AIMC Topic: Molecular Docking Simulation

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Machine Learning Consensus Scoring Improves Performance Across Targets in Structure-Based Virtual Screening.

Journal of chemical information and modeling Jul 12, 2017
In structure-based virtual screening, compound ranking through a consensus of scores from a variety of docking programs or scoring functions, rather than ranking by scores from a single program, provides better predictive performance and reduces targ...
Benchmarking Drug Evaluation, Preclinical Molecular Targeted Therapy Machine Learning Molecular Docking Simulation User-Computer Interface Proteins
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Machine-Learning-Assisted Approach for Discovering Novel Inhibitors Targeting Bromodomain-Containing Protein 4.

Journal of chemical information and modeling Jul 10, 2017
Bromodomain-containing protein 4 (BRD4) is implicated in the pathogenesis of a number of different cancers, inflammatory diseases and heart failure. Much effort has been dedicated toward discovering novel scaffold BRD4 inhibitors (BRD4is) with differ...
Humans Machine Learning Molecular Docking Simulation Drug Discovery Drug Evaluation, Preclinical Molecular Targeted Therapy Protein Conformation Cell Cycle Proteins Nuclear Proteins Transcription Factors Cell Line Structure-Activity Relationship
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Editorial-Sequences and topology.

Current opinion in structural biology Jun 4, 2017
Humans Machine Learning Animals Molecular Docking Simulation Protein Interaction Domains and Motifs Protein Conformation, alpha-Helical Protein Conformation, beta-Strand Binding Sites Thermodynamics Protein Interaction Mapping Protein Multimerization Protein Binding Computational Biology Proteins
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Protein-Protein Interaction Interface Residue Pair Prediction Based on Deep Learning Architecture.

IEEE/ACM transactions on computational biology and bioinformatics May 19, 2017
MOTIVATION: Proteins usually fulfill their biological functions by interacting with other proteins. Although some methods have been developed to predict the binding sites of a monomer protein, these are not sufficient for prediction of the interactio...
Molecular Docking Simulation Deep Learning Protein Binding Computational Biology Proteins Surface Properties Protein Conformation Binding Sites
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InterPred: A pipeline to identify and model protein-protein interactions.

Proteins Mar 21, 2017
Protein-protein interactions (PPI) are crucial for protein function. There exist many techniques to identify PPIs experimentally, but to determine the interactions in molecular detail is still difficult and very time-consuming. The fact that the numb...
Protein Interaction Mapping Sequence Analysis, Protein Protein Interaction Domains and Motifs Molecular Docking Simulation Computational Biology Support Vector Machine Proteins Internet Benchmarking Amino Acid Sequence Software
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Predicting DPP-IV inhibitors with machine learning approaches.

Journal of computer-aided molecular design Feb 2, 2017
Dipeptidyl peptidase IV (DPP-IV) is a promising Type 2 diabetes mellitus (T2DM) drug target. DPP-IV inhibitors prolong the action of glucagon-like peptide-1 (GLP-1) and gastric inhibitory peptide (GIP), improve glucose homeostasis without weight gain...
Dipeptidyl Peptidase 4 Small Molecule Libraries Dipeptidyl-Peptidase IV Inhibitors Drug Design Diabetes Mellitus, Type 2 Bayes Theorem Humans Machine Learning Molecular Docking Simulation Computer-Aided Design
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Rapid Design of Knowledge-Based Scoring Potentials for Enrichment of Near-Native Geometries in Protein-Protein Docking.

PloS one Jan 24, 2017
Protein-protein docking protocols aim to predict the structures of protein-protein complexes based on the structure of individual partners. Docking protocols usually include several steps of sampling, clustering, refinement and re-scoring. The scorin...
Linear Models Protein Conformation Monte Carlo Method Protein Interaction Mapping Software Protein Binding Models, Molecular Models, Chemical Knowledge Bases Algorithms Computer Simulation Molecular Docking Simulation
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Machine learning and docking models for Mycobacterium tuberculosis topoisomerase I.

Tuberculosis (Edinburgh, Scotland) Jan 20, 2017
There is a shortage of compounds that are directed towards new targets apart from those targeted by the FDA approved drugs used against Mycobacterium tuberculosis. Topoisomerase I (Mttopo I) is an essential mycobacterial enzyme and a promising target...
Dose-Response Relationship, Drug Humans Tuberculosis Molecular Docking Simulation Mycobacterium smegmatis Structure-Activity Relationship Machine Learning Mycobacterium tuberculosis Computer-Aided Design Molecular Targeted Therapy Drug Design Bayes Theorem Protein Conformation DNA Topoisomerases, Type I Antitubercular Agents Topoisomerase I Inhibitors
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A machine learning approach for ranking clusters of docked protein-protein complexes by pairwise cluster comparison.

Proteins Jan 20, 2017
Reliable identification of near-native poses of docked protein-protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein-protein interactions is challenging for traditional biophysical or knowledge based potentials and th...
Machine Learning Software Research Design Binding Sites Cluster Analysis Molecular Docking Simulation Thermodynamics Proteins Protein Binding Protein Interaction Mapping Benchmarking Computational Biology Structural Homology, Protein Protein Conformation
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Synthesis and antimicrobial studies of novel derivatives of 4-(4-formyl-3-phenyl-1H-pyrazol-1-yl)benzoic acid as potent anti-Acinetobacter baumannii agents.

Bioorganic & medicinal chemistry letters Dec 29, 2016
Microbial resistance to antibiotics is a global concern. The World Health Organization (WHO) has identified antimicrobial resistance as one the three greatest threats for human beings in the 21st century. Without urgent and coordinated action, the wo...
Drug Resistance, Multiple, Bacterial Benzoic Acid Anti-Infective Agents Gram-Positive Bacteria Pyrazoles Binding Sites Gram-Negative Bacteria Molecular Docking Simulation Microbial Sensitivity Tests Structure-Activity Relationship Catalytic Domain Acinetobacter baumannii
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