computational analysis for the determination of deleterious nsSNPs in
           human MTHFR gene
    • 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
  • Imidazolium ionic liquids as effective antiseptics and disinfectants
           against drug resistant S. aureus: In silico and in vitro studies
    • 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
  • Scaffold-based novel SHP2 allosteric inhibitors design using
           Receptor-Ligand pharmacophore model, virtual screening and molecular
    • Abstract: Publication date: April 2018
      Source:Computational Biology and Chemistry, Volume 73
      Author(s): Wen-Yan Jin, Ying Ma, Wei-Ya Li, Hong-Lian Li, Run-Ling Wang
      SHP2 is a potential target for the development of novel therapies for SHP2-dependent cancers. In our research, with the aid of the ‘Receptor-Ligand Pharmacophore’ technique, a 3D-QSAR method was carried out to explore structure activity relationship of SHP2 allosteric inhibitors. Structure-based drug design was employed to optimize SHP099, an efficacious, potent, and selective SHP2 allosteric inhibitor. A novel class of selective SHP2 allosteric inhibitors was discovered by using the powerful ‘SBP’, ‘ADMET’ and ‘CDOCKER’ techniques. By means of molecular dynamics simulations, it was observed that these novel inhibitors not only had the same function as SHP099 did in inhibiting SHP2, but also had more favorable conformation for binding to the receptor. Thus, this report may provide a new method in discovering novel and selective SHP2 allosteric inhibitors.
      Graphical abstract image

      PubDate: 2018-03-08T13:10:32Z
  • QM/MM Analysis of Effect of Divalent Metal Ions on OPRT Action
    • 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
  • Molecular docking and MM/GBSA calculations of novel spiro- and
           pyrazolo[1,5-c]quinazolines as AChE inhibitors
    • 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
  • POAP: A GNU Parallel based multithreaded pipeline of Open Babel and
           AutoDock suite for boosted High Throughput Virtual Screening
    • 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
  • LQTA-R: A new 3D-QSAR methodology applied to a set of DGAT1 inhibitors
    • 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
  • Statistical methods to detect novel genetic variants using publicly
           available GWAS summary data
    • 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
  • Design, synthesis and biological evaluation of novel thiazol-2-yl
           benzamide derivatives as glucokinase activators
    • Abstract: Publication date: Available online 27 February 2018
      Source:Computational Biology and Chemistry
      Author(s): Neha Charaya, Deepti Pandita, Ajmer Singh Grewal, Viney Lather
      Glucokinase (GK) is the main enzyme which controls the blood glucose levels in a safe and narrow physiological range in humans. GK activators are the novel type of therapeutic agents which act on GK enzyme and show their anti-diabetic potential. The present work was planned to synthesize and evaluate the antidiabetic potential of a new series of thiazole-2-yl benzamide derivatives as potential GK activators. A series of thiazole-2-yl benzamide derivatives were synthesized from benzoic acid and evaluated by in vitro enzymatic assay for GK activation. In silico docking studies were carried out to determine the binding interactions for the best fit conformations in the allosteric site of GK enzyme. Based on the results of in vitro enzyme assay and in silico studies, the selected molecules were tested for their antidiabetic activity in the oral glucose tolerance test (OGTT). The results of the in vitro enzymatic assay were found to be in accordance to that of in silico studies. Amongst the synthesized molecules, compounds 1, 2, 5 and 8 displayed good in vitro GK activation (activation fold between 1.48 and 1.83). Compounds 2 and 8 exhibited highest antidiabetic activity in OGTT studies. The results of the in vivo antidiabetic studies were found to be in parallel to that of docking and in vitro studies. These newly synthesized thiazol-2-yl benzamide derivatives thus can be treated as the initial hits for the development of new, safe, effective and orally bioavailable GK activators as therapeutic agents for the treatment of type 2 diabetes.
      Graphical abstract image

      PubDate: 2018-03-08T13:10:32Z
    • Abstract: Publication date: Available online 27 February 2018
      Source:Computational Biology and Chemistry
      Author(s): Premnath D., Akila D., Indiraleka M.
      Epigenetic characterization studies have clearly shown that the association of genital Human Papilloma Virus (HPV) with cervical cancer is strong, independent of other risk factors, and consistent in several countries. Even though all the strains of Human Papilloma Virus can cause cancer, the high-risk strains can cause severe cancer in a human. The E6 and E7 protein are responsible for the carcinogenic property of HPV. Among these two proteins, the HPV E7 protein plays a major role in the viral life cycle by allowing the virus to replicate in differentiating epithelial cells. All the strains of HPV are variants (High risk and low risk). A computational analysis study is done to find which low-risk strain is showing most similarity with the high risk there by predicting that this low −risk strain can be converted to high-risk if a mutation occurs in future. Through mutation, a normal strain will get converted to low-risk and a low-risk to high-risk. So the mutations are important and it can affect the viruses to a greater extent because of their smaller size. In order to inhibit the expression of Type 11 low-risk strain a noval suppressor molecule is synthesized and characterized using UV, FTIR and NMR spectrometry. The suppressor molecule is a quinazoline derivative, as it can act as an anti-cancer agent to inhibit the expression of the E7 protein in Type 11 strain. The efficiency of binding of type 11 E7 protein with quinazoline derivative is calculated through docking studies using G-Score (Schrodinger). Thus proposing this noval suppressor molecule can be lead against cervical cancer caused by HPV Type 11 strain after further in-vitro and in Vivo characterization.
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      PubDate: 2018-03-08T13:10:32Z
  • DFT/TD-DFT calculations, spectroscopic characterizations (FTIR, NMR,
           UV–vis), molecular docking and enzyme inhibition study of
    • 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.
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      PubDate: 2018-02-26T09:16:25Z
  • Elucidation of Chemosensitization Effect of Acridones in Cancer Cell
           lines: Combined Pharmacophore Modeling, 3D QSAR, and Molecular Dynamics
    • 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.
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      PubDate: 2018-02-26T09:16:25Z
  • QM/MM reveals the sequence of substrate binding during OPRT action
    • 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.
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      PubDate: 2018-02-26T09:16:25Z
  • Characterization of regulatory elements in OsRGLP2 gene promoter from
           different rice accessions through sequencing and in silico evaluation
    • Abstract: Publication date: Available online 23 February 2018
      Source:Computational Biology and Chemistry
      Author(s): Tariq Mahmood, Tamkeen Tahir, Faiza Munir, Zabta Khan Shinwari
      Germins and germin-like proteins from cupin superfamily contribute resistance to heat denaturation, chemical degradation and against plant pathogens, further functions in plant growth and development. In this study, from three different Oryza sativa accessions KS-282 and Pak 7178 and Pak 7865, OsRGLP2 gene promoter region was amplified, sequenced and analyzed. Sequencing data was evaluated via different computational tools. The regulatory elements were predicted by Consite tool and mapping was done. Many transcription factors binding sites were discovered in OsRGLP2 gene promoter; among these factors, HFH-1 having a significant role in germination was picked for further investigation. To study the interaction between HFH-1 and corresponding regulatory factors, HADDOCK Webserver was used. Graphical models for the interactions of HFH-1 and related regulatory elements were studied by graphic molecular system PyMOL. Mapping of cis-acting regulatory elements in OsRGLP2 gene promoter from three rice accessions showed differences in their position and copy number. Important regulatory elements found in OsRGLP2 promoter region were TATA, CAAT Box, ARR1, GATA, AGAAA, CAAT and DNA-binding One Zinc Finger (Dof) factors, few of them contribute to the regulation of plant defensive system, light responses, developmental and growth activities. Furthermore, during DNA interaction studies, it was found that HFH-1 transcription factor participates in hydrogen bonds formation with thymine and adenine bases.
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      PubDate: 2018-02-26T09:16:25Z
  • Computational Design of the Helical Hairpin Structure of Membrane-Active
           Antibacterial Peptides based on RSV Glycoprotein Epitope Scaffold
    • Abstract: Publication date: Available online 21 February 2018
      Source:Computational Biology and Chemistry
      Author(s): Jinhua Fu, Hong Yang, Jing Wang
      Peptides with helical hairpin conformation have been found to possess potent membrane activity and can be exploited as the structural scaffold of antibacterial peptides (ABPs). Here, we attempted to computationally design membrane-active ABPs based on the helical hairpin motif of respiratory syncytial virus (RSV) glycoprotein epitope. Dynamics simulations revealed that the epitope peptide Rfe (net charge = −1) cannot effectively interact with and permeabilize bacterial membrane due to the electrostatic repulsion between the negatively charged peptide and anionic membrane surface. The native Rfe can be modified to a cationic peptide Rfe-KKK (net charge = +6) by triple mutation of its positively charged residues Glu256, Asp263 and Asp269 to a basic lysine as well as by C-terminal amidation. As might be expected, the modified peptide was able to target membrane surface with a moderate antibacterial potency (MIC = 50–100 μg/ml). Next, a cyclized version of the linear Rfe-KKK was generated, termed as cycRfe-KKK, which was observed to have improved membrane activity and increased antibacterial potency (MIC < 50 μg/ml) by pre-stabilizing amphipathic hairpin conformation of the peptide.
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      PubDate: 2018-02-26T09:16:25Z
  • CCFS: A Cooperating Coevolution Technique for Large Scale Feature
           Selection on Microarray Datasets
    • 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.
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      PubDate: 2018-02-26T09:16:25Z
  • 3D QSAR Pharmacophore Based Virtual Screening for Identification of
           Potential Inhibitors for CDC25B
    • 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.
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      PubDate: 2018-02-16T08:59:44Z
  • Molecular dynamics studies show solvation structure of type III antifreeze
           protein is disrupted at low pH
    • 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.
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      PubDate: 2018-02-16T08:59:44Z
  • Interferon induced Mx protein from Indian snow trout Schizothorax
           richardsonii (Gray) lacks critical functional features unlike its
           mammalian homologues
    • 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.
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      PubDate: 2018-02-16T08:59:44Z
  • Molecular dynamics simulation studies suggests unconventional roles of
           non-secretary laccases from enteropathogenic gut bacteria and Cryptococcus
           neoformans serotype D
    • 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.
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      PubDate: 2018-02-16T08:59:44Z
  • Allosteric inhibition abrogates dysregulated LFA-1 activation: Structural
           insight into mechanisms of diminished immunologic disease
    • 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.
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      PubDate: 2018-02-16T08:59:44Z
  • A random version of principal component analysis in data clustering
    • 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.
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      PubDate: 2018-02-16T08:59:44Z
  • Multiple Grid Arrangement Improves Ligand Docking with Unknown Binding
           Sites: Application to the Inverse Docking Problem
    • 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
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      PubDate: 2018-02-16T08:59:44Z
  • Markovian Encoding Models in Human splice site recognition using SVM
    • 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
  • In vitro and in silico evaluation of Centaurea saligna (K.Koch)
           Wagenitz—an endemic folk medicinal plant
    • 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.
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      PubDate: 2018-02-16T08:59:44Z
  • Predictive models for tyrosinase inhibitors: challenges from heterogeneous
           activity data determined by different experimental protocols
    • 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.
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      PubDate: 2018-02-16T08:59:44Z
  • Collective transcriptomic deregulation of hypertrophic and dilated
           cardiomyopathy – Importance of fibrotic mechanism in heart failure
    • 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.
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      PubDate: 2018-02-16T08:59:44Z
  • Guiding Exploration in Conformational Feature Space with Lipschitz
           Underestimation for ab-initio Protein Structure Prediction
    • 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.
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      PubDate: 2018-02-16T08:59:44Z
  • The effect of in silico targeting Pseudomonas aeruginosa Patatin-like
           protein D, for immunogenic administration
    • Abstract: Publication date: Available online 5 February 2018
      Source:Computational Biology and Chemistry
      Author(s): Alireza Salimi Chirani, Robabeh Majidzadeh, Ramin Pouriran, Mohsen Heidary, Mohammad Javad Nasiri, Mehrdad Gholami, Mehdi Goudarzi, Vahid Fallah Omrani
      Vaccine candidates which have been introduced for immunization against Pseudomonas aeruginosa strains as are quite diverse. In fact, there is no proper antigen as vaccine against this ubiquitous pathogen in the market yet. Complications caused by this bacterium due to rapid developments of multiple drug resistant strains led to clinical problem world-wide. P. aeruginosa encodes plenty specific virulence elements which could be reckoned as an appropriate vaccine candidate. Type Vd secretion system which termed patatin-like protein D, is a novel P. aeruginosa auto-transporter system. It was obtained that cellular or humoral immune responses could be elevated by chimeric proteins carry epitopes. It has been recognized that in silico tools are essential for the evaluation of new chimeric antigens. The nobility of the present in silico study was modeling and assessment of both humoral and cellular immune potential against P. aeruginosa type Vd secretion system apparatus as strong phospholipase A2 cytotoxin. The patatin-like protein D was assessed by multiple sequence alignment and homology evaluation. The extremely conserved regions were designated for construction of the chimeric molecule. The predicted allergenic and physicochemical properties of the target introduced the molecule as non-allergic and stable molecule. The high-resolution secondary and tertiary structural conformation were created. Indeed, the B-and T-cell restricted epitopes mapping on the chimeric target protein confirmed that the engineered protein contained tremendous both B-cell and T-cell corresponding epitopes. In this investigation, it was magnificently attained that the chimeric molecule as potent lipolytic enzyme composed numerous B-and T-cell restricted epitope and could provoke both humoral and cellular immune responses. The results indicate that this molecule have therapeutic potential against several potent pathogenic P. aeruginosa strains.
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      PubDate: 2018-02-16T08:59:44Z
  • Normal mode analysis of Zika virus
    • Abstract: Publication date: February 2018
      Source:Computational Biology and Chemistry, Volume 72
      Author(s): Byung Ho Lee, Soojin Jo, Moon-ki Choi, Min Hyeok Kim, Jae Boong Choi, Moon Ki Kim
      In recent years, Zika virus (ZIKV) caused a new pandemic due to its rapid spread and close relationship with microcephaly. As a result, ZIKV has become an obvious global health concern. Information about the fundamental viral features or the biological process of infection remains limited, despite considerable efforts. Meanwhile, the icosahedral shell structure of the mature ZIKV was recently revealed by cryo-electron microscopy. This structural information enabled us to simulate ZIKV. In this study, we analyzed the dynamic properties of ZIKV through simulation from the mechanical viewpoint. We performed normal mode analysis (NMA) for a dimeric structure of ZIKV consisting of the envelope proteins and the membrane proteins as a unit structure. By analyzing low-frequency normal modes, we captured intrinsic vibrational motions and defined basic vibrational properties of the unit structure. Moreover, we also simulated the entire shell structure of ZIKV at the reduced computational cost, similar to the case of the unit structure, by utilizing its icosahedral symmetry. From the NMA results, we can not only comprehend the putative dynamic fluctuations of ZIKV but also verify previous inference such that highly mobile glycosylation sites would play an important role in ZIKV. Consequently, this theoretical study is expected to give us an insight on the underlying biological functions and infection mechanism of ZIKV.
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      PubDate: 2018-02-16T08:59:44Z
  • NFκB pathway analysis: An approach to analyze gene co-expression networks
           employing feedback cycles
    • Abstract: Publication date: February 2018
      Source:Computational Biology and Chemistry, Volume 72
      Author(s): Fabiane Cristine Dillenburg, Alfeu Zanotto-Filho, José Cláudio Fonseca Moreira, Leila Ribeiro, Luigi Carro
      The genes of the NFκB pathway are involved in the control of a plethora of biological processes ranking from inhibition of apoptosis to metastasis in cancer. It has been described that Gliobastoma multiforme (GBM) patients carry aberrant NFκB activation, but the molecular mechanisms are not completely understood. Here, we present a NFκB pathway analysis in tumor specimens of GBM compared to non-neoplasic brain tissues, based on the different kind of cycles found among genes of a gene co-expression network constructed using quantized data obtained from the microarrays. A cycle is a closed walk with all vertices distinct (except the first and last). Thanks to this way of finding relations among genes, a more robust interpretation of gene correlations is possible, because the cycles are associated with feedback mechanisms that are very common in biological networks. In GBM samples, we could conclude that the stoichiometric relationship between genes involved in NFκB pathway regulation is unbalanced. This can be measured and explained by the identification of a cycle. This conclusion helps to understand more about the biology of this type of tumor.
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      PubDate: 2018-02-16T08:59:44Z
  • An integrative in silico approach to the structure of Omp33-36 in
           Acinetobacter baumannii
    • Abstract: Publication date: February 2018
      Source:Computational Biology and Chemistry, Volume 72
      Author(s): Abolfazl Jahangiri, Iraj Rasooli, Parviz Owlia, Abbas Ali Imani Fooladi, Jafar Salimian
      Omp33-36 in A. baumannii, a bacterium causing serious nosocomial infections, is a virulence factor associated with the pathogen metabolic fitness as well as its adherence and invasion to human epithelial cells. This protein is also involved in interaction of the bacteria with host cells by binding to fibronectin. Moreover, Omp33-36 renders cytotoxicity to A. baumannii in addition to inducing apoptosis and modulation of autophagy. In the present study, an integrated strategy is launched to pierce into the 3D structure of Omp33-36 protein. The signal peptide within the sequence was determined, then, topology as well as secondary and tertiary structures of the protein were predicted. The mature protein assigned as a 14-stranded barrel in which residues 1–19 is removed as signal peptide. The obtained 3D models were evaluated in terms of quality; and then, served as queries to find similar protein structures. The hits were analyzed regarding topology among which 14-stranded were considered. The most qualified model was refined and then its sequence aligned to its counterpart similar structure protein (CymA from Klebsiella oxytoca). The determined structure of Omp33-36 could justify its porin function and carbapenem-resistance associated with the loss of this protein.
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      PubDate: 2018-02-16T08:59:44Z
  • DEEPAligner: Deep encoding of pathways to align epigenetic signatures
    • Abstract: Publication date: February 2018
      Source:Computational Biology and Chemistry, Volume 72
      Author(s): R. Visakh, K.A. Abdul Nazeer
      Background and objective Recently, differential DNA Methylation is known to affect the regulatory mechanism of biological pathways. A pathway encompasses a set of interacting genes or gene products that altogether perform a given biological function. Pathways often encode strong methylation signatures that are capable of distinguishing biologically distinct subtypes. Even though Next Generation Sequencing techniques such as MeDIP-seq and MBD-isolated genome sequencing (MiGS) allow for genome-wide identification of clinical and biological subtypes, there is a pressing need for computational methods to compare epigenetic signatures across pathways. Methods A novel alignment method, called DEEPAligner (Deep Encoded Epigenetic Pathway Aligner), is proposed in this paper that finds functionally consistent and topologically sound alignments of epigenetic signatures from pathway networks. A deep embedding framework is used to obtain epigenetic signatures from pathways which are then aligned for functional consistency and local topological similarity. Results Experiments on four benchmark cancer datasets reveal epigenetic signatures that are conserved in cancer-specific and across-cancer subtypes. Conclusion The proposed deep embedding framework obtains highly coherent signatures that are aligned for biological as well as structural orthology. Comparison with state-of-the-art network alignment methods clearly suggest that the proposed method obtains topologically and functionally more consistent alignments. Availability
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      PubDate: 2018-02-16T08:59:44Z
  • Physical quantity of residue electrostatic energy in flavin mononucleotide
           binding protein dimer
    • Abstract: Publication date: February 2018
      Source:Computational Biology and Chemistry, Volume 72
      Author(s): Nadtanet Nunthaboot, Arthit Nueangaudom, Kiattisak Lugsanangarm, Somsak Pianwanit, Sirirat Kokpol, Fumio Tanaka
      The electrostatic (ES) energy of each residue was for the first time quantitatively evaluated in a flavin mononucleotide binding protein (FBP). A residue electrostatic energy (RES) was obtained as the sum of the ES energies between atoms in each residue and all other atoms in the FBP dimer using atomic coordinates obtained by a molecular dynamics (MD) simulation. ES is one of the most important energies among the interaction energies in a protein. It is determined from the RES, the residues which mainly contribute to stabilize the structure of each subunit, and the binding energy between two subunits can be estimated. The RES of all residues in subunit A (Sub A) and subunit B (Sub B) were attractive forces, even though the residues contain net negative or positive charges. This reveals that the ES energies of any of the residues can contribute to stabilize the protein structure. The total binding ES energy over all residues among the subunits was distributed between −0.2 to −1.2 eV (mean = −0.67 eV) from the MD simulation time.
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      PubDate: 2018-02-16T08:59:44Z
  • Quantum Molecular Modelling of Hepatitis C Virus Inhibition through
           Non-Structural Protein 5B Polymerase Receptor Binding of C5-Arylidene
    • 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.
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      PubDate: 2018-02-16T08:59:44Z
  • Patterns of cation binding to the aromatic amino acid R groups in Trp,
           Tyr, and Phe
    • Abstract: Publication date: February 2018
      Source:Computational Biology and Chemistry, Volume 72
      Author(s): Shelby L. Scherer, Amanda L. Stewart, Ryan C. Fortenberry
      Previous joint experimental and theoretical work demonstrates that typically soluble peptides will be rendered insoluble in the presence of saturated sodium ions in aqueous solution due to disruption of cation-π interactions between Trp and Lys. The present work utilizes quantum chemical methods including density functional theory, symmetry-adapted perturbation theory, and even coupled cluster theory to determine the strengths of cation-π interactions for the aromatic R groups of Trp, Tyr, and Phe (approximated as skatole, methyl phenol, and toluene) with both alkali and alkaline-Earth atomic cations and electron-accepting R groups from Lys, Arg, and His approximated as methyl ammonium, guanidinium, and imidazolium cations. This work shows that sodium ion is still the most likely disrupter of peptide folding built upon cation-π interactions, since Trp, Tyr, and Phe all bind more strongly to sodium ion than to any of the polyatomic cations. Additionally, the atomic cation complex binding energies decrease with an increase in partial charge on the atomic cation in the complex. However, as the average partial charge increases in the interacting hydrogen atoms in the polyatomic cations, the binding energy increases. The disruption of such peptide–peptide cation-π interactions is certainly relevant for peptide design in β-sheets or β-hairpin structures, but it could also have implications for astrobiology.
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      PubDate: 2018-01-05T19:20:03Z
  • CORAL: QSAR Models for Carcinogenicity of Organic Compounds For Male and
           Female Rats
    • Abstract: Publication date: Available online 2 January 2018
      Source:Computational Biology and Chemistry
      Author(s): Alla P. Toropova, Andrey A. Toropov
      Quantitative structure - activity relationships (QSARs) for carcinogenicity (rats, TD50 ) have been built up using the CORAL software. Different molecular features, which are extracted from simplified molecular input-line entry system (SMILES) serve as the basis for building up a model. Correlation weights for the molecular features are calculated by means of the Monte Carlo optimization. Using the numerical data on the correlation weights, one can calculate a model of carcinogenicity as a mathematical function of descriptors, which are sum of the corresponding correlation weights. In other words, the correlation weights provide the maximal correlation coefficient between the descriptor and carcinogenicity, for the training set. This correlation was assessed via external validation set. Finally, lists of molecular alerts in aspects of carcinogenicity for male rats and for female rats were compared and their differences were characterized.
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      PubDate: 2018-01-05T19:20:03Z
  • Identification of potential inhibitors against nuclear Dam1 complex
           subunit Ask1 of Candida albicans using virtual screening and MD
    • Abstract: Publication date: Available online 1 January 2018
      Source:Computational Biology and Chemistry
      Author(s): Himanshu Tripathi, Feroz Khan
      Identification of hit compounds against specific target form the starting point for a drug discovery program. A consistent decline of new chemical entities (NCEs) in recent years prompted a challenge to explore newer approaches to discover potential hit compounds that in turn can be converted into leads, and ultimately drug with desired therapeutic efficacy. The vast amount of omics and activity data available in public databases offers an opportunity to identify novel targets and their potential inhibitors. State of the art in silico methods viz., clustering of compounds, virtual screening, molecular docking, MD simulations and MMPBSA calculations were employed in a pipeline to identify potential ‘hits’ against those targets as well whose structures, as of now, could only predict through threading approaches. In the present work, we have started from scratch, amino acid sequence of target and compounds retrieved from PubChem compound database, modeled it in such a way that led to the identification of possible inhibitors of Dam1 complex subunit Ask1 of Candida albicans. We also propose a ligand based binding site determination approach. We have identified potential inhibitors of Ask1 subunit of a Dam1 complex of C. albicans, which is required to prevent precocious spindle elongation in pre-mitotic phases. The proposed scheme may aid to find virtually potential inhibitors of other unique targets against candida.
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      PubDate: 2018-01-05T19:20:03Z
  • Synthesis, biological evaluation and molecular docking studies of novel
           benzimidazole derivatives
    • Abstract: Publication date: Available online 30 December 2017
      Source:Computational Biology and Chemistry
      Author(s): Gagandeep Singh, Amanjot Singh, Raman K. Verma, Rajiv Mall, Uzma Azeem
      A novel series of N-substituted-benzimidazolyl linked para substituted benzylidene based molecules containing three pharmacologically potent hydrogen bonding parts namely; 2,4-thiazolidinedione (TZD: a 2,4-dicarbonyl), diethyl malonate (DEM: a 1,3-diester and an isooxazolidinedione analog) and methyl acetoacetate (MAA: a β-ketoester) (6a–11b) were synthesized and evaluated for in vitro α-glucosidase inhibition. The structure of the novel synthesized compounds was confirmed through the spectral studies (LC–MS, 1H NMR, 13C NMR, FT-IR). Comparative evaluation of these compounds revealed that the compound 9b showed maximum inhibitory potential against α-amylase and α-glucosidase giving an IC50 value of 0.54 ± 0.01 μM. Furthermore, binding affinities in terms of G score values and hydrogen bond interactions between all the synthesized compounds and the AA residues in the active site of the protein (PDB code: 3TOP) to that of Acarbose (standard drug) were explored with the help of molecular docking studies. Compound 9b was considered as promising candidate of this series.
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      PubDate: 2018-01-05T19:20:03Z
  • Proteome-scale identification of Leishmania infantum for novel vaccine
           candidates: A hierarchical subtractive approach
    • Abstract: Publication date: Available online 24 December 2017
      Source:Computational Biology and Chemistry
      Author(s): Bahareh Vakili, Navid Nezafat, Gholam Reza Hatam, Bijan Zare, Nasrollah Erfani, Younes Ghasemi
      Vaccines are one of the most significant achievements in medical science. However, vaccine design is still challenging at all stages. The selection of antigenic peptides as vaccine candidates is the first and most important step for vaccine design. Experimental selection of antigenic peptides for the design of vaccines is a time-consuming, labor-intensive and expensive procedure. More recently, in the light of computer-aided biotechnology and reverse vaccinology, the precise selection of antigenic peptides and rational vaccine design against many pathogens have developed. In this study, the whole proteome of Leishmania infantum was analyzed using a pipeline of algorithms. From the set of 8045 proteins of L. infantum, sixteen novel antigenic proteins were derived using a hierarchical proteome subtractive analysis. These novel vaccine targets can be utilized as top candidates for designing the new prophylactic or therapeutic vaccines against visceral leishmaniasis. Significantly, all the sixteen novel vaccine candidates are non-allergen antigenic proteins that have not been used for the design of vaccines against visceral leishmaniasis until now.

      PubDate: 2017-12-24T19:00:57Z
  • Rational design of methicillin resistance staphylococcus aureus Inhibitors
           through 3D-QSAR, molecular docking and molecular dynamics simulations
    • 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.
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      PubDate: 2017-12-24T19:00:57Z
  • AROHap: An Effective Algorithm for Single Individual Haplotype
           Reconstruction based on Asexual Reproduction Optimization
    • Abstract: Publication date: Available online 14 December 2017
      Source:Computational Biology and Chemistry
      Author(s): Mohammad-H Olyaee, Alireza Khanteymoori
      In this paper, a method for single individual haplotype (SIH) reconstruction using Asexual reproduction optimization (ARO) is proposed. Haplotypes, as a set of genetic variations in each chromosome, contain vital information such as the relationship between human genome and diseases. Finding haplotypes in diploid organisms is a challenging task. Experimental methods are expensive and require special equipment. In SIH problem, we encounter with several fragments and each fragment covers some parts of desired haplotype. The main goal is bi-partitioning of the fragments with minimum error correction (MEC). This problem is addressed as NP-hard and several attempts have been made in order to solve it using heuristic methods. The current method, AROHap, has two main phases. In the first phase, most of the fragments are clustered based on a practical metric distance. In the second phase, ARO algorithm as a fast convergence bio-inspired method is used to improve the initial bi-partitioning of the fragments in the previous step. AROHap is implemented with several benchmark datasets. The experimental results demonstrate that satisfactory results were obtained, proving that AROHap can be used for SIH reconstruction problem.

      PubDate: 2017-12-24T19:00:57Z
  • Exciton states and optical properties of the CP26 photosynthetic protein
    • Abstract: Publication date: Available online 13 December 2017
      Source:Computational Biology and Chemistry
      Author(s): Daniil V. Khokhlov, Aleksandr S. Belov, Vadim V. Eremin
      The photosynthetic complex CP26, one of the minor antennae of the photosystem II, plays an important role in regulation of the excitation energy transfer in the PSII. Due to instability during isolation and purification, it remained poorly studied from the viewpoint of theoretical chemistry because of the absence of X-ray crystallography data. In this work, using the recently determined three-dimensional structure of the complex we apply the quantum chemical approach to study the properties of exciton states in it. Spectral properties, structure of exciton states and roles of the pigments in the complex and photosystem II are discussed.
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      PubDate: 2017-12-24T19:00:57Z
  • Identification of Novel nt-MGAM Inhibitors for Potential Treatment of Type
           2 Diabetes: Virtual Screening, Atom based 3D-QSAR Model, Docking Analysis
           and ADME Study
    • Abstract: Publication date: Available online 12 December 2017
      Source:Computational Biology and Chemistry
      Author(s): Aicha Laoud, Fouad Ferkous, Laura Maccari, Giorgio Maccari, Youcef Saihi, Khaireddine Kraim
      In this study, a virtual screening procedure was applied to identify new potential nt-MGAM inhibitors as a possible medication for type 2 diabetes. To this aim, a series of salacinol analogues were first investigated by docking analysis for their binding to the X-ray structure of the biological target nt-MGAM. Key interactions for ligand binding into the receptor active site were identified which shared common features to those found for other known inhibitors, which strengthen the results of this study. 3D QSAR model was then built and showed to be statistically significant and with a good predictive power for the training (R2 =0.99, SD=0.17, F=555.3 and N=27) and test set (Q2 =0.81, Pearson(r)=0.92, RMSE=0.52, N=08). The model was then used to virtually screen the ZINC database with the aim of identifying novel chemical scaffolds as potential nt-MGAM inhibitors. Further, in silico predicted ADME properties were investigated for the most promising molecules. The outcome of this investigation sheds light on the molecular characteristics of the binding of salacinol analogues to nt-MGAM enzyme and identifies new possible inhibitors which have the potential to be developed into drugs, thus significantly contributing to the design and optimization of therapeutic strategies against type 2 diabetes.
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      PubDate: 2017-12-13T11:23:55Z
  • Experimental and density functional theory studies on benzalkonium
           ibuprofenate, a double active pharmaceutical ingredient
    • Abstract: Publication date: Available online 9 December 2017
      Source:Computational Biology and Chemistry
      Author(s): K.P. Safna Hussan, M. Shahin Thayyil, Vijisha K. Rajan, K. Muraleedharan
      Molecular aspects of a double active pharmaceutical ingredient in ionic liquid form, benzalkonium ibuprofenate (BaIb), were studied using density functional theory (DFT/B3LYP/6-31+G (d, p)). A detailed discussion on optimized geometry, energy, heat and the enthalpy of BaIb was carried out. The computed vibrational results agree well with the experimental results. The stability and biological activity were compared to the parent drugs on the basis of global descriptive parameters. The electrophilic and nucleophilic sites were pointed out in the MESP structures well evidently. NBO analysis was also done to predict the relative aromaticity, delocalization effects and the contribution towards stabilization energy of the title compound. The information about non-covalent, non-ionic weak interaction between the cation and anion were obtained from the list of Mulliken charges and NBO analysis.
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      PubDate: 2017-12-13T11:23:55Z
  • In silico toxicity profiling of natural product compound libraries from
           African flora with anti-malarial and anti-HIV properties
    • Abstract: Publication date: Available online 6 December 2017
      Source:Computational Biology and Chemistry
      Author(s): Pascal Amoa Onguéné, Conrad V. Simoben, Ghislain W. Fotso, Kerstin Andrae-Marobela, Sami A. Khalid, Bonaventure T. Ngadjui, Luc Meva’a Mbaze, Fidele Ntie-Kang
      This paper describes an analysis of the diversity and chemical toxicity assessment of three chemical libraries of compounds from African flora (the p-ANAPL, AfroMalariaDb, and Afro-HIV), respectively containing compounds exhibiting activities against diverse diseases, malaria and HIV. The diversity of the three data sets was done by comparison of the three most important principal components computed from standard molecular descriptors. This was also done by a study of the most common substructures (MCSS keys). Meanwhile, the in silico toxicity predictions were done through the identification of chemical structural alerts using Lhasa's knowledge based Derek system. The results show that the libraries occupy different chemical space and that only an insignificant part of the respective libraries could exhibit toxicities beyond acceptable limits. The predicted toxicities end points for compounds which were predicted to “plausible” were further discussed in the light of available experimental data in the literature. Toxicity predictions are in agreement when using a machine learning approach that employs graph-based structural signatures. The current study sheds further light towards the use of the studied chemical libraries for virtual screening purposes.
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      PubDate: 2017-12-13T11:23:55Z
  • A novel in silico minigene vaccine based on CD4+ T-helper and B-cell
           epitopes of EG95 isolates for vaccination against cystic echinococcosis
    • Abstract: Publication date: Available online 23 November 2017
      Source:Computational Biology and Chemistry
      Author(s): Mohammad M. Pourseif, Gholamali Moghaddam, Behrouz Naghili, Nazli Saeedi, Sepideh Parvizpour, Ahmad Nematollahi, Yadollah Omidi
      EG95 oncospheral antigen plays a crucial role in Echinococcus granulosus pathogenicity. Considering the diversity of antigen among different EG95 isolates, it seems to be an ideal antigen for designing a universal multivalent minigene vaccine, so-called multi-epitope vaccine. This is the first in silico study to design a construct for the development of global EG95-based hydatid vaccine against E. granulosus in intermediate hosts. After antigen sequence selection, the three-dimensional structure of EG95 was modeled and multilaterally validated. The preliminary parameters for B-cell epitope prediction were implemented such as the possible transmembrane helix, signal peptide, post-translational modifications and allergenicity. The high ranked linear and conformational B-cell epitopes derived from several online web-servers (e.g., ElliPro, BepiPred v1.0, BcePred, ABCpred, SVMTrip, IEDB algorithms, SEPPA v2.0 and Discotope v2.0) were utilized for multiple sequence alignment and then for engineering the vaccine construct. T-helper based epitopes were predicted by molecular docking between the high frequent ovar class II allele (Ovar-DRB1*1202) and hexadecamer fragments of the EG95 protein. Having used the immune-informatics tools, we formulated the first EG95-based minigene vaccine based on T-helper epitope with high-binding affinity to the ovar MHC allele. This designed construct was analyzed for different physicochemical properties. It was also codon-optimized for high-level expression in Escherichia coli k12. Taken all, we propose the present in silico vaccine constructs as a promising platform for the generation of broadly protective vaccines for species and genus-specific immunization of the natural hosts of the parasite.
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      PubDate: 2017-12-06T15:27:21Z
  • Identification of new antibacterial targets in RNA polymerase of
           Mycobacterium tuberculosis by detecting positive selection sites
    • 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.
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      PubDate: 2017-12-06T15:27:21Z
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