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Molecular Docking Simulation

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AK-Score: Accurate Protein-Ligand Binding Affinity Prediction Using an Ensemble of 3D-Convolutional Neural Networks.

International journal of molecular sciences Nov 10, 2020
Accurate prediction of the binding affinity of a protein-ligand complex is essential for efficient and successful rational drug design. Therefore, many binding affinity prediction methods have been developed. In recent years, since deep learning tech...
Computer-Aided Design Drug Design Drug Discovery Humans Neural Networks, Computer Molecular Docking Simulation Proteins Databases, Protein Molecular Dynamics Simulation Ligands Deep Learning User-Computer Interface Protein Binding
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COSMO-RS-Based Descriptors for the Machine Learning-Enabled Screening of Nucleotide Analogue Drugs against SARS-CoV-2.

The journal of physical chemistry letters Oct 26, 2020
Chemical similarity-based approaches employed to repurpose or develop new treatments for emerging diseases, such as COVID-19, correlates molecular structure-based descriptors of drugs with those of a physiological counterpart or clinical phenotype. W...
Pneumonia, Viral RNA-Dependent RNA Polymerase Nucleotides Binding Sites Betacoronavirus Molecular Docking Simulation Principal Component Analysis RNA, Viral Drug Evaluation, Preclinical Quantum Theory Coronavirus Infections Pandemics COVID-19 SARS-CoV-2 Humans Machine Learning
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Performance of Force-Field- and Machine Learning-Based Scoring Functions in Ranking MAO-B Protein-Inhibitor Complexes in Relevance to Developing Parkinson's Therapeutics.

International journal of molecular sciences Oct 16, 2020
Monoamine oxidase B (MAOB) is expressed in the mitochondrial membrane and has a key role in degrading various neurologically active amines such as benzylamine, phenethylamine and dopamine with the help of Flavin adenine dinucleotide (FAD) cofactor. T...
Humans Machine Learning Monoamine Oxidase Antiparkinson Agents Monoamine Oxidase Inhibitors Molecular Docking Simulation Protein Binding Drug Development
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Guiding Conventional Protein-Ligand Docking Software with Convolutional Neural Networks.

Journal of chemical information and modeling Oct 14, 2020
The high-performance computational techniques have brought significant benefits for drug discovery efforts in recent decades. One of the most challenging problems in drug discovery is the protein-ligand binding pose prediction. To predict the most st...
Neural Networks, Computer Proteins Ligands Software Molecular Docking Simulation Protein Binding
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Predictive Modeling of Angiotensin I-Converting Enzyme Inhibitory Peptides Using Various Machine Learning Approaches.

Journal of agricultural and food chemistry Oct 1, 2020
Food-derived angiotensin I-converting enzyme (ACE) inhibitory peptides could potentially be used as safe supportive therapeutic products for high blood pressure. Theoretical approaches are promising methods with the advantage through exploring the re...
Machine Learning Peptides Hydrogen Bonding Models, Molecular Peptidyl-Dipeptidase A Angiotensin-Converting Enzyme Inhibitors Molecular Docking Simulation
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Discovery of Dual FGFR4 and EGFR Inhibitors by Machine Learning and Biological Evaluation.

Journal of chemical information and modeling Sep 23, 2020
Kinase inhibitors are widely used in antitumor research, but there are still many problems such as drug resistance and off-target toxicity. A more suitable solution is to design a multitarget inhibitor with certain selectivity. Herein, computational ...
Quantitative Structure-Activity Relationship ErbB Receptors Machine Learning Molecular Docking Simulation Support Vector Machine
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Emulating Docking Results Using a Deep Neural Network: A New Perspective for Virtual Screening.

Journal of chemical information and modeling Sep 16, 2020
Docking is one of the most important steps in virtual screening pipelines, and it is an established method for examining potential interactions between ligands and receptors. However, this method is computationally expensive, and it is often among th...
Receptors, G-Protein-Coupled Ligands Retrospective Studies Molecular Docking Simulation Protein Binding Neural Networks, Computer Software
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Drug Design of Targeted Chemical Libraries Based on Artificial Intelligence and Pair-Based Multiobjective Optimization.

Journal of chemical information and modeling Sep 9, 2020
Artificial intelligence and multiobjective optimization represent promising solutions to bridge chemical and biological landscapes by addressing the automated design of compounds as a result of a humanlike creative process. In the present study, we ...
Coronavirus 3C Proteases Neural Networks, Computer Artificial Intelligence Pandemics COVID-19 SARS-CoV-2 Molecular Docking Simulation Cholinesterase Inhibitors Humans Enzyme Inhibitors Coronavirus Infections Viral Nonstructural Proteins Drug Design Neuraminidase Small Molecule Libraries Influenza A virus Betacoronavirus Acetylcholinesterase Antiviral Agents Pneumonia, Viral Cysteine Endopeptidases
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Bayesian machine learning to discover Bruton's tyrosine kinase inhibitors.

Chemical biology & drug design Aug 18, 2020
Bruton's tyrosine kinase (BTK) has a crucial role in multiple cell signaling pathways including B-cell antigen receptor (BCR) and Fc receptor (FcR) signaling cascades, which has attracted much attention to find BTK inhibitors to treat autoimmune dise...
Molecular Dynamics Simulation Protein Kinase Inhibitors Agammaglobulinaemia Tyrosine Kinase Reproducibility of Results Molecular Docking Simulation Humans Bayes Theorem Machine Learning
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Screening of Therapeutic Agents for COVID-19 Using Machine Learning and Ensemble Docking Studies.

The journal of physical chemistry letters Aug 14, 2020
The current pandemic demands a search for therapeutic agents against the novel coronavirus SARS-CoV-2. Here, we present an efficient computational strategy that combines machine learning (ML)-based models and high-fidelity ensemble docking studies to...
Drug Evaluation, Preclinical Molecular Docking Simulation Betacoronavirus Protein Conformation Antiviral Agents Hydrogen Bonding Humans Spike Glycoprotein, Coronavirus Machine Learning SARS-CoV-2
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