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Molecular Docking Simulation

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Optimized Virtual Screening Workflow: Towards Target-Based Polynomial Scoring Functions for HIV-1 Protease.

Combinatorial chemistry & high throughput screening Jan 1, 2017
BACKGROUND: One key step in the development of inhibitors for an enzyme is the application of computational methodologies to predict protein-ligand interactions. The abundance of structural and ligand-binding information for HIV-1 protease opens up t...
Machine Learning Molecular Docking Simulation HIV Protease HIV Protease Inhibitors Drug Evaluation, Preclinical Ligands
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Some Remarks on Prediction of Drug-Target Interaction with Network Models.

Current topics in medicinal chemistry Jan 1, 2017
System-level understanding of the relationships between drugs and targets is very important for enhancing drug research, especially for drug function repositioning. The experimental methods used to determine drug-target interactions are usually time-...
Molecular Targeted Therapy Ion Channels Molecular Docking Simulation Neural Networks, Computer Algorithms Pharmaceutical Preparations Receptors, G-Protein-Coupled Humans Ligands
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Machine Learning and Molecular Dynamics Based Insights into Mode of Actions of Insulin Degrading Enzyme Modulators.

Combinatorial chemistry & high throughput screening Jan 1, 2017
BACKGROUND: Alzheimer's disease (AD) is one of the most common lethal neurodegenerative disorders having impact on the lives of millions of people worldwide. The disease lacks effective treatment options and the unavailability of the drugs to cure th...
Humans Machine Learning Molecular Dynamics Simulation Insulysin Molecular Docking Simulation Drug Discovery
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Integrated machine learning, molecular docking and 3D-QSAR based approach for identification of potential inhibitors of trypanosomal N-myristoyltransferase.

Molecular bioSystems Nov 15, 2016
N-Myristoyltransferase (NMT) catalyzes the transfer of myristate to the amino-terminal glycine of a subset of proteins, a co-translational modification involved in trafficking substrate proteins to membrane locations, stabilization and protein-protei...
Trypanocidal Agents Acyltransferases Catalytic Domain Parasitic Sensitivity Tests Quantitative Structure-Activity Relationship Binding Sites Enzyme Inhibitors Algorithms Molecular Dynamics Simulation Datasets as Topic Molecular Docking Simulation Machine Learning Protein Binding Workflow
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SAnDReS a Computational Tool for Statistical Analysis of Docking Results and Development of Scoring Functions.

Combinatorial chemistry & high throughput screening Jan 1, 2016
BACKGROUND: Docking allows to predict ligand binding to proteins, since the 3D-structure for the target is available. Several docking studies have been carried out to identify potential ligands for drug targets. Many of these studies resulted in the ...
Machine Learning Data Interpretation, Statistical Molecular Docking Simulation Databases, Protein
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Use of machine learning approaches for novel drug discovery.

Expert opinion on drug discovery Jan 1, 2016
INTRODUCTION: The use of computational tools in the early stages of drug development has increased in recent decades. Machine learning (ML) approaches have been of special interest, since they can be applied in several steps of the drug discovery met...
Drug Design Drug Discovery Support Vector Machine Decision Trees Machine Learning Binding Sites Humans Molecular Docking Simulation Models, Biological Neural Networks, Computer Ligands
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Classification models of HCV NS3 protease inhibitors based on support vector machine (SVM).

Combinatorial chemistry & high throughput screening Jan 1, 2015
Inhibition of the hepatitis C virus (HCV) non-structural protein 3 (NS3) serine protease by molecule inhibitors is an attractive strategy for the treatment of hepatitis C. We built four classification models based on a dataset of 413 HCV NS3 protease...
Molecular Docking Simulation Hepacivirus Databases, Pharmaceutical Quantitative Structure-Activity Relationship Protease Inhibitors Support Vector Machine Hepatitis C Viral Nonstructural Proteins Humans
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