AI Medical Compendium Topic:
Molecular Docking Simulation

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Antileishmanial activity of novel indolyl-coumarin hybrids: Design, synthesis, biological evaluation, molecular docking study and in silico ADME prediction.

Bioorganic & medicinal chemistry letters Dec 24, 2015
In present work we have designed and synthesized total twelve novel 3-(3-(1H-indol-3-yl)-3-phenylpropanoyl)-4-hydroxy-2H-chromen-2-one derivatives 13(a-l) using Ho(3+) doped CoFe2O4 nanoparticles as catalyst and evaluated for their potential antileis...
Coumarins Binding Sites Leishmania Oxidoreductases Protein Structure, Tertiary Enzyme Inhibitors Antiprotozoal Agents Protozoan Proteins Molecular Docking Simulation Drug Design Antioxidants HeLa Cells Inhibitory Concentration 50 Cell Survival Humans Structure-Activity Relationship
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A Sequence-Based Dynamic Ensemble Learning System for Protein Ligand-Binding Site Prediction.

IEEE/ACM transactions on computational biology and bioinformatics Dec 3, 2015
BACKGROUND: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands...
Algorithms Molecular Docking Simulation Protein Binding Proteins Machine Learning Pattern Recognition, Automated Data Interpretation, Statistical Protein Interaction Mapping Binding Sites Models, Chemical Sequence Analysis, Protein Ligands
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Accurate refinement of docked protein complexes using evolutionary information and deep learning.

Journal of bioinformatics and computational biology Nov 24, 2015
One of the major challenges for protein docking methods is to accurately discriminate native-like structures from false positives. Docking methods are often inaccurate and the results have to be refined and re-ranked to obtain native-like complexes a...
Neural Networks, Computer Databases, Protein Molecular Docking Simulation Protein Conformation Proteins
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Prediction the Substrate Specificities of Membrane Transport Proteins Based on Support Vector Machine and Hybrid Features.

IEEE/ACM transactions on computational biology and bioinformatics Nov 11, 2015
Membrane transport proteins and their substrate specificities play crucial roles in a variety of cellular functions. Identifying the substrate specificities of membrane transport proteins is closely related to the protein-target interaction predictio...
Protein Interaction Mapping Protein Binding Sequence Analysis, Protein Support Vector Machine Models, Chemical Binding Sites Algorithms Pattern Recognition, Automated Substrate Specificity Membrane Transport Proteins Molecular Docking Simulation
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idDock+: Integrating Machine Learning in Probabilistic Search for Protein-Protein Docking.

Journal of computational biology : a journal of computational molecular cell biology Jul 29, 2015
Predicting the three-dimensional native structures of protein dimers, a problem known as protein-protein docking, is key to understanding molecular interactions. Docking is a computationally challenging problem due to the diversity of interactions an...
Protein Multimerization Ligands Machine Learning Protein Conformation Algorithms Computational Biology Binding Sites Molecular Docking Simulation Proteins Protein Binding
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Development of 3D-QSAR Model for Acetylcholinesterase Inhibitors Using a Combination of Fingerprint, Molecular Docking, and Structure-Based Pharmacophore Approaches.

Toxicological sciences : an official journal of the Society of Toxicology Jul 21, 2015
Acetylcholinesterase (AChE), a serine hydrolase vital for regulating the neurotransmitter acetylcholine in animals, has been used as a target for drugs and pesticides. With the increasing availability of AChE crystal structures, with or without ligan...
Cholinesterase Inhibitors Expert Systems Catalytic Domain Molecular Conformation Insecticides Ligands Acetylcholinesterase Nootropic Agents Quantitative Structure-Activity Relationship Binding Sites Peptide Mapping Molecular Docking Simulation Imaging, Three-Dimensional Computational Biology Models, Molecular GPI-Linked Proteins Databases, Protein Nerve Tissue Proteins Humans Artificial Intelligence Animals
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Multistage virtual screening and identification of novel HIV-1 protease inhibitors by integrating SVM, shape, pharmacophore and docking methods.

European journal of medicinal chemistry Jul 6, 2015
The HIV-1 protease has proven to be a crucial component of the HIV replication machinery and a reliable target for anti-HIV drug discovery. In this study, we applied an optimized hierarchical multistage virtual screening method targeting HIV-1 protea...
Molecular Docking Simulation Support Vector Machine Dose-Response Relationship, Drug HIV Protease Structure-Activity Relationship HIV Protease Inhibitors Molecular Structure Drug Evaluation, Preclinical
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The study of dual COX-2/5-LOX inhibitors by using electronic-topological approach based on data on the ligand-receptor interactions.

Journal of molecular graphics & modelling Jun 19, 2015
Structural and electronic factors influencing selective inhibition of cyclooxygenase-2 and 5-lipoxygenase (COX-2/5-LOX) were studied by using Electronic-Topological Method combined with Neural Networks (ETM-NN), molecular docking, and Density Functio...
Neural Networks, Computer Algorithms Molecular Docking Simulation Molecular Structure Quantum Theory Protein Binding Structure-Activity Relationship Substrate Specificity Humans Catalytic Domain Arachidonate 5-Lipoxygenase Cyclooxygenase 2 Ligands Lipoxygenase Inhibitors Cyclooxygenase 2 Inhibitors Datasets as Topic
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Multi-Step Protocol for Automatic Evaluation of Docking Results Based on Machine Learning Methods--A Case Study of Serotonin Receptors 5-HT(6) and 5-HT(7).

Journal of chemical information and modeling Apr 8, 2015
Molecular docking, despite its undeniable usefulness in computer-aided drug design protocols and the increasing sophistication of tools used in the prediction of ligand-protein interaction energies, is still connected with a problem of effective resu...
Protein Conformation Receptors, Adrenergic, beta-2 Receptors, Serotonin Molecular Docking Simulation Ligands Machine Learning Automation Algorithms
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Improving AutoDock Vina Using Random Forest: The Growing Accuracy of Binding Affinity Prediction by the Effective Exploitation of Larger Data Sets.

Molecular informatics Feb 12, 2015
There is a growing body of evidence showing that machine learning regression results in more accurate structure-based prediction of protein-ligand binding affinity. Docking methods that aim at optimizing the affinity of ligands for a target rely on h...
Molecular Docking Simulation Machine Learning Models, Theoretical Software
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