for Journals by Title or ISSN
for Articles by Keywords
help
  Subjects -> ENGINEERING (Total: 2278 journals)
    - CHEMICAL ENGINEERING (190 journals)
    - CIVIL ENGINEERING (182 journals)
    - ELECTRICAL ENGINEERING (102 journals)
    - ENGINEERING (1206 journals)
    - ENGINEERING MECHANICS AND MATERIALS (390 journals)
    - HYDRAULIC ENGINEERING (55 journals)
    - INDUSTRIAL ENGINEERING (64 journals)
    - MECHANICAL ENGINEERING (89 journals)

CHEMICAL ENGINEERING (190 journals)                     

Showing 1 - 0 of 0 Journals sorted alphabetically
AATCC Journal of Research     Full-text available via subscription   (Followers: 5)
ACS Sustainable Chemistry & Engineering     Hybrid Journal   (Followers: 2)
Acta Crystallographica Section B: Structural Science, Crystal Engineering and Materials     Hybrid Journal   (Followers: 5)
Acta Polymerica     Hybrid Journal   (Followers: 9)
Additives for Polymers     Full-text available via subscription   (Followers: 20)
Adhesion Adhesives & Sealants     Hybrid Journal   (Followers: 7)
Advanced Chemical Engineering Research     Open Access   (Followers: 30)
Advanced Powder Technology     Hybrid Journal   (Followers: 16)
Advances in Applied Ceramics     Hybrid Journal   (Followers: 5)
Advances in Chemical Engineering     Full-text available via subscription   (Followers: 24)
Advances in Chemical Engineering and Science     Open Access   (Followers: 52)
Advances in Polymer Technology     Hybrid Journal   (Followers: 13)
African Journal of Pure and Applied Chemistry     Open Access   (Followers: 7)
Annual Review of Analytical Chemistry     Full-text available via subscription   (Followers: 9)
Annual Review of Chemical and Biomolecular Engineering     Full-text available via subscription   (Followers: 12)
Anti-Corrosion Methods and Materials     Hybrid Journal   (Followers: 7)
Applied Petrochemical Research     Open Access   (Followers: 2)
Asia-Pacific Journal of Chemical Engineering     Hybrid Journal   (Followers: 7)
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: 3)
Bulletin of Chemical Reaction Engineering & Catalysis     Open Access   (Followers: 2)
Bulletin of the Chemical Society of Ethiopia     Open Access   (Followers: 3)
Carbohydrate Polymers     Hybrid Journal   (Followers: 8)
Catalysts     Open Access   (Followers: 6)
ChemBioEng Reviews     Full-text available via subscription   (Followers: 1)
Chemical and Engineering News     Free   (Followers: 11)
Chemical and Materials Engineering     Open Access   (Followers: 10)
Chemical and Petroleum Engineering     Hybrid Journal   (Followers: 11)
Chemical and Process Engineering     Open Access   (Followers: 23)
Chemical and Process Engineering Research     Open Access   (Followers: 20)
Chemical Engineering & Technology     Hybrid Journal   (Followers: 32)
Chemical Engineering and Processing: Process Intensification     Hybrid Journal   (Followers: 17)
Chemical Engineering and Science     Open Access   (Followers: 16)
Chemical Engineering Communications     Hybrid Journal   (Followers: 13)
Chemical Engineering Education     Full-text available via subscription  
Chemical Engineering Journal     Hybrid Journal   (Followers: 32)
Chemical Engineering Research and Design     Hybrid Journal   (Followers: 21)
Chemical Engineering Research Bulletin     Open Access   (Followers: 10)
Chemical Engineering Science     Hybrid Journal   (Followers: 22)
Chemical Geology     Hybrid Journal   (Followers: 15)
Chemical Papers     Hybrid Journal   (Followers: 2)
Chemical Product and Process Modeling     Hybrid Journal   (Followers: 3)
Chemical Reviews     Full-text available via subscription   (Followers: 155)
Chemical Society Reviews     Full-text available via subscription   (Followers: 41)
Chemical Technology     Open Access   (Followers: 14)
ChemInform     Hybrid Journal   (Followers: 7)
Chemistry & Industry     Hybrid Journal   (Followers: 4)
Chemistry Central Journal     Open Access   (Followers: 4)
Chemistry of Materials     Full-text available via subscription   (Followers: 164)
Chemometrics and Intelligent Laboratory Systems     Hybrid Journal   (Followers: 15)
ChemSusChem     Hybrid Journal   (Followers: 7)
Chinese Chemical Letters     Full-text available via subscription   (Followers: 3)
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  
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: 19)
Corrosion Engineering, Science and Technology     Hybrid Journal   (Followers: 34)
Corrosion Reviews     Hybrid Journal   (Followers: 4)
Crystal Research and Technology     Hybrid Journal   (Followers: 6)
Current Opinion in Chemical Engineering     Open Access   (Followers: 8)
Education for Chemical Engineers     Hybrid Journal   (Followers: 5)
Eksergi     Open Access  
Emerging Trends in Chemical Engineering     Full-text available via subscription   (Followers: 2)
European Polymer Journal     Hybrid Journal   (Followers: 41)
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)
Frontiers of Chemical Science and Engineering     Hybrid Journal   (Followers: 2)
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: 10)
Industrial & Engineering Chemistry Research     Full-text available via subscription   (Followers: 21)
Industrial Chemistry Library     Full-text available via subscription   (Followers: 3)
Industrial Gases     Open Access  
Info Chimie Magazine     Full-text available via subscription   (Followers: 3)
International Journal of Chemical and Petroleum Sciences     Open Access   (Followers: 2)
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: 5)
International Journal of Science and Engineering     Open Access   (Followers: 4)
International Journal of Waste Resources     Open Access   (Followers: 3)
Journal of Chemical Engineering & Process Technology     Open Access   (Followers: 3)
Journal of Applied Crystallography     Hybrid Journal   (Followers: 6)
Journal of Applied Electrochemistry     Hybrid Journal   (Followers: 11)
Journal of Applied Polymer Science     Hybrid Journal   (Followers: 113)
Journal of Biomaterials Science, Polymer Edition     Hybrid Journal   (Followers: 9)
Journal of Bioprocess Engineering and Biorefinery     Full-text available via subscription   (Followers: 1)
Journal of Chemical & Engineering Data     Full-text available via subscription   (Followers: 10)
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: 17)
Journal of Chemical Engineering and Materials Science     Open Access   (Followers: 2)
Journal of Chemical Science and Technology     Open Access   (Followers: 4)
Journal of Chemical Sciences     Partially Free   (Followers: 17)
Journal of Chemical Technology & Biotechnology     Hybrid Journal   (Followers: 10)
Journal of Chemical Theory and Computation     Full-text available via subscription   (Followers: 14)
Journal of CO2 Utilization     Hybrid Journal   (Followers: 2)
Journal of Crystallization Process and Technology     Open Access   (Followers: 8)
Journal of Environmental Chemical Engineering     Hybrid Journal   (Followers: 3)
Journal of Food Measurement and Characterization     Hybrid Journal  
Journal of Food Processing & Technology     Open Access   (Followers: 1)
Journal of Fuel Chemistry and Technology     Full-text available via subscription   (Followers: 4)
Journal of Geochemical Exploration     Hybrid Journal   (Followers: 1)
Journal of Industrial and Engineering Chemistry     Hybrid Journal   (Followers: 1)
Journal of Information Display     Hybrid Journal   (Followers: 1)
Journal of Inorganic and Organometallic Polymers and Materials     Partially Free   (Followers: 8)
Journal of Modern Chemistry & Chemical Technology     Full-text available via subscription   (Followers: 2)
Journal of Molecular Catalysis A: Chemical     Hybrid Journal   (Followers: 5)
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: 4)
Journal of Polymer Engineering     Hybrid Journal   (Followers: 9)
Journal of Polymer Research     Hybrid Journal   (Followers: 6)
Journal of Polymer Science Part C : Polymer Letters     Hybrid Journal   (Followers: 6)
Journal of Polymers     Open Access   (Followers: 3)
Journal of Polymers and the Environment     Hybrid Journal   (Followers: 1)
Journal of Pure and Applied Chemistry Research     Open Access   (Followers: 1)
Journal of the American Chemical Society     Full-text available via subscription   (Followers: 276)
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: 1)
Journal of the Pakistan Institute of Chemical Engineers     Open Access   (Followers: 1)
Journal of the Taiwan Institute of Chemical Engineers     Hybrid Journal   (Followers: 2)
Journal of Water Chemistry and Technology     Hybrid Journal   (Followers: 8)
Jurnal Bahan Alam Terbarukan     Open Access  
Jurnal Inovasi Pendidikan Kimia     Open Access   (Followers: 1)
Jurnal Reaktor     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: 1)
Materials Chemistry and Physics     Full-text available via subscription   (Followers: 14)
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  
Nanocontainers     Open Access  
Nanofabrication     Open Access  
Noise Control Engineering Journal     Full-text available via subscription   (Followers: 2)
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 Processes and Polymers     Hybrid Journal   (Followers: 1)
Plasmas and Polymers     Hybrid Journal  
Polymer     Hybrid Journal   (Followers: 111)
Polymer Bulletin     Hybrid Journal   (Followers: 7)
Polymer Composites     Hybrid Journal   (Followers: 15)
Polyolefins Journal     Open Access  
Powder Technology     Hybrid Journal   (Followers: 14)
Recyclable Catalysis     Open Access   (Followers: 1)
Research on Chemical Intermediates     Hybrid Journal  
Reviews in Chemical Engineering     Hybrid Journal   (Followers: 5)
Revista Cubana de Química     Open Access  
Revista ION     Open Access  
Revista Mexicana de Ingeniería Química     Open Access  
Rubber Chemistry and Technology     Full-text available via subscription   (Followers: 2)
Russian Chemical Bulletin     Hybrid Journal   (Followers: 2)
Russian Journal of Applied Chemistry     Hybrid Journal   (Followers: 1)
Science and Engineering of Composite Materials     Hybrid Journal   (Followers: 59)
Solid Fuel Chemistry     Hybrid Journal  
South African Journal of Chemical Engineering     Open Access   (Followers: 2)
South African Journal of Chemistry     Open Access   (Followers: 2)
Surface Engineering and Applied Electrochemistry     Hybrid Journal   (Followers: 5)
Sustainable Chemical Processes     Open Access   (Followers: 2)
Synthesis Lectures on Chemical Engineering and Biochemical Engineering     Full-text available via subscription  
The Canadian Journal of Chemical Engineering     Hybrid Journal   (Followers: 3)
The Chemical Record     Hybrid Journal   (Followers: 1)
Theoretical Foundations of Chemical Engineering     Hybrid Journal   (Followers: 2)
Transition Metal Chemistry     Hybrid Journal   (Followers: 3)
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  [3039 journals]
  • IDENTIFICATION OF NOVEL ANTI CANCER AGENTS BY APPLYING INSILICO METHODS
           FOR INHIBITION OF TSPO PROTEIN
    • Abstract: Publication date: Available online 14 February 2017
      Source:Computational Biology and Chemistry
      Author(s): Manan Bhargavi, Sree Kanth Sivan, Sarita Rajender Potlapally
      Cancer is a genomic disease characterised as impaired cellular energy metabolism. Cancer cells derive most of their energy from oxidative phosphorylation unlike normal ones during cell progression TSPO protein present in external mitochondrial membrane, is involved in various cellular functions like Cell proliferation, mitochondrial respiration, synthesis of steroids and also participates in import of cholesterol into the inner mitochondrial membrane from outside of the membrane of mitochondria. The 3D model of TSPO protein is built using comparative homology modelling techniques and validated by proSA, Ramachandran plot and ERRAT in the present work. Active site prediction is carried out using SiteMap and literature, which allows the prediction of the important binding pockets for the identification of putative active site. New molecular entities as TSPO inhibitors were obtained from Virtual screening using MS Spectrum databank in Schrodinger suite and were prioritised based on Glide Score. Docking was performed using Autodock to identify molecules with different scaffolds and were prioritised based on binding energy and RMSD values. Qikprop is used to calculate pharmacokinetic properties of the screened molecules which are found to be in permissible range as possible novel inhibitors of TSPO protein to supress cell proliferation.
      Graphical abstract image

      PubDate: 2017-02-19T07:37:52Z
       
  • Enhanced identification of β-lactamases and its classes using sequence,
           physicochemical and evolutionary information with sequence feature
           characterization of the classes
    • Abstract: Publication date: Available online 14 February 2017
      Source:Computational Biology and Chemistry
      Author(s): Abhigyan Nath, S. Karthikeyan
      β-lactamases provides one of the most successful means of evading the therapeutic effects of β lactam class of antibiotics by many gram positive and gram negative bacteria. On the basis of sequence identity, β-lactamases have been identified into four distinct classes- A, B, C and D. The classes A, C and D are the serine β-lactamases and class B is the metallo-lactamse. In the present study, we developed a two stage cascade classification system. The first-stage performs the classification of β-lactamases from non-β-lactamases and the second-stage performs the further classification of β-lactamases into four different β–lactamase classes. In the first-stage binary classification, we obtained an accuracy of 97.3% with a sensitivity of 89.1% and specificity of 98.0% and for the second stage multi-class classification, we obtained an accuracy of 87.3% for the class A, 91.0% for the class B, 96.3% for the class C and 96.4% for class D. A systematic statistical analysis is carried out on the sieved-out, correctly-predicted instances from the second stage classifier, which revealed some interesting patterns. We analyzed different classes of β-lactamases on the basis of sequence and physicochemical property differences between them. Among amino acid composition, H, W, Y and V showed significant differences between the different β-lactamases classes. Differences in average physicochemical properties are observed for isoelectric point, volume, flexibility, hydrophobicity, bulkiness and charge in one or more β-lactamase classes. The key differences in physicochemical property groups can be observed in small and aromatic groups. Among amino acid property group n-grams except charged n-grams, all other property group n-grams are significant in one or more classes. Statistically significant differences in dipeptide counts among different β-lactamase classes are also reported.
      Graphical abstract image

      PubDate: 2017-02-19T07:37:52Z
       
  • Rational design and synthesis of some PPAR-γ agonists: Substituted
           benzylideneamino-benzylidene-thiazolidine-2,4-diones
    • Abstract: Publication date: April 2017
      Source:Computational Biology and Chemistry, Volume 67
      Author(s): Santosh S. Chhajed, Shital Chaskar, Sanjay K. Kshirsagar, G.M Animeshchandra Haldar, Debarshi Kar Mahapatra
      The peroxisome proliferator activator receptor-γ (PPAR-γ) remained the most successful target for management of diabetes mellitus. The present work endeavors rational designing of some novel PPAR-γ agonists bearing benzylideneamino-benzylidene-thiazolidine-2,4-dione scaffold. The research involved virtual screening of 37 different molecules by molecular docking studies performed by Molecular Design Suite (MDS) into the ligand binding domain of PPAR-γ receptor to explore the binding affinity and conformations of the molecules. Eight compounds; TZD1, TZD-4, TZD-7, TZD-16, TZD-25, TZD-28, TZD-34, and TZD-37 demonstrated high affinity for PPAR-γ binding site. The following compounds were taken into the account and synthesized using a multi-step synthesis protocol. The purity of the synthesized compounds was ascertained by sophisticated analytical techniques such as IR, NMR, Mass and elemental analysis. The compounds were tested for glucose uptake assay by using 3T3-L1 cell lines, where all the candidates exhibited nearly similar potential for uptake of glucose into the lines as that of standard drug rosiglitazone. Three molecules; TZD-1, TZD-4, and TZD-34 showed most prominent activity over hyperglycemic control. This research opened new avenues for smart designing of molecules with high efficiency towards the management of hyperglycemia.

      PubDate: 2017-02-13T16:04:54Z
       
  • Construction of new EST-SSRs for Fusarium resistant wheat breeding
    • Abstract: Publication date: Available online 11 February 2017
      Source:Computational Biology and Chemistry
      Author(s): Aysen Yumurtaci, Hulya Sipahi, Ayed Al-Abdallat, Abdulqader Jighly, Michael Baum
      Surveying Fusarium resistance in wheat with easy applicable molecular markers such as simple sequence repeats (SSRs) is a prerequest for molecular breeding. Expressed sequence tags (ESTs) are one of the main sources for development of new SSR candidates. Therefore, 18.292 publicly available wheat ESTs were mined and genotyping of newly developed 55 EST-SSR derived primer pairs produced clear fragments in ten wheat cultivars carrying different levels of Fusarium resistance. Among the proved markers, 23 polymorphic EST-SSRs were obtained and related alleles were mostly found on B and D genome. Based on the fragment profiling and similarity analysis, a 327bp amplicon, which was a product of contig 1207 (chromosome 5BL), was detected only in Fusarium head blight (FHB) resistant cultivars (CM82036 and Sumai) and the amino acid sequences showed a similarity to pathogen related proteins. Another FHB resistance related EST-SSR, Contig 556 (chromosome 1BL) produced a 151bp fragment in Sumai and was associated to wax2-like protein. A polymorphic 204bp fragment, derived from Contig 578 (chromosome 1DL), was generated from root rot (FRR) resistant cultivars (2-49; Altay2000 and Sunco). A total of 98 alleles were displayed with an average of 1.8 alleles per locus and the polymorphic information content (PIC) ranged from 0.11 to 0.78. Dendrogram tree with two main and five sub-groups were displayed the highest genetic relationship between FRR resistant cultivars (2-49 and Altay2000), FRR sensitive cultivars (Seri82 and Scout66) and FHB resistant cultivars (CM82036 and Sumai). Thus, exploitation of these candidate EST-SSRs may help to genotype other wheat sources for Fusarium resistance.
      Graphical abstract image

      PubDate: 2017-02-13T16:04:54Z
       
  • In silico structural and functional analysis of Mesorhizobium ACC
           deaminase
    • Abstract: Publication date: Available online 11 February 2017
      Source:Computational Biology and Chemistry
      Author(s): Krishnendu Pramanik, Tithi Soren, Soumik Mitra, Tushar Kanti Maiti
      Nodulation is one of the very important processes of legume plants as it is the initiating event of fixing nitrogen. Although ethylene has essential role in normal plant metabolism but it has also negative impact on plants particularly in nodule formation in legume plants. It is also produced due to a variety of biotic or abiotic stresses. 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase is a rhizobial enzyme which cleaves ACC (immediate precursor of ethylene) into α-ketobutyrate and ammonia. As a result, the level of ethylene from the plant cells is decreased and the negative impact of ethylene on nodule formation is reduced. ACC deaminase is widely studied in several plant growth promoting rhizobacterial (PGPR) strains including many legume nodulating bacteria like Mesorhizobium sp. It is an important symbiotic nitrogen fixer belonging to the class – alphaproteobacteria under the order Rhizobiales. ACC deaminase has positive role in Legume-rhizobium symbiosis. Rhizobial ACC deaminase has the potentiality to reduce the adverse effects of ethylene, thereby triggering the nodulation process. The present study describes an in silico comparative structural (secondary structure prediction, homology modeling) and functional analysis of ACC deaminase from Mesorhizobium spp. to explore physico-chemical properties using a number of bio-computational tools. M. loti was selected as a representative species of Mesorhizobium genera for 3D modelling of ACC deaminase protein. Correlation by the phylogenetic relatedness on the basis of both ACC deaminase enzymes and respective acdS genes of different strains of Mesorhizobium has also studied.
      Graphical abstract image

      PubDate: 2017-02-13T16:04:54Z
       
  • An in-silico approach to find a peptidomimetic targeting extracellular
           domain of HER3 from a HER3 Nanobody
    • Abstract: Publication date: Available online 10 February 2017
      Source:Computational Biology and Chemistry
      Author(s): Z. Pourhashem, M. Mehrpouya, N. Yardehnavi, A. Eslamparast, F. Kazemi-Lomedasht
      HER3 is an important therapeutic target in cancer treatments. HER3 Nanobodies (Nbs) are a novel class of antibodies with several competitive advantages over conventional antibodies. A peptidomimetic derived from these Nbs can be considered to be a small peptide mimicking some of the molecular recognition interactions of a natural peptide or protein in a three-dimensional (3D) space, with a receptor that has improved properties. In this study, we introduce a new approach to design a peptidomimetic derived from HER3 Nb through an in silico analysis. We propose that the complementarity determining region (CDR3) of HER3 Nb is large enough to effectively interact with HER3 antigen as well as with the entire Nb. A computational analysis has been performed using Nb models retrieved from SWISS-pdb Viewer 4.1.0 (spdbv) as a target spot and HER3 extracellular domain as its antigenic target to identify the interactions between them by the protein-protein docking method. Detailed analysis of selected models with docked complex help us to identify the interacting amino acid residues between the two molecules. The results of in silico analysis show that the CDR3 of HER3 Nb might be used by itself as a peptidomimetic drug instead of the full Nb. HER3 peptidomimetic-derived HER3 Nb may reduce Nb production costs and be used as a substitute for HER3 Nb after further experimental work. The paper demonstrates the feasibility of peptidomimetics designs using bioinformatic tools.
      Graphical abstract image

      PubDate: 2017-02-13T16:04:54Z
       
  • Computer Evaluation of VirE2 Protein Complexes for ssDNA Transfer Ability
    • Abstract: Publication date: Available online 9 February 2017
      Source:Computational Biology and Chemistry
      Author(s): Irina Volokhina, Yury Gusev, Svyatoslav Mazilov, Yelizaveta Moiseeva, Mikhail Chumakov
      The single-stranded transfer DNA from the Ti plasmid of the soil bacteria Agrobacterium nonspecifically integrates into the plant chromosome and is inherited at subsequent cell divisions. How it is transferred across host membranes is unknown, but it is believed that VirE2 proteins form a membrane-spanning pore or channel in a lipid bilayer and possibly mediate the delivery of the single-stranded transfer DNA–VirD2–VirE2 complex to the plant cell chromosomes. The aim of this work was to perform a computer simulation of VirE2’s pore-forming capacity and an evaluation of constructed VirE2 complexes. The oscillating motions of complexes consisting of two and four VirE2 subunits were estimated by the molecular dynamics and normal modes methods. We did not predict any large changes in domain orientation for two and four-subunit VirE2 complexes within simulation times of 1ns. A possible gating mechanism similar to that seen in the ion channels of the complex formed from two VirE2 proteins was proposed, whereas no conformational changes were predicted inside the pore in the complex formed from four VirE2 proteins.
      Graphical abstract image

      PubDate: 2017-02-13T16:04:54Z
       
  • 2,4-Ditellurouracil and its 5-fluoro derivative: Theoretical
           investigations of structural, energetics and ADME parameters
    • Abstract: Publication date: Available online 9 February 2017
      Source:Computational Biology and Chemistry
      Author(s): Ibrahim A. Alswaidan, Kritish Sooknah, Lydia Rhyman, Cemal Parlak, Derek T. Ndinteh, Mohamed I. Elzagheid, Ponnadurai Ramasami
      2,4-Ditellurouracil exhibits keto-enol tautomerism via different pathways resulting in seven tautomers. These pathways were studied in the gas phase using density functional theory method. The functionals used were BLYP, B3LYP and BHLYP and the basis sets were 6–311++G(d,p) for all atoms except that LanL2DZ ECP was used for tellurium atom only. The results indicate that the diketo form is more stable as observed for uracil and its sulfur and selenium analogues. The effect of introducing fluorine at position 5 was also investigated and the energy difference between the diketo and dienol forms is reduced. 2,4-Ditellurouracil and its 5-fluoro analogue are expected to exist exclusively as the diketo form due to the high interconversion energy barrier. We extended the investigation to predict ADME parameters of the most stable diketo and dienol tautomers in view of understanding their biological properties. This research enlightens keto-enol tautomerism of 2,4-ditellurouracil and its 5-fluoro derivative with additional insights to biological functions.
      Graphical abstract image

      PubDate: 2017-02-13T16:04:54Z
       
  • Application of sequential factorial design and orthogonal array composite
           design (OACD) to study combination of 5 prostate cancer drugs
    • Abstract: Publication date: Available online 4 February 2017
      Source:Computational Biology and Chemistry
      Author(s): Xiaolong Jia, Yiyang Li, Alok Sharma, Yulong Li, Guohai Xie, Guoyao Wang, Junhui Jiang, Yue Cheng, Xianting Ding
      Prostate cancer is one of the most common cancers among men in the United States. It is also a major leading cause of cancer death among men of all races. In order to treat prostate cancer, drug combinations are often applied. Drug combinations target at different pathways of cells can potentially lead to higher efficacy and lower toxicity due to drug synergy. In this paper, we sequentially applied a two-level design and a follow-up orthogonal array composite design (OACD) to investigate combinations of five anti-cancer drugs, namely, doxorubicin, docetaxel, paclitaxel, cis-dichlorodiamine platinum and dihydroartemisinin. Our initial screening using a two-level full factorial design identified doxorubicin and docetaxel as the most significant drugs. A follow-up experiment with an OACD revealed more complicated drug interactions among these 5 anti-cancer drugs. Quadratic effects of doxorubicin and paclitaxel appeared to be significant. A further investigation on contour plots of all the two-drug pairs indicated that combination of doxorubicin and docetaxel are the most effective companion, while the combination of cis-dichlorodiamine platinum and dihydroartemisinin showed unknown antagonistic effects which diminished the individual drug anti-cancer efficacy. These observations have significant practical implications in the understanding of anti-cancer drug mechanism that can facilitate clinical practice of better drug combinations.
      Graphical abstract image

      PubDate: 2017-02-06T15:49:06Z
       
  • In silico analyses of heat shock protein 60 and calreticulin to designing
           a novel vaccine shifting immune response toward T helper 2 in
           atherosclerosis
    • Abstract: Publication date: Available online 3 February 2017
      Source:Computational Biology and Chemistry
      Author(s): Ahmad Karkhah, Mahdiye Saadi, Hamid Reza Nouri
      Recent experiments demonstrated that atherosclerosis is a Th1 dominant autoimmune condition, whereas Th2 cells are rarely detected within the atherosclerotic lesions. Several studies have indicated that Th2 type cytokines could be effective in the reduction and stabilization of atherosclerotic plaque. Therefore, the modulation of the adaptive immune response by shifting immune responses toward Th2 cells by a novel vaccine could represent a promising approach to prevent from progression and thromboembolic events in coronary artery disease. In the present study, an in silico approach was applied to design a novel multi-epitope vaccine to elicit a desirable immune response against atherosclerosis. Six novel IL-4 inducing epitopes were selected from HSP60 and calreticulin proteins. To enhance epitope presentation, IL-4 inducing epitopes were linked together by AAY and HEYGAEALERAG linkers. In addition, helper epitopes selected from Tetanus toxin fragment C (TTFrC) were applied to induce CD4+ helper T lymphocytes (HTLs) responses. Moreover, cholera toxin B (CTB) was employed as an adjuvant. A multi-epitope construct was designed based on predicted epitopes which was 320 residues in length. Then, the physico-chemical properties, secondary and tertiary structures, stability, intrinsic protein disorder, solubility and allergenicity of this chimeric protein were analyzed using bioinformatics tools and servers. Based on bioinformatics analysis, a soluble, and non-allergic protein with 35.405kDa molecular weight was designed. Expasy ProtParam classified this chimeric protein as a stable protein. In addition, predicted epitopes in the chimeric vaccine indicated strong potential to induce B-cell mediated immune response and shift immune responses toward protective Th2 immune response. Various in silico analyses indicate that this vaccine is a qualified candidate for improvement of atherosclerosis by inducing immune responses toward T helper 2.
      Graphical abstract image

      PubDate: 2017-02-06T15:49:06Z
       
  • Genome-wide analysis of Excretory/Secretory proteins in root-knot
           nematode, Meloidogyne incognita provides potential targets for parasite
           control
    • Abstract: Publication date: Available online 1 February 2017
      Source:Computational Biology and Chemistry
      Author(s): Shachi Gahoi, Budhayash Gautam
      The root-knot nematode, Meloidogyne incognita causes significant damage to various economically important crops. Infection is associated with secretion of effector proteins into host cytoplasm and interference with host innate immunity. To combat this infection, the identification and functional annotations of Excretory/Secretory (ES) proteins serve as a key to produce durable control measures. The identification of ES proteins through experimental methods are expensive and time consuming while bioinformatics approaches are cost-effective by prioritizing the experimental analysis of potential drug targets for parasitic diseases. In this study, we predicted and functionally annotated the 1,889 ES proteins in M. incognita genome using integration of several bioinformatics tools. Of these 1,889 ES proteins, 473 (25%) had orthologues in free living nematode Caenorhabditis elegans, 825(67.8%) in parasitic nematodes whereas 561 (29.7%) appeared to be novel and M. incognita specific molecules. Of the C. elegans homologues, 17 ES proteins had “loss of function phenotype” by RNA interference and could represent potential drug targets for parasite intervention and control. We could functionally annotate 429 (22.7%) ES proteins using Gene Ontology (GO) terms, 672 (35.5%) proteins to protein domains and established pathway associations for 223 (11.8%) sequences using Kyoto Encyclopaedia of Genes and Genomes (KEGG). The 162 (8.5%) ES proteins were also mapped to several important plant cell-wall degrading CAZyme families including chitinase, cellulase, xylanase, pectate lyase and endo-β-1,4-xylanase. Our comprehensive analysis of M. incognita secretome provides functional information for further experimental study.
      Graphical abstract image

      PubDate: 2017-02-06T15:49:06Z
       
  • Simultaneous estimation of detection sensitivity and absolute copy number
           from digital PCR serial dilution
    • Abstract: Publication date: Available online 1 February 2017
      Source:Computational Biology and Chemistry
      Author(s): Xutao Deng, Brian S. Custer, Michael P. Busch, Sonia Bakkour, Tzong-Hae Lee
      Digital polymerase chain reaction (dPCR) is a refinement of the conventional PCR approach to nucleic acid detection and absolute quantification. Digital PCR works by partitioning a sample of DNA or cDNA into many individual, parallel PCR reactions. Current quantification methods rely on the assumption that the PCR reactions are always able to detect single target molecules. When the assumption does not hold, the copy numbers will be severely underestimated. We developed a novel dPCR quantification method which determines whether the single copy assumption is violated or not by simultaneously estimating the assay sensitivity and the copy numbers using serial dilution data sets. The implemented method is available as an R package “digitalPCR”.

      PubDate: 2017-02-06T15:49:06Z
       
  • A new search subspace to compensate failure of cavity-based localization
           of ligand-binding sites
    • Abstract: Publication date: Available online 31 January 2017
      Source:Computational Biology and Chemistry
      Author(s): Kalpana Singh, Tapobrata Lahiri
      The common exercise adopted in almost all the ligand-binding sites (LBS) predictive methods is to considerably reduce the search space up to a meager fraction of the whole protein. In this exercise it is assumed that the LBS are mostly localized within a search subspace, cavities, which topologically appear to be valleys within a protein surface. Therefore, extraction of cavities is considered as a most important preprocessing step for finally predicting LBS. However, prediction of LBS based on cavity search subspace is found to fail for some proteins. To solve this problem a new search subspace was introduced which was found successful to localize LBS in most of the proteins used in this work for which cavity-based method MetaPocket 2.0 failed. Therefore this work appeared to augment well the existing binding site predictive methods through its applicability for complementary set of proteins for which cavity-based methods might fail. Also, to decide on the proteins for which instead of cavity-subspace the new subspace should be explored, a decision framework based on simple heuristic is made which uses geometric parameters of cavities extracted through MetaPocket 2.0. It is found that option for selecting the new or cavity-search subspace can be predicted correctly for nearly 87.5% of test proteins.
      Graphical abstract image

      PubDate: 2017-02-06T15:49:06Z
       
  • Structure-based virtual screening to identify the beta-lactamase CTX-M-9
           inhibitors: An in silico effort to overcome antibiotic resistance in E.
           coli
    • Abstract: Publication date: Available online 22 January 2017
      Source:Computational Biology and Chemistry
      Author(s): Kambiz Davari, Jamileh Nowroozi, Farzaneh Hosseini, Abbas Akhavan Sepahy, Sako Mirzaie
      Recently, the quick spreads of broad-spectrum beta-lactams antibiotic resistance in pathogenic strains of bacteria have become a major global health problem. These new emerging resistances cause ineffectiveness of antibiotics and increasing the severity of diseases and treatment costs. Among different and diverse resistance targets, we chose a class A beta lactamase, CTX-M-9, with the aim of identifying new chemical entities to be used for further rational drug design. Based on this purpose, a set of 5000 molecules from the Zinc database have been screened by docking experiments using AutoDock Vina software. The best ranked compound, with respect of the previously proved inhibitor compound 19, was further tested by molecular dynamics (MD) simulation. Our molecular modeling analysis demonstrates that ZINC33264777 has ideal characteristics a potent beta lactamase CTX-M-9 inhibitor. In the free form of beta lactamase, NMR relaxation studies showed the extensive motions near the active site and in the Ω-loop. However, our molecular dynamics studies revealed that in the compound 1: beta lactamase complex, the flexibility of Ω-loop was restricted.
      Graphical abstract image

      PubDate: 2017-01-24T01:57:35Z
       
  • A Gibbs sampling method to determine biomarkers for asthma
    • Abstract: Publication date: Available online 22 January 2017
      Source:Computational Biology and Chemistry
      Author(s): Zhi-Jian Huang, Qin-Hai Shen, Yan-Sheng Wu, Ya-Li Huang
      Purpose To identify potential biomarkers and to uncover the mechanisms underlying asthma based on Gibbs sampling. Methods The molecular functions (MFs) with genes greater than 5 were determined using AnnotationMFGO of BAGS package, and the obtained MFs were then transformed to Markov chain (MC). Gibbs sampling was conducted to obtain a new MC. Meanwhile, the average probabilities of MFs were computed via MC Monte Carlo (MCMC) algorithm, followed by identification of differentially expressed MFs based on the probabilities of MF more than 0.6. Moreover, the differentially expressed genes (DEGs) and their correlated genes were screened and merged, called as co-expressed genes. Pathways enrichment analysis was implemented for the co-expressed genes. Results Based on the gene set more than 5, overall 396 MFs were determined. After Gibbs sampling, 5 differentially expressed MF were acquired according to alfa.pi>0.6. Moreover, the genes in these 5 differentially expressed MF were merged, and 110 DEGs were identified. Subsequently, 338 co-expressed genes were gained. Based on the P value<0.01, the co-expressed genes were significantly enriched in 6 pathways. Among these, ubiquitin mediated proteolysis contained the maximum numbers of 35 co-expressed genes, and cell cycle were enriched by the second largest number of 11 co-expressed genes, respectively. Conclusions The identified pathways such as ubiquitin mediated proteolysis and cell cycle might play important roles in the development of asthma and may be useful for developing the credible therapeutic approaches for diagnosis and treatment of asthma in future.
      Graphical abstract image

      PubDate: 2017-01-24T01:57:35Z
       
  • Comparison of the molecular interactions of 7'-carboxyalkyl apigenin
           derivatives with S. cerevisiae α-glucosidase
    • Abstract: Publication date: Available online 19 January 2017
      Source:Computational Biology and Chemistry
      Author(s): Y.J. Qi, H.N. Lu, J.X. Liang, Y.M. Zhao, X.E. Wang, N.Z. Jin
      As one of the most investigated flavonoids, apigenin, is considered to be a strong α-glucosidase inhibitor. However, the clinical utility of apigenin is limited due to its low solubility. It was reported that the solubility and biological activity can be improved by introducing sole carboxyalkyl group into apigenin, especially the 7'-substitution. With the increase of length of the alkyl chain in carboxyalkyl group, B ring of the apigenin derivative is embedded much more deeply into the binding cavity while the carboxyalkyl stretches to the neighboring cavity. All of the terminal carboxyl groups form hydrogen bonding interactions easily with the surrounding polar amino acids, such as His239, Ser244, Arg312 and Asp349. Thus, the electron density values of the carbonyl in the carboxyl group become higher than the solution status due to the strong molecular interactions. In fact, electron densities of most of the chemical bonds are decreased after molecular docking procedure. On compared with the solution phase, however, dipole moments of most of these molecules are increased, and their vectors are reoriented distinctly in the active sites. It is noticed that all of the Highest Occupied Molecular Orbital (HOMO) and Lowest Unoccupied Molecular Orbital (LUMO) are distributed throughout the whole parent apigenin ring in solution phase, whereas the disappeared situation happened on the B rings of some molecules (II–IV) in the active site, leading to higher energy gaps.
      Graphical abstract image

      PubDate: 2017-01-24T01:57:35Z
       
  • Attractors of hypertrophic cardiomyopathy using maximal cliques and
           Attract methods
    • Abstract: Publication date: Available online 19 January 2017
      Source:Computational Biology and Chemistry
      Author(s): Ming-Jun Feng, Hui-Min Chu, Cai-Jie Shen, Bin He, Xian-Feng Du, Yi-Bo Yu, Jing Liu, Xiao-Min Chen
      Background Our study was designed to identify the differential attractor modules related with hypertrophic cardiomyopathy (HCM) by integrating clustering-based on maximal cliques algorithm and Attract method. Methods We firstly recruited the HCM-related microarray data from ArrayExpress database. Next, protein-protein interaction (PPI) networks of normal and HCM were constructed and re-weighted using spearman correlation coefficient (SCC). Then, maximal cliques were found from the PPI networks through the clustering-based on maximal cliques approach. Afterwards, highly overlapped cliques were eliminated or merged according to the interconnectivity, and then modules were obtained. Subsequently, we used Attract method to identify differential attractor modules, following by the pathway enrichment analyses for genes in differential attractor modules. Results After removing the cliques with nodes less than or equal to 4, 926 and 1118 maximal cliques in normal and HCM PPI networks were obtained for module analysis. Then, we obtained 32 and 55 modules from the PPI networks of normal and HCM, respectively. By comparing with normal condition, there were 5 module pairs with the same or similar gene composition. Significantly, based on attract method, we found that these 5 modules were differential attractors. Pathway enrichment analyses indicated that proteasome, ribosome and oxidative phosphorylation were the significant pathways. Conclusions Proteasome, ribosome and oxidative phosphorylation might play pathophysiological roles in HCM.
      Graphical abstract image

      PubDate: 2017-01-24T01:57:35Z
       
  • Response Surface Methodology in Drug Design: A Case Study on Docking
           Analysis of a Potent Antifungal Fluconazole
    • Abstract: Publication date: Available online 19 January 2017
      Source:Computational Biology and Chemistry
      Author(s): Fatemeh Bohlooli, Saghi Sepehri, Nima Razzaghi-Asl
      Molecular docking is a valuable in silico technique for discovery/design of bioactive compounds. A current challenge within docking simulations is the incorporation of receptor flexibility. A useful strategy toward solving such problem would be the docking of a typical ligand into the multiple conformations of the target. In this study, a multifactor response surface model was constructed to estimate the AutoDock based binding free energy of fluconazole within multiple conformations of 14α-demethylase (CYP51) (cross docking) as a validated antifungal target. On the basis of developed models, individual and interactive effects of important experimental parameters on cross docking of fluconazole were elucidated. For this purpose, a set of high-resolution holo crystallographic structures from CYP51 of human pathogen Trypanosoma cruzi were retrieved to statistically model the binding mode and affinity of fluconazole. The changes of AutoDock binding free energy for the complexes of CYP51-fluconazole were elucidated with the simultaneous variations of six independent variables including grid size, grid spacing, number of genetic algorithm (GA) runs, maximum number of energy evaluations, torsion degrees for ligand and quaternion degrees for ligand. It was revealed that grid spacing (distance between adjacent grid points) and maximum number of energy evaluations were two significant model terms. It was also revealed that grid size, torsion degrees for ligand and quaternion degrees for ligand had insignificant effects on estimated binding energy while the effect of GA runs was non-significant. The interactive effect of “torsion degrees for ligand” with number of GA runs was found to be the significant factor. Other important interactive effects were the interaction of “number of GA runs” with “grid spacing” and “number of energy evaluations” with “grid size”. Furthermore; results of modeling studies within several CYP51 conformations exhibited that “number of GA runs” and “number of energy evaluations” were less sensitive to varied target conformations.
      Graphical abstract image

      PubDate: 2017-01-24T01:57:35Z
       
  • An Exponential Galerkin Method for Solutions of HIV Infection Model of
           CD4+ T-cells
    • Abstract: Publication date: Available online 18 January 2017
      Source:Computational Biology and Chemistry
      Author(s): Şuayip Yüzbaşı, Murat Karaçayır
      In this study, we consider a nonlinear first order model about the infection of CD4+ T-cells by HIV. In order to solve it numerically, we present a new method based on exponential polynomials reminiscent of the Galerkin method. Considering the approximate solutions in the form of exponential polynomials, we first substitute these approximate solutions in the original model. Some relations are thus obtained, which we express in terms of matrices. Taking inner product of a set of exponential functions with these matrix expressions then yields a nonlinear system of algebraic equations. The solution of these equations gives the approximate solutions of the model. Additionally, the technique of residual correction, which aims to reduce the error of the approximate solution by estimating this error, is discussed in some detail. The method and the residual correction technique are illustrated with an example. The results are also compared with numerous existing methods from the literature.

      PubDate: 2017-01-24T01:57:35Z
       
  • Pharmacoinformatics study of Piperolactam A from Piper betle root as new
           lead for non steroidal anti fertility drug development
    • Abstract: Publication date: Available online 11 January 2017
      Source:Computational Biology and Chemistry
      Author(s): Sk. Abdul Amin, Plaban Bhattacharya, Souvik Basak, Shovanlal Gayen, Ashis Nandy, Achintya Saha
      Fertility control is a burning problem all over the world to regulate population overflow and maintain ecological balance. This study is an in-silico approach to explore a non-steroidal lead as contraceptive agent in order to avoid several contraindications generated by steroidal analogues. Piperolactam A, an aristolactam isolated from Piper betle Linn. showed binding affinity towards estrogen and progesterone receptor as −8.9 and −9.0 Kcal/mol (inhibition constant Ki =0.294μM and 0.249μM) respectively which is even larger than that of reported antagonists such as Rohitukine and OrgC (binding affinity −8.7 and −8.4Kcal/mol; Ki 0.443μM and 0.685μM respectively). The binding site exploration displayed more hydrogen bonding of Piperolactam A (His 524, Leu 346, Thr 347) than Rohitukine and OrgC (Leu 718) with associated receptors which was further confirmed by molecular dynamics simulations. The drug-likeliness of the compound has been proved from its tally with Lipinsky’s Rule of Five and lowered toxicity such as cardiac toxicity, liver toxicity, mutagenicity and ecological toxicity. Endocrine disruptome and later docking guided molecular simulations revealed that Piperolactam A has weaker binding affinity and/or lower probability of binding with nuclear receptors especially hERG and cytochrome P450. The high Caco-2 permeability suggested more bioavailability hence more therapeutic efficacy of the drug.
      Graphical abstract image

      PubDate: 2017-01-17T07:46:15Z
       
  • Disruption of redox catalytic functions of peroxiredoxin-thioredoxin
           complex in Mycobacterium tuberculosis H37Rv using small interface binding
           molecules
    • Abstract: Publication date: April 2017
      Source:Computational Biology and Chemistry, Volume 67
      Author(s): Arun Bahadur Gurung, Amit Kumar Das, Atanu Bhattacharjee
      Mycobacterium tuberculosis has distinctive ability to detoxify various microbicidal superoxides and hydroperoxides via a redox catalytic cycle involving thiol reductants of peroxiredoxin (Prx) and thioredoxin (Trx) systems which has conferred on it resistance against oxidative killing and survivability within host. We have used computational approach to disrupt catalytic functions of Prx-Trx complex which can possibly render the pathogen vulnerable to oxidative killing in the host. Using protein–protein docking method, we have successfully constructed the Prx-Trx complex. Statistics of interface region revealed contact area of each monomer less than 1500Å2 and enriched in polar amino acids indicating transient interaction between Prx and Trx. We have identified ZINC40139449 as a potent interface binding molecule through virtual screening of drug-like compounds from ZINC database. Molecular dynamics (MD) simulation studies showed differences in structural properties of Prx-Trx complex both in apo and ligand bound states with regard to root mean square deviation (RMSD), radius of gyration (Rg), root mean square fluctuations (RMSF), solvent accessible surface area (SASA) and number of hydrogen bonds (NHBs). Interestingly, we found stability of two conserved catalytic residues Cys61 and Cys174 of Prx and conserved catalytic motif, WCXXC of Trx upon binding of ZINC40139449. The time dependent displacement study reveals that the compound is quite stable in the interface binding region till 30ns of MD simulation. The structural properties were further validated by principal component analysis (PCA). We report ZINC40139449 as promising lead which can be further evaluated by in vitro or in vivo enzyme inhibition assays.
      Graphical abstract image

      PubDate: 2017-01-10T14:49:24Z
       
  • The in silico identification of small molecules for protein-protein
           interaction inhibition in AKAP-Lbc–RhoA signaling complex
    • Abstract: Publication date: April 2017
      Source:Computational Biology and Chemistry, Volume 67
      Author(s): Asifullah Khan, Mehwish Munir, Sara Aiman, Abdul Wadood, Arif-ullah Khan
      The rational design of small molecules that mimic key residues at the interface of interacting proteins can be a successful approach to target certain biological signaling cascades causing pathophysiological outcome. The A-Kinase Anchoring Protein, i.e. AKAP-Lbc, catalyses nucleotide exchange on RhoA and is involved in cardiac repolarization. The oncogenic AKAP-Lbc induces the RhoA GTPase hyperactivity and aberrantly amplifies the signaling pathway leading to hypertrophic cardiomyocytes. We took advantage of the AKAP-Lbc–RhoA complex crystal structure to design in silico small molecules predicted to inhibit the associated pathological signaling cascade. We adopted the strategies of pharmacophore building, virtual screening and molecular docking to identify the small molecules capable to target AKAP-Lbc and RhoA interactions. The pharmacophore model based virtual screening unveils two lead compounds from the TIMBAL database of small molecules modulating the targeted protein-protein interactions. The molecular docking analysis revealed the lead compounds’ potentialities to establish the essential chemical interactions with the key interactive residues of the complex. These features provided a road map for designing additional potent chemical derivatives and fragments of the original lead compounds to perturb the AKAP-Lbc and RhoA interactions. Experimental validations may elucidate the therapeutic potential of these lead chemical scaffolds to deal with aberrant AKAP-Lbc signaling based cardiac hypertrophy.
      Graphical abstract image

      PubDate: 2017-01-10T14:49:24Z
       
  • A L1-regularized feature selection method for local dimension reduction on
           microarray data
    • Abstract: Publication date: April 2017
      Source:Computational Biology and Chemistry, Volume 67
      Author(s): Shun Guo, Donghui Guo, Lifei Chen, Qingshan Jiang
      Dimension reduction is a crucial technique in machine learning and data mining, which is widely used in areas of medicine, bioinformatics and genetics. In this paper, we propose a two-stage local dimension reduction approach for classification on microarray data. In first stage, a new L1-regularized feature selection method is defined to remove irrelevant and redundant features and to select the important features (biomarkers). In the next stage, PLS-based feature extraction is implemented on the selected features to extract synthesis features that best reflect discriminating characteristics for classification. The suitability of the proposal is demonstrated in an empirical study done with ten widely used microarray datasets, and the results show its effectiveness and competitiveness compared with four state-of-the-art methods. The experimental results on St Jude dataset shows that our method can be effectively applied to microarray data analysis for subtype prediction and the discovery of gene coexpression.
      Graphical abstract image

      PubDate: 2017-01-10T14:49:24Z
       
  • Comparative analysis of amino acid composition in the active site of nirk
           gene encoding copper-containing nitrite reductase (CuNiR) in bacterial
           spp.
    • Abstract: Publication date: April 2017
      Source:Computational Biology and Chemistry, Volume 67
      Author(s): Utpal Kumar Adhikari, M. Mizanur Rahman
      The nirk gene encoding the copper-containing nitrite reductase (CuNiR), a key catalytic enzyme in the environmental denitrification process that helps to produce nitric oxide from nitrite. The molecular mechanism of denitrification process is definitely complex and in this case a theoretical investigation has been conducted to know the sequence information and amino acid composition of the active site of CuNiR enzyme using various Bioinformatics tools. 10 Fasta formatted sequences were retrieved from the NCBI database and the domain and disordered regions identification and phylogenetic analyses were done on these sequences. The comparative modeling of protein was performed through Modeller 9v14 program and visualized by PyMOL tools. Validated protein models were deposited in the Protein Model Database (PMDB) (PMDB id: PM0080150 to PM0080159). Active sites of nirk encoding CuNiR enzyme were identified by Castp server. The PROCHECK showed significant scores for four protein models in the most favored regions of the Ramachandran plot. Active sites and cavities prediction exhibited that the amino acid, namely Glycine, Alanine, Histidine, Aspartic acid, Glutamic acid, Threonine, and Glutamine were common in four predicted protein models. The present in silico study anticipates that active site analyses result will pave the way for further research on the complex denitrification mechanism of the selected species in the experimental laboratory.
      Graphical abstract image

      PubDate: 2017-01-10T14:49:24Z
       
  • A DFT study on the complex formation between desferrithiocin and metal
           ions (Mg2+, Al3+, Ca2+, Mn2+, Fe3+, Co2+, Ni2+, Cu2+, Zn2+)
    • Abstract: Publication date: April 2017
      Source:Computational Biology and Chemistry, Volume 67
      Author(s): Sadegh Kaviani, Mohammad Izadyar, Mohammad Reza Housaindokht
      In recent years, Metal-chelating compounds, namely siderphores have been considered very much because of their crucial role in various fields of the environmental researches. Their importance lies in the fact that they are able to be bonded to a variety of metals in addition to iron. A theoretical study on the structures of desferrithiocin siderphore coordinated to Mg2+, Al3+, Ca2+, Mn2+, Fe3+, Co2+, Ni2+, Cu2+ and Zn2+ metal ions was carried out, using the CAM-B3LYP/6-31G(d) level of the theory in the water. In order to understand the factors which control the stability, reactivity and the strength of toxic metals excretion as well as microbial uptake of the metal-siderphore complexes, we examined the stability and binding energies of the desferrithiocin and various metal ions with different spin states. The binding affinity of desferrithiocin to Fe3+ (log β2 =23.88) showed that the desferrithiocin can scavenge the excess iron(III) from the labile sources. Also, the binding energy values were well described by addition of the dispersion-corrected D3 functional. Because of the importance of the charge transfer in the complex formation, donor-acceptor interaction energies were evaluated. Based on this analysis, an increase in the effective nuclear charge increases E(2) values. Vibrational analysis showed that the critical bonds (CO stretching and CH bending) are in the range of 1300–1800cm−1. Finally, some probable correlations between the complexation behavior and quantum chemistry descriptors have been analyzed.
      Graphical abstract image

      PubDate: 2017-01-10T14:49:24Z
       
  • Comparative genome-wide phylogenetic and expression analysis of SBP genes
           from potato (Solanum tuberosum)
    • Abstract: Publication date: April 2017
      Source:Computational Biology and Chemistry, Volume 67
      Author(s): Musa Kavas, Aslıhan Kurt Kızıldoğan, Büşra Abanoz
      Flowering time is a very important phase in transition to reproductive stage of life in higher plants. SQUAMOSA promoter-binding protein (SBP) gene family encodes plant-specific transcription factors that are involved in regulation of several developmental processes, especially flowering. Although SBP-box genes have been identified in different plants, there have been no study indicating the regulatory effect of SBP box in potato flowering. Here, we report for the first time the identification and characterization of SBP-box transcription factors as well as determination of expression level of SBP-box genes in Solanum tuberosum L. an important crop worldwide. Fifteen different SBP-box transcription factor genes were identified in potato genome. They were found to be distributed in nine chromosomes and eight of them included miR156 and miRNA157 target sites. Characterization of amino acid sequences were performed and protein interactions were predicted. In addition, expression levels of five S. tuberosum SBP-box genes were analysed by both in silico and qRT-PCR. All these results provide a better understanding of functional role of SBP-box gene family members in flowering time in potato.
      Graphical abstract image

      PubDate: 2017-01-10T14:49:24Z
       
  • Targeting eukaryotic-like Serine/Threonine Protein Kinase of Mycobacterium
           tuberculosis, PknB with phytomolecules
    • Abstract: Publication date: Available online 9 January 2017
      Source:Computational Biology and Chemistry
      Author(s): Sandeep Appunni, P.M. Rajisha, Muni Rubens, Sangoju Chandana, Himanshu Narayan Singh, Vishnu Swarup
      Tuberculosis (TB), caused by Mycobacterium tuberculosis is one of the most lethal communicable disease globally. As per the WHO Global TB Report (2015), 9.6 million cases were reported in year 2014 alone. The receptor-like protein kinase, PknB is crucial for sustained mycobacterial growth. Therefore, PknB can be a potential target to develop anti-tuberculosis drugs. In present study, we performed a comparative study to investigate binding efficacies of three phytomolecules namely, Demethylcalabaxanthone, Cryptolepine hydrochloride and Ermanin. 3D structures of PknB and phytomolecules were retrieved from Protein Data Bank (PDB ID: 2FUM) and PubChem Chemical Compound Database, respectively. PknB was set to be rigid and phytochemicals were kept free to rotate. All computational simulations were carried out using Autodock 4.0 on Windows platform. In-silico study demonstrated a strong complex formation (large binding constants and low ΔG) between phytomolecules and target protein PknB of Mycobacterium tuberculosis. However, Demethylcalabaxanthone was able to bind PknB more strongly (Kb =6.8×105 M−1, ΔG=−8.06kcal/mol) than Cryptolepine hydrochloride (Kb =3.06×105 M−1, ΔG=−7.58kcal/mol) and Ermanin (Kb =9.8×104 M−1, ΔG=−6.9kcal/mol). These in silico analysis indicate that phytomolecules are capable to target PknB protein efficiently which is vital for mycobacterial survival and therefore can be excellent alternatives to conventional anti-tuberculosis drugs.
      Graphical abstract image

      PubDate: 2017-01-10T14:49:24Z
       
  • Bipartite network analysis reveals metabolic gene expression profiles that
           are highly associated with the clinical outcomes of acute myeloid leukemia
           
    • Abstract: Publication date: Available online 6 January 2017
      Source:Computational Biology and Chemistry
      Author(s): Fanfan Xie, Mingxiong He, Li He, Keqin Liu, Menglong Li, Guoquan Hu, Zhining Wen
      Dysregulated and reprogrammed metabolism is one of the most important characteristics of cancer, and exploiting cancer cell metabolism can aid in understanding the diverse clinical outcomes for patients. To investigate the differences in metabolic pathways among patients with acute myeloid leukemia (AML) and differential survival outcomes, we systematically conducted microarray data analysis of the metabolic gene expression profiles from 384 patients available from the Gene Expression Omnibus and Cancer Genome Atlas databases. Pathway enrichment analysis of differentially expressed genes (DEGs) showed that the metabolic differences between low-risk and high-risk patients mainly existed in two pathways: biosynthesis of unsaturated fatty acids and oxidative phosphorylation. Using the gene-pathway bipartite network, 62 metabolic genes were identified from 272 DEGs involved in 88 metabolic pathways. Based on the expression patterns of the 62 genes, patients with shorter overall survival (OS) durations in the training set (hazard ratio (HR)=1.58, p =0.038) and in two test sets (HR=1.69 and 1.56 and p =0.089 and 0.029, respectively) were well discriminated by hierarchical clustering analysis. Notably, the expression profiles of ALAS2, BCAT1, BLVRB, and HK3 showed distinct differences between the low-risk and high-risk patients. In addition, models for predicting the OS outcome of AML from the 62 gene signatures achieved improved performance compared with previous studies. In conclusion, our findings reveal significant differences in metabolic processes of patients with AML with diverse survival durations and provide valuable information for clinical translation.
      Graphical abstract image

      PubDate: 2017-01-10T14:49:24Z
       
  • Effect of the R119G Mutation on Human P5CR Structure and Its Interactions
           with NAD: Insights Derived from Molecular Dynamics Simulation and Free
           Energy Analysis
    • Abstract: Publication date: Available online 5 January 2017
      Source:Computational Biology and Chemistry
      Author(s): Peng Sang, Yue-Hui Xie, Lin-Hua Li, Yu-Jia Ye, Wei Hu, Jing Wang, Wen Wan, Rui Li, Long-Jun Li, Lin-Ling Ma, Zhi Li, Shu-Qun Liu, Zhao-Hui Meng
      Pyrroline-5-carboxylate reductase (P5CR), an enzyme with conserved housekeeping roles, is involved in the etiology of cutis laxa. While previous work has shown that the R119G point mutation in the P5CR protein is involved, the structural mechanism behind the pathology remains to be elucidated. In order to probe the role of the R119G mutation in cutis laxa, we performed molecular dynamics (MD) simulations, essential dynamics (ED) analysis, and Molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) binding free energy calculations on wild type (WT) and mutant P5CR-NAD complex. These MD simulations and ED analyses suggest that the R119G mutation decreases the flexibility of P5CR, specifically in the substrate binding pocket, which could decrease the kinetics of the cofactor entrance and egress. Furthermore, the MM-PBSA calculations suggest the R119G mutant has a lower cofactor binding affinity for NAD than WT. Our study provides insight into the possible role of the R119G mutation during interactions between P5CR and NAD, thus bettering our understanding of how the mutation promotes cutis laxa.
      Graphical abstract image

      PubDate: 2017-01-10T14:49:24Z
       
  • Predicting protein subcellular localization based on information content
           of gene ontology terms
    • Authors: Shu-Bo Zhang; Qiang-Rong Tang
      Pages: 1 - 7
      Abstract: Publication date: Available online 14 September 2016
      Source:Computational Biology and Chemistry
      Author(s): Shu-Bo Zhang, Qiang-Rong Tang
      Predicting the location where a protein resides within a cell is important in cell biology. Computational approaches to this issue have attracted more and more attentions from the community of biomedicine. Among the protein features used to predict the subcellular localization of proteins, the feature derived from Gene Ontology (GO) has been shown to be superior to others. However, most of the sights in this field are set on the presence or absence of some predefined GO terms. We proposed a method to derive information from the intrinsic structure of the GO graph. The feature vector was constructed with each element in it representing the information content of the GO term annotating to a protein investigated, and the support vector machines was used as classifier to test our extracted features. Evaluation experiments were conducted on three protein datasets and the results show that our method can enhance eukaryotic and human subcellular location prediction accuracy by up to 1.1% better than previous studies that also used GO-based features. Especially in the scenario where the cellular component annotation is absent, our method can achieved satisfied results with an overall accuracy of more than 87%.
      Graphical abstract image

      PubDate: 2016-09-19T04:30:37Z
      DOI: 10.1016/j.compbiolchem.2016.09.009
      Issue No: Vol. 65 (2016)
       
  • An efficient perturbation method to predict the functionally key sites of
           glutamine binding protein
    • Abstract: Publication date: Available online 29 December 2016
      Source:Computational Biology and Chemistry
      Author(s): Dashuai Lv, Cunxin Wang, Chunhua Li, Jianjun Tan, Xiaoyi Zhang
      Glutamine-Binding Protein (GlnBP) of Escherichia coli, an important member of the periplasmic binding protein family, is responsible for the first step in the active transport of glutamine across the cytoplasmic membrane. In this work, the functionally key regulation sites of GlnBP were identified by utilizing a perturbation method proposed by our group, in which the residues whose perturbations markedly change the binding free energy between GlnBP and glutamine are considered to be functionally key residues. The results show that besides the substrate binding sites, some other residues distant from the binding pocket, including the ones in the hinge regions between the two domains, the front- and back- door channels and the exposed region, are important for the function of glutamine binding and transport. The predicted results are well consistent with the theoretical and experimental data, which indicates that our method is an effective approach to identify the key residues important for both ligand binding and long-range allosteric signal transmission. This work can provide some insights into the function performance of GlnBP and the physical mechanism of its allosteric regulation.
      Graphical abstract image

      PubDate: 2016-12-30T14:40:09Z
       
  • In silico approach to identify non-synonymous SNPs in human obesity
           related gene, MC3R (melanocortin-3-receptor)
    • Abstract: Publication date: Available online 29 December 2016
      Source:Computational Biology and Chemistry
      Author(s): Rajan Kumar Singh, Kulandaivelu Mahalingam
      The melanocortin-3-receptor (MC3R) is a novel gene candidate for human obesity, which involved in controlling the energy homeostasis and food intake behavior. The main aim behind this work is to investigate the potentially deleterious non-synonymous single nucleotide polymorphisms (nsSNPs) in obesity related gene MC3R by using six computational tools viz., PolyPhen, I-Mutant, PROVEAN, SIFT, PANTHER and PhD-SNP. In our study, we predicted eight nsSNPs i.e., rs74315393 (Ile146Asn), rs368205448 (Asp121Tyr), rs143321797 (Phe45Ser), rs17847261 (Cys274Ser), rs144166442 (Pro257His), rs370533946 (Leu224Pro), rs371354428 (Pro72Leu) and rs373708098 (Gly249Ser) found to be potentially deleterious. The functional impact of three nsSNPs i.e., rs74315393, rs368205448 and rs143321797 have already been validated experimentally in the context of human obesity. Moreover, Homology modeling and structural analysis were carried out for already experimentally validated nsSNPs i.e., rs74315393, rs368205448 and rs143321797 to check the stability of predicted models. The mutant models showed higher energy and RMSD (Root mean square deviation) values. In addition, FTSite server predicted one nsSNP i.e., rs368205448 (Asp121Tyr) out of eight identified nsSNPs found in the MC3R protein binding site. Thus, the present computational study may suggest that predicted nsSNPs possibly be a better drug target and contribute to the treatment and better understanding of human obesity.
      Graphical abstract image

      PubDate: 2016-12-30T14:40:09Z
       
  • Comparative QSAR studies using HQSAR, CoMFA, and CoMSIA methods on cyclic
           sulfone hydroxyethylamines as BACE1 inhibitors
    • Abstract: Publication date: Available online 23 December 2016
      Source:Computational Biology and Chemistry
      Author(s): Shuqun Zhang, Zichun Lin, Yinglan Pu, Yunqin Zhang, Li Zhang, Zhili Zuo
      The inhibition of β-secretase (BACE1) is currently the main pharmacological strategy available for Alzheimer’s disease (AD). 2D QSAR and 3D QSAR analysis on some cyclic sulfone hydroxyethylamines inhibitors against β-secretase (IC50: 0.002 to 2.75μM) were carried out using hologram QSAR (HQSAR), comparative molecular field analysis (CoMFA), and comparative molecular similarity indices analysis (CoMSIA) methods. The best model based on the training set was generated with a HQSAR q2 value of 0.693 and r2 value of 0.981; a CoMFA q2 value of 0.534 and r2 value of 0.913; and a CoMSIA q2 value of 0.512 and r2 value of 0.973. In order to gain further understand of the vital interactions between cyclic sulfone hydroxyethylamines and the protease, the analysis was performed by combining the CoMFA and CoMSIA field distributions with the active sites of the BACE1. The final QSAR models could be helpful in the design and development of novel active BACE1 inhibitors.
      Graphical abstract image

      PubDate: 2016-12-30T14:40:09Z
       
  • A comparative QSAR analysis and molecular docking studies of phenyl
           piperidine derivatives as potent dual NK1R antagonists/serotonin
           transporter (SERT) inhibitors
    • Abstract: Publication date: Available online 23 December 2016
      Source:Computational Biology and Chemistry
      Author(s): Somayeh Zare, Masood Fereidoonnezhad, Davoud Afshar, Zahra Ramezani
      Depression is a critical mood disorder that affects millions of patients. Available therapeutic antidepressant agents are associated with several undesirable side effects. Recently, it has been shown that Neurokinin 1 receptor (NK1R) antagonists can potentiate the antidepressant effects of serotonin-selective reuptake inhibitors (SSRIs). In this study, a series of phenyl piperidine derivatives as potent dual NK1R antagonists/serotonin transporter (SERT) inhibitors were applied to quantitative structure–activity relationship (QSAR) analysis. A collection of chemometrics methods such as multiple linear regression (MLR), factor analysis–based multiple linear regression (FA-MLR), principal component regression (PCR), and partial least squared combined with genetic algorithm for variable selection (GA-PLS) were applied to make relations between structural characteristics and NK1R antagonism/SERT inhibitory of these compounds. The best multiple linear regression equation was obtained from GA-PLS and MLR for NK1R and SERT, respectively. Based on the resulted model, an in silico-screening study was also conducted and new potent lead compounds based on new structural patterns were designed for both targets. Molecular docking studies of these compounds on both targets were also conducted and encouraging results were acquired. There was a good correlation between QSAR and docking results. The results obtained from validated docking studies indicate that the important amino acids inside the active site of the cavity that are responsible for essential interactions are Glu33, Asp395 and Arg26 for SERT and Ala30, Lys7, Asp31, Phe5 and Tyr82 for NK1R receptors.
      Graphical abstract image

      PubDate: 2016-12-30T14:40:09Z
       
  • Role of computational efficiency indices and pose clustering in effective
           decision making: an example of annulated furanones in Pf-DHFR space
    • Abstract: Publication date: Available online 23 December 2016
      Source:Computational Biology and Chemistry
      Author(s): Manoj Kumar, Tanpreet Kaur, Anuj Sharma
      In the present report, the role of computationally estimated efficiency indices and pose clustering has been demonstrated in effective decision making, resource management and chemical prioritization. As an example, 720 annulated furanones from six different scaffold classes were computationally docked against Pf-DHFR active site using AutoDock 4.2. Many trends were established by navigating efficiency indices (BEI and SEI) in 2D planes. These trends were then explained by comparing interaction profiles of docked poses with that of known actives/inhibitors. Cases where trends emerged from efficiency plotsresonated well with the pattern of a particular cluster diagram were considered as guidelines for optimization purpose. These kind of guidelines could help medicinal chemists in prioritization their work and in effective management of time, energy and chemical resources.
      Graphical abstract image

      PubDate: 2016-12-30T14:40:09Z
       
  • IFC Editorial Board
    • Abstract: Publication date: February 2017
      Source:Computational Biology and Chemistry, Volume 66


      PubDate: 2016-12-23T14:35:32Z
       
  • Title page
    • Abstract: Publication date: February 2017
      Source:Computational Biology and Chemistry, Volume 66


      PubDate: 2016-12-23T14:35:32Z
       
  • Structure and expression of dna methyltransferase genes from apomictic and
           sexual Boechera species
    • Abstract: Publication date: Available online 20 December 2016
      Source:Computational Biology and Chemistry
      Author(s): Kemal Melik Taşkin, Aslıhan Özbilen, Fatih Sezer, Kaan Hürkan, Şebnem Güneş
      In this study, we determined the structure of DNA methyltransferase (DNMT) genes in apomict and sexual Boechera species and investigated the expression levels during seed development. Protein and DNA sequences of diploid sexual Boechera stricta DNMT genes obtained from Phytozome 10.3 were used to identify the homologues in apomicts, Boechera holboellii and Boechera divaricarpa. Geneious R8 software was used to map the short-paired reads library of B. holboellii whole genome or B. divaricarpa transcriptome reads to the reference gene sequences. We determined three DNMT genes; for Boechera spp. METHYLTRANSFERASE1 (MET1), CHROMOMETHYLASE 3 (CMT3) and DOMAINS REARRANGED METHYLTRANSFERASE 1/2 (DRM2). We examined the structure of these genes with bioinformatic tools and compared with other DNMT genes in plants. We also examined the levels of expression in silique tissues after fertilization by semi-quantitative PCR. The structure of DNMT proteins in apomict and sexual Boechera species share common features. However, the expression levels of DNMT genes were different in apomict and sexual Boechera species. We found that DRM2 was upregulated in apomictic Boechera species after fertilization. Phylogenetic trees showed that three genes are conserved among green algae, monocotyledons and dicotyledons. Our results indicated a deregulation of DNA methylation machinery during seed development in apomicts.
      Graphical abstract image

      PubDate: 2016-12-23T14:35:32Z
       
  • In silico Study of Porphyrin-Anthraquinone Hybrids as CDK2 Inhibitor
    • Abstract: Publication date: Available online 19 December 2016
      Source:Computational Biology and Chemistry
      Author(s): Muhammad Arba, Sunandar Iksan, La Ode Ahmad Nur Ramadhan, Daryono Hadi Tjahjono
      Cyclin-Dependent Kinases (CDKs) are known to play crucial roles in controlling cell cycle progression of eukaryotic cell and inhibition of their activity has long been considered as potential strategy in anti-cancer drug research. In the present work, a series of porphyrin-anthraquinone hybrids bearing meso-substituents, i.e. either pyridine or pyrazole rings were designed and computationally evaluated for their Cyclin Dependent Kinase-2 (CDK2) inhibitory activity using molecular docking, molecular dynamics simulation, and binding free energy calculation. The molecular docking simulation revealed that all six porphyrin hybrids were able to bind to ATP-binding site of CDK2 and interacted with key residues constituted the active cavity of CDK2, while molecular dynamics simulation indicated that all porphyrins bound to CDK2 were stable for 6ns. The binding free energies predicted by MM-PBSA method showed that most compounds exhibited higher affinity than that of native ligand (4-anilinoquinazoline, DTQ) and the affinity of mono-H2PyP-AQ was about three times better than that of DTQ, indicating its potential to be advanced as a new CDK2 inhibitor.
      Graphical abstract image

      PubDate: 2016-12-23T14:35:32Z
       
  • Exploring the resistance mechanism of imipenem in carbapenem hydrolysing
           class D beta-lactamases OXA-143 and its variant OXA-231 (D224A) expressing
           Acinetobacter baumannii: An in-silico approach
    • Abstract: Publication date: Available online 7 December 2016
      Source:Computational Biology and Chemistry
      Author(s): Kullappan Malathi, Anand Anbarasu, Sudha Ramaiah
      Acinetobacter baumannii (A. baumannii), is a Gram negative, coccobacilli and is associated with nosocomial infections. The bacterium has developed resistance to all known classes of antibiotics. Multi-drug resistant A. baumannii infections have been treated with the carbapenem group of antibiotics like imipenem and meropenem. Recent reports indicate that A. baumannii has acquired resistance to imipenem due to the secretion of carbapenem hydrolysing class D beta-lactamases (CHDLs). Such CHDLs found in carbapenem resistant A. baumannii belongs to OXA-143 and its variant OXA-231, which has Alanine (A) in place of Aspartic acid (D) at sequence position 224. The mutation of the OXA-231 CHDL alters the catalytic activity of the enzyme. Hence, the present study was carried out to find the probable mechanism of imipenem resistance in OXA-143 and OXA-231 (D224A) CHDLs expressing A. baumannii by employing molecular docking and dynamics. Methods Our study reveals that OXA-143 CHDL-imipenem complex has more binding affinity than OXA-231 (D224A) CHDL-imipenem complex. Our results indicate that there is a strong binding affinity of OXA-143 with imipenem when compared with OXA-243 and this mechanism might be the probable reason for imipenem resistance in OXA-143 expressing A. baumannii strains.
      Graphical abstract image

      PubDate: 2016-12-09T13:21:14Z
       
  • PrAS: Prediction of amidation sites using multiple feature extraction
    • Abstract: Publication date: February 2017
      Source:Computational Biology and Chemistry, Volume 66
      Author(s): Tong Wang, Wei Zheng, Qiqige Wuyun, Zhenfeng Wu, Jishou Ruan, Gang Hu, Jianzhao Gao
      Amidation plays an important role in a variety of pathological processes and serious diseases like neural dysfunction and hypertension. However, identification of protein amidation sites through traditional experimental methods is time consuming and expensive. In this paper, we proposed a novel predictor for Prediction of Amidation Sites (PrAS), which is the first software package for academic users. The method incorporated four representative feature types, which are position-based features, physicochemical and biochemical properties features, predicted structure-based features and evolutionary information features. A novel feature selection method, positive contribution feature selection was proposed to optimize features. PrAS achieved AUC of 0.96, accuracy of 92.1%, sensitivity of 81.2%, specificity of 94.9% and MCC of 0.76 on the independent test set. PrAS is freely available at https://sourceforge.net/p/praspkg.
      Graphical abstract image

      PubDate: 2016-12-03T21:53:35Z
       
  • Structure-based Optimization of Salt-bridge Network across the Complex
           Interface of PTPN4 PDZ Domain with Its Peptide Ligands in Neuroglioma
    • Abstract: Publication date: Available online 30 November 2016
      Source:Computational Biology and Chemistry
      Author(s): Xian Xiao, Qiang-Hua He, Li-Yan Yu, Song-Qing Wang, Yang Li, Hua Yang, Ai-Hua Zhang, Xiao-Hong Ma, Yu-Jie Peng, Bing Chen
      The PTP non-receptor type 4 (PTPN4) is an important regulator protein in learning, spatial memory and cerebellar synaptic plasticity; targeting the PDZ domain of PTPN4 has become as attractive therapeutic strategy for human neuroglioma. Here, we systematically examined the complex crystal structures of PTPN4 PDZ domain with its known peptide ligands; a number of charged amino acid residues were identified in these ligands and in the peptide-binding pocket of PDZ domain, which can constitute a complicated salt-bridge network across the complex interface. Molecular dynamics (MD) simulations, binding free energy calculations and continuum model analysis revealed that the electrostatic effect plays a predominant role in domain–peptide binding, while other noncovalent interactions such as hydrogen bonds and hydrophobic forces are also responsible for the binding. The computational findings were then used to guide structure-based optimization of the interfacial salt-bridge network. Consequently, five peptides were rationally designed using the high-affinity binder Cyto8-RETEV (RETEV−COOH) as template, including four single-point mutants (i.e. Cyto8-mtxe0: RETE E −COOH, Cyto8-mtxd-1: RET D V−COOH, Cyto8-mtxd-3: R D TEV−COOH and Cyto8-mtxk-4: K ETEV−COOH) and one double-point mutant (i.e. Cyto8-mtxd-1k-4: K ET D V−COOH). Binding assays confirmed that three (Cyto8-mtxd-1, Cyto8-mtxk-4 and Cyto8-mtxd-1k-4) out of the five designed peptides exhibit moderately or considerably increased affinity as compared to the native peptide Cyto8-RETEV.
      Graphical abstract image

      PubDate: 2016-12-03T21:53:35Z
       
  • IFC Editorial Board
    • Abstract: Publication date: December 2016
      Source:Computational Biology and Chemistry, Volume 65


      PubDate: 2016-11-26T20:09:57Z
       
  • Title page
    • Abstract: Publication date: December 2016
      Source:Computational Biology and Chemistry, Volume 65


      PubDate: 2016-11-26T20:09:57Z
       
  • Modeling of the catalytic core of Arabidopsis thaliana Dicer-like 4
           protein and its complex with double-stranded RNA
    • Abstract: Publication date: Available online 17 November 2016
      Source:Computational Biology and Chemistry
      Author(s): Agnieszka Mickiewicz, Joanna Sarzyńska, Maciej Miłostan, Anna Kurzyńska-Kokorniak, Agnieszka Rybarczyk, Piotr Łukasiak, Tadeusz Kuliński, Marek Figlerowicz, Jacek Błażewicz
      Plant Dicer-like proteins (DCLs) belong to the Ribonuclease III (RNase III) enzyme family. They are involved in the regulation of gene expression and antiviral defense through RNA interference pathways. A model plant, Arabidopsis thaliana encodes four DCL proteins (AtDCL1-4) that produce different classes of small regulatory RNAs. Our studies focus on AtDCL4 that processes double-stranded RNAs (dsRNAs) into 21 nucleotide trans-acting small interfering RNAs. So far, little is known about the structures of plant DCLs and the complexes they form with dsRNA. In this work, we present models of the catalytic core of AtDCL4 and AtDCL4-dsRNA complex constructed by computational methods. We built a homology model of the catalytic core of AtDCL4 comprising Platform, PAZ, Connector helix and two RNase III domains. To assemble the AtDCL4-dsRNA complex two modeling approaches were used. In the first method, to establish conformations that allow building a consistent model of the complex, we used Normal Mode Analysis for both dsRNA and AtDCL4. The second strategy involved template-based approach for positioning of the PAZ domain and manual arrangement of the Connector helix. Our results suggest that the spatial orientation of the Connector helix, Platform and PAZ relative to the RNase III domains is crucial for measuring dsRNA of defined length. The modeled complexes provide information about interactions that may contribute to the relative orientations of these domains and to dsRNA binding. All these information can be helpful for understanding the mechanism of AtDCL4-mediated dsRNA recognition and binding, to produce small RNA of specific size.
      Graphical abstract image

      PubDate: 2016-11-21T20:01:17Z
       
  • Investigating dysregulated pathways in Staphylococcus aureus (SA) exposed
           macrophages based on pathway interaction network
    • Abstract: Publication date: Available online 13 November 2016
      Source:Computational Biology and Chemistry
      Author(s): Wei Zhou, Yan Zhang, Yue-Hua Li, Shuang Wang, Jing-Jing Zhang, Cui-Xia Zhang, Zhi-Sheng Zhang
      Objective This work aimed to identify dysregulated pathways for Staphylococcus aureus (SA) exposed macrophages based on pathway interaction network (PIN). Methods The inference of dysregulated pathways was comprised of four steps: preparing gene expression data, protein-protein interaction (PPI) data and pathway data; constructing a PIN dependent on the data and Pearson correlation coefficient (PCC); selecting seed pathway from PIN by computing activity score for each pathway according to principal component analysis (PCA) method; and investigating dysregulated pathways in a minimum set of pathways (MSP) utilizing seed pathway and the area under the receiver operating characteristics curve (AUC) index implemented in support vector machines (SVM) model. Results A total of 20,545 genes, 449,833 interactions and 1,189 pathways were obtained in the gene expression data, PPI data and pathway data, respectively. The PIN was consisted of 8,388 interactions and 1,189 nodes, and Respiratory electron transport, ATP synthesis by chemiosmotic coupling, and heat production by uncoupling proteins was identified as the seed pathway. Finally, 15 dysregulated pathways in MSP (AUC=0.999) were obtained for SA infected samples, such as Respiratory electron transport and DNA Replication. Conclusions We have identified 15 dysregulated pathways for SA infected macrophages based on PIN. The findings might provide potential biomarkers for early detection and therapy of SA infection, and give insights to reveal the molecular mechanism underlying SA infections. However, how these dysregulated pathways worked together still needs to be studied.
      Graphical abstract image

      PubDate: 2016-11-15T13:00:54Z
       
  • Insights into structure and function of 30S Ribosomal Protein S2 (30S2) in
           Chlamydophila Pneumoniae: A potent target of Pneumonia
    • Abstract: Publication date: Available online 9 November 2016
      Source:Computational Biology and Chemistry
      Author(s): G. Koteswara Reddy, K. Nagamalleswara Rao, Kiran Yarrakula
      The gene 30S ribosomal protein S2 (30S2) is identified as a potential drug and vaccine target for Pneumonia. Its structural characterization is an important to understand the mechanism of action for identifying its receptor and/or other binding partners. The comparative genomics and proteomics studies are useful for structural characterization of 30S2 in C. Pneumoniae using different bioinformatics tools and web servers. In this study, the protein 30S2 structure was modelled and validated by Ramachandran plot. It is found that the modelled protein under most favoured “core” region was 88.7% and overall G-factor statistics with average score was −0.20. However, seven sequential motifs have been identified for 30S2 with reference codes (PR0095, PF0038, TIGR01012, PTHR11489, SSF52313 and PTHR11489). In addition, seven structural highly conserved residues have been identified in the large cleft are Lys160, Gly161and Arg162 with volume 1288.83Å3 and average depth of the cleft was 10.75Å. Moreover, biological functions, biochemical process and structural constituents of ribosome are also explored. The study will be helped us to understand the sequential, structural, functional and evolutionary clues of unknown proteins available in C. Pneumoniae.
      Graphical abstract image

      PubDate: 2016-11-15T13:00:54Z
       
  • Identification of miRNA from Bouteloua gracilis, a drought tolerant grass,
           by deep sequencing and their in silico analysis
    • Abstract: Publication date: Available online 9 November 2016
      Source:Computational Biology and Chemistry
      Author(s): Perla Lucía Ordóñez-Baquera, Everardo González-Rodríguez, Gerardo Armando Aguado-Santacruz, Quintín Rascón-Cruz, Ana Conesa, Verónica Moreno-Brito, Raquel Echavarria, Joel Dominguez-Viveros
      Background MicroRNAs (miRNAs) are small non-coding RNA molecules that regulate signal transduction, development, metabolism, and stress responses in plants through post-transcriptional degradation and/or translational repression of target mRNAs. Several studies have addressed the role of miRNAs in model plant species, but miRNA expression and function in economically important forage crops, such as Bouteloua gracilis (Poaceae), a high-quality and drought-resistant grass distributed in semiarid regions of the United States and northern Mexico remain unknown. Results We applied high-throughput sequencing technology and bioinformatics analysis and identified 31 conserved miRNA families and 53 novel putative miRNAs with different abundance of reads in chlorophyllic cell cultures derived from B. gracilis. Some conserved miRNA families were highly abundant and possessed predicted targets involved in metabolism, plant growth and development, and stress responses. We also predicted additional identified novel miRNAs with specific targets, including B. gracilis ESTs, which were detected under drought stress conditions. Conclusions Here we report 31 conserved miRNA families and 53 putative novel miRNAs in B. gracilis. Our results suggested the presence of regulatory miRNAs involved in modulating physiological and stress responses in this grass species.
      Graphical abstract image

      PubDate: 2016-11-15T13:00:54Z
       
  • Development of a sugar-binding residue prediction system from protein
           sequences using support vector machine
    • Abstract: Publication date: Available online 9 November 2016
      Source:Computational Biology and Chemistry
      Author(s): Masaki Banno, Yusuke Komiyama, Wei Cao, Yuya Oku, Kokoro Ueki, Kazuya Sumikoshi, Shugo Nakamura, Tohru Terada, Kentaro Shimizu
      Several methods have been proposed for protein–sugar binding site prediction using machine learning algorithms. However, they are not effective to learn various properties of binding site residues caused by various interactions between proteins and sugars. In this study, we classified sugars into acidic and nonacidic sugars and showed that their binding sites have different amino acid occurrence frequencies. By using this result, we developed sugar-binding residue predictors dedicated to the two classes of sugars: an acid sugar binding predictor and a nonacidic sugar binding predictor. We also developed a combination predictor which combines the results of the two predictors. We showed that when a sugar is known to be an acidic sugar, the acidic sugar binding predictor achieves the best performance, and showed that when a sugar is known to be a nonacidic sugar or is not known to be either of the two classes, the combination predictor achieves the best performance. Our method uses only amino acid sequences for prediction. Support vector machine was used as a machine learning algorithm and the position-specific scoring matrix created by the position-specific iterative basic local alignment search tool was used as the feature vector. We evaluated the performance of the predictors using five-fold cross-validation. We have launched our system, as an open source freeware tool on the GitHub repository (http://doi.org/10.5281/zenodo.61513).
      Graphical abstract image Highlights

      PubDate: 2016-11-09T12:45:46Z
       
  • Computational analysis, structural modeling and ligand binding site
           prediction of Plasmodium falciparum 1-deoxy-d-xylulose-5-phosphate
           synthase
    • Abstract: Publication date: Available online 5 November 2016
      Source:Computational Biology and Chemistry
      Author(s): Achintya Mohan Goswami
      Malaria remains one of the most serious infectious diseases in the world. Though there are four species of Plasmodium genus, but the most responsible and virulent among them is Plasmodium falciparum. The unique biochemical processes that exist in Plasmodium falciparum provide a useful way to develop novel inhibitors. One such biochemical pathway is the methyl erythritol phosphate pathway (MEP), required to synthesize isoprenoid precursors. In the present study, a detailed computational analysis has been performed for 1-deoxy-d-xylulose-5-phosphate synthase, a key enzyme in MEP. The protein is found to be stable and residues from 825 to 971 are highly conserved across species. The homology model of the enzyme is developed using three web-based servers and Modeller software. It has twelve disordered regions indicating its druggability. Virtual screening of ZINC database identifies ten potential compounds in thiamine diphosphate binding region of the enzyme.
      Graphical abstract image

      PubDate: 2016-11-09T12:45:46Z
       
 
 
JournalTOCs
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
Email: journaltocs@hw.ac.uk
Tel: +00 44 (0)131 4513762
Fax: +00 44 (0)131 4513327
 
Home (Search)
Subjects A-Z
Publishers A-Z
Customise
APIs
Your IP address: 23.22.53.106
 
About JournalTOCs
API
Help
News (blog, publications)
JournalTOCs on Twitter   JournalTOCs on Facebook

JournalTOCs © 2009-2016