AIMC Topic: Molecular Docking Simulation

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Learning from Docked Ligands: Ligand-Based Features Rescue Structure-Based Scoring Functions When Trained on Docked Poses.

Journal of chemical information and modeling Sep 1, 2021
Machine learning scoring functions for protein-ligand binding affinity have been found to consistently outperform classical scoring functions when trained and tested on crystal structures of bound protein-ligand complexes. However, it is less clear h...
Molecular Docking Simulation Protein Binding Proteins Ligands Machine Learning
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Machine Learning-Enabled Pipeline for Large-Scale Virtual Drug Screening.

Journal of chemical information and modeling Aug 17, 2021
Virtual screening is receiving renewed attention in drug discovery, but progress is hampered by challenges on two fronts: handling the ever-increasing sizes of libraries of drug-like compounds and separating true positives from false positives. Here,...
Neural Networks, Computer Machine Learning Molecular Docking Simulation Drug Discovery Drug Evaluation, Preclinical
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MCN-CPI: Multiscale Convolutional Network for Compound-Protein Interaction Prediction.

Biomolecules Jul 29, 2021
In the process of drug discovery, identifying the interaction between the protein and the novel compound plays an important role. With the development of technology, deep learning methods have shown excellent performance in various situations. Howeve...
Protein Interaction Domains and Motifs Protein Conformation, alpha-Helical Protein Conformation, beta-Strand Drugs, Investigational High-Throughput Screening Assays Datasets as Topic Binding Sites Deep Learning Protein Binding Proteins Humans Kinetics Molecular Docking Simulation Drug Discovery
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Support Vector Machine as a Supervised Learning for the Prioritization of Novel Potential SARS-CoV-2 Main Protease Inhibitors.

International journal of molecular sciences Jul 19, 2021
In the last year, the COVID-19 pandemic has highly affected the lifestyle of the world population, encouraging the scientific community towards a great effort on studying the infection molecular mechanisms. Several vaccine formulations are nowadays a...
Humans Pandemics COVID-19 Antiviral Agents Support Vector Machine SARS-CoV-2 Molecular Docking Simulation Coronavirus Protease Inhibitors Viral Proteases Molecular Dynamics Simulation Small Molecule Libraries COVID-19 Drug Treatment Drug Evaluation, Preclinical Databases, Pharmaceutical Supervised Machine Learning Viral Nonstructural Proteins
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Identification of kinase inhibitors that rule out the CYP27B1-mediated activation of vitamin D: an integrated machine learning and structure-based drug designing approach.

Molecular diversity Jul 16, 2021
CYP27B1, a cytochrome P450-containing hydroxylase enzyme, converts vitamin D precursor calcidiol (25-hydroxycholecalciferol) to its active form calcitriol (1α,25(OH)D). Tyrosine kinase inhibitor such as imatinib is reported to interfere with the acti...
Small Molecule Libraries Databases, Pharmaceutical Phosphotransferases Humans Protein Binding Algorithms Support Vector Machine Animals Reproducibility of Results Vitamin D Molecular Docking Simulation Neural Networks, Computer 25-Hydroxyvitamin D3 1-alpha-Hydroxylase Drug Design Machine Learning Structure-Activity Relationship Enzyme Inhibitors Metabolic Networks and Pathways Binding Sites Models, Molecular Molecular Dynamics Simulation Amino Acid Sequence
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Structure-Based Molecular Generator Combined with Artificial Intelligence and Docking Simulations.

Journal of chemical information and modeling Jul 9, 2021
Recently, molecular generation models based on deep learning have attracted significant attention in drug discovery. However, most existing molecular generation models have serious limitations in the context of drug design wherein they do not suffici...
Neural Networks, Computer Artificial Intelligence Molecular Docking Simulation Drug Design Drug Discovery Proteins
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Machine learning approach to discovery of small molecules with potential inhibitory action against vasoactive metalloproteases.

Molecular diversity Jul 3, 2021
With the advancement of combinatorial chemistry and big data, drug repositioning has boomed. In this sense, machine learning and artificial intelligence techniques offer a priori information to identify the most promising candidates. In this study, w...
Machine Learning Molecular Docking Simulation Humans Artificial Intelligence Drug Repositioning Bayes Theorem Quantitative Structure-Activity Relationship Metalloproteases
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Synthesis, docking, machine learning and antiproliferative activity of the 6-ferrocene/heterocycle-2-aminopyrimidine and 5-ferrocene-1H-Pyrazole derivatives obtained by microwave-assisted Atwal reaction as potential anticancer agents.

Bioorganic & medicinal chemistry letters Jul 2, 2021
A simple and fast methodology under microwave irradiation for the synthesis of 2-aminopyrimidine and pyrazole derivatives using Atwal reaction is reported. After the optimization of the reaction conditions, eight 2-aminolpyrimidines containing ferroc...
Machine Learning Molecular Docking Simulation Antineoplastic Agents Cell Line, Tumor Humans Pyrazoles Pyrimidines Metallocenes Structure-Activity Relationship Molecular Structure Ferrous Compounds Microwaves Cell Proliferation Dose-Response Relationship, Drug Drug Screening Assays, Antitumor
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Molecular insights on ABL kinase activation using tree-based machine learning models and molecular docking.

Molecular diversity Jun 30, 2021
Abelson kinase (c-Abl) is a non-receptor tyrosine kinase involved in several biological processes essential for cell differentiation, migration, proliferation, and survival. This enzyme's activation might be an alternative strategy for treating disea...
Quantitative Structure-Activity Relationship Protein Kinase Inhibitors Binding Sites Proto-Oncogene Proteins c-abl Molecular Structure Humans Molecular Dynamics Simulation Ligands Drug Design Protein Binding Machine Learning Molecular Docking Simulation
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Predicting aptamer sequences that interact with target proteins using an aptamer-protein interaction classifier and a Monte Carlo tree search approach.

PloS one Jun 25, 2021
Oligonucleotide-based aptamers, which have a three-dimensional structure with a single-stranded fragment, feature various characteristics with respect to size, toxicity, and permeability. Accordingly, aptamers are advantageous in terms of diagnosis a...
Models, Chemical Monte Carlo Method Aptamers, Nucleotide Sequence Analysis, RNA Proteins Machine Learning Computer Simulation Molecular Docking Simulation
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