AIMC Topic: Hydrogen Bonding

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Machine learning and classical MD simulation to identify inhibitors against the P37 envelope protein of monkeypox virus.

Journal of biomolecular structure & dynamics May 23, 2023
Monkeypox virus (MPXV) outbreak is a serious public health concern that requires international attention. P37 of MPXV plays a pivotal role in DNA replication and acts as one of the promising targets for antiviral drug design. In this study, we intent...
Machine Learning Molecular Docking Simulation Antiviral Agents Hydrogen Bonding Binding Sites Viral Envelope Proteins Protein Binding Monkeypox virus Molecular Dynamics Simulation Hydrophobic and Hydrophilic Interactions
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Efficient enumeration-selection computational strategy for adaptive chemistry.

Scientific reports Aug 29, 2022
Design problems of finding efficient patterns, adaptation of complex molecules to external environments, affinity of molecules to specific targets, dynamic adaptive behavior of chemical systems, reconstruction of 3D structures from diffraction data a...
Polymers Hydrogen Bonding Physics Machine Learning
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Effective prediction of short hydrogen bonds in proteins via machine learning method.

Scientific reports Jan 10, 2022
Short hydrogen bonds (SHBs), whose donor and acceptor heteroatoms lie within 2.7 Å, exhibit prominent quantum mechanical characters and are connected to a wide range of essential biomolecular processes. However, exact determination of the geometry an...
Proteins Databases, Protein Machine Learning Models, Molecular Amino Acid Sequence Peptides Hydrogen Bonding
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Combining machine learning and quantum mechanics yields more chemically aware molecular descriptors for medicinal chemistry applications.

Journal of computational chemistry Aug 19, 2021
Molecular interaction fields (MIFs), describing molecules in terms of their ability to interact with any chemical entity, are one of the most established and versatile concepts in drug discovery. Improvement of this molecular description is highly de...
Density Functional Theory Molecular Structure Hydrogen Bonding Machine Learning Organic Chemicals
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Protein structure prediction using deep learning distance and hydrogen-bonding restraints in CASP14.

Proteins Aug 7, 2021
In this article, we report 3D structure prediction results by two of our best server groups ("Zhang-Server" and "QUARK") in CASP14. These two servers were built based on the D-I-TASSER and D-QUARK algorithms, which integrated four newly developed com...
Proteins Models, Molecular Protein Conformation Software Deep Learning Computational Biology Sequence Analysis, Protein Hydrogen Bonding Protein Folding Sequence Alignment
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A novel artificial intelligence protocol to investigate potential leads for diabetes mellitus.

Molecular diversity Mar 9, 2021
Dipeptidyl peptidase-4 (DPP4) is highly participated in regulating diabetes mellitus (DM), and inhibitors of DPP4 may act as potential DM drugs. Therefore, we performed a novel artificial intelligence (AI) protocol to screen and validate the potentia...
Humans Neural Networks, Computer Artificial Intelligence Machine Learning Algorithms Molecular Docking Simulation Molecular Dynamics Simulation Hypoglycemic Agents Quantitative Structure-Activity Relationship Drug Design Binding Sites Molecular Structure Hydrogen Bonding Drug Discovery Dipeptidyl-Peptidase IV Inhibitors Protein Binding Workflow
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Recapitulating the Binding Affinity of Nrf2 for KEAP1 in a Cyclic Heptapeptide, Guided by NMR, X-ray Crystallography, and Machine Learning.

Journal of the American Chemical Society Mar 8, 2021
Macrocycles, including macrocyclic peptides, have shown promise for targeting challenging protein-protein interactions (PPIs). One PPI of high interest is between Kelch-like ECH-Associated Protein-1 (KEAP1) and Nuclear Factor (Erythroid-derived 2)-li...
Kelch-Like ECH-Associated Protein 1 Fluorescence Polarization Nuclear Magnetic Resonance, Biomolecular NF-E2-Related Factor 2 Mutagenesis, Site-Directed Amino Acid Motifs Cyclization Structure-Activity Relationship Crystallography, X-Ray Hydrogen Bonding Peptides Humans Protein Binding Machine Learning Recombinant Proteins
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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...
Angiotensin-Converting Enzyme Inhibitors Hydrogen Bonding Peptidyl-Dipeptidase A Peptides Molecular Docking Simulation Models, Molecular 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...
SARS-CoV-2 Molecular Docking Simulation Humans Hydrogen Bonding Machine Learning Antiviral Agents Spike Glycoprotein, Coronavirus Betacoronavirus Drug Evaluation, Preclinical Protein Conformation
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Characterizing Protein-Ligand Binding Using Atomistic Simulation and Machine Learning: Application to Drug Resistance in HIV-1 Protease.

Journal of chemical theory and computation Jan 16, 2020
Over the past several decades, atomistic simulations of biomolecules, whether carried out using molecular dynamics or Monte Carlo techniques, have provided detailed insights into their function. Comparing the results of such simulations for a few clo...
Monte Carlo Method Ligands Drug Resistance, Viral HIV Protease HIV Protease Inhibitors Mutation Humans Hydrogen Bonding Molecular Dynamics Simulation Machine Learning Static Electricity HIV-1 Protein Binding
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