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Molecular Docking Simulation

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ET-score: Improving Protein-ligand Binding Affinity Prediction Based on Distance-weighted Interatomic Contact Features Using Extremely Randomized Trees Algorithm.

Molecular informatics May 21, 2021
The molecular docking simulation is a key computational tool in modern drug discovery research that its predictive performance strongly depends on the employed scoring functions. Many recent studies have shown that the application of machine learning...
Protein Binding Proteins Ligands Machine Learning Molecular Docking Simulation
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Treasuring the computational approach in medicinal plant research.

Progress in biophysics and molecular biology May 15, 2021
Medicinal plants serve as a valuable source of secondary metabolites since time immemorial. Computational Research in 21st century is giving more attention to medicinal plants for new drug design as pharmacological screening of bioactive compound was...
Artificial Intelligence Software Molecular Docking Simulation Molecular Dynamics Simulation Plants, Medicinal
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DeepBSP-a Machine Learning Method for Accurate Prediction of Protein-Ligand Docking Structures.

Journal of chemical information and modeling May 12, 2021
In recent years, machine-learning-based scoring functions have significantly improved the scoring power. However, many of these methods do not perform well in distinguishing the native structure from docked decoy poses due to the lack of decoy struct...
Ligands Molecular Docking Simulation Protein Binding Proteins Machine Learning
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An Integrated Approach toward NanoBRET Tracers for Analysis of GPCR Ligand Engagement.

Molecules (Basel, Switzerland) May 12, 2021
Gaining insight into the pharmacology of ligand engagement with G-protein coupled receptors (GPCRs) under biologically relevant conditions is vital to both drug discovery and basic research. NanoLuc-based bioluminescence resonance energy transfer (Na...
Protein Binding Receptors, G-Protein-Coupled Luciferases Molecular Docking Simulation Drug Discovery Luminescent Agents Binding, Competitive Bioluminescence Resonance Energy Transfer Techniques Transfection Ligands HEK293 Cells Humans Machine Learning
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Integrated support vector machine and pharmacophore based virtual screening driven identification of thiophene carboxamide scaffold containing compound as potential PARP1 inhibitor.

Journal of biomolecular structure & dynamics May 5, 2021
Poly (ADP-ribose) polymerase-1 (PARP1) inhibition strategy for cancer treatment is gaining advantage particularly in patients having a mutation in BRCA1/BRCA2 gene. To date, four drugs have obtained FDA approval and some inhibitors are in clinical tr...
Humans Molecular Docking Simulation Thiophenes Quantitative Structure-Activity Relationship Poly (ADP-Ribose) Polymerase-1 Support Vector Machine Molecular Dynamics Simulation Ligands
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Deep-learning based repurposing of FDA-approved drugs against dihydrofolate reductase and molecular dynamics study.

Journal of biomolecular structure & dynamics Apr 21, 2021
causes the fatal fungal bloodstream infection in humans called Candidiasis. Most of the species are resistant to the antifungals used to treat them. Drug-resistant poses very serious public health issues. To overcome this, the development of effec...
Drug Repositioning Aminopyridines Candidiasis Tetrahydrofolate Dehydrogenase Antifungal Agents Benzodioxoles Candida albicans Rifampin Cyclopropanes Folic Acid Antagonists Humans Molecular Dynamics Simulation Proline Molecular Docking Simulation Sulfonamides Lactams, Macrocyclic Deep Learning United States Food and Drug Administration Drug Approval United States
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Application of deep learning and molecular modeling to identify small drug-like compounds as potential HIV-1 entry inhibitors.

Journal of biomolecular structure & dynamics Apr 15, 2021
A generative adversarial autoencoder for the rational design of potential HIV-1 entry inhibitors able to block CD4-binding site of the viral envelope protein gp120 was developed. To do this, the following studies were carried out: (i) an autoencoder ...
Molecular Docking Simulation Deep Learning Anti-HIV Agents Molecular Dynamics Simulation HIV-1 HIV Envelope Protein gp120
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Performance improvement for a 2D convolutional neural network by using SSC encoding on protein-protein interaction tasks.

BMC bioinformatics Apr 12, 2021
BACKGROUND: The interactions of proteins are determined by their sequences and affect the regulation of the cell cycle, signal transduction and metabolism, which is of extraordinary significance to modern proteomics research. Despite advances in expe...
Computational Biology Amino Acid Sequence Neural Networks, Computer Software Molecular Docking Simulation
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Development of a graph convolutional neural network model for efficient prediction of protein-ligand binding affinities.

PloS one Apr 8, 2021
Prediction of protein-ligand interactions is a critical step during the initial phase of drug discovery. We propose a novel deep-learning-based prediction model based on a graph convolutional neural network, named GraphBAR, for protein-ligand binding...
Proteins Drug Discovery Neural Networks, Computer Ligands Deep Learning Molecular Docking Simulation Protein Binding
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Identification of novel inhibitors of Keap1/Nrf2 by a promising method combining protein-protein interaction-oriented library and machine learning.

Scientific reports Apr 1, 2021
Protein-protein interactions (PPIs) are prospective but challenging targets for drug discovery, because screening using traditional small-molecule libraries often fails to identify hits. Recently, we developed a PPI-oriented library comprising 12,593...
Binding Sites Small Molecule Libraries Protein Interaction Mapping Kelch-Like ECH-Associated Protein 1 Ligands Molecular Conformation NF-E2-Related Factor 2 Molecular Structure Molecular Dynamics Simulation Machine Learning Molecular Docking Simulation Humans Drug Discovery Protein Interaction Maps Protein Binding Structure-Activity Relationship
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