Molecular Dynamics Simulation

Machine learning discovery of novel antihypertensive peptides from highland barley protein inhibiting angiotensin I-converting enzyme (ACE).

Food research international (Ottawa, Ont.) 39967093

Hypertension is a major global health concern, and there is a need for new antihypertensive agents derived from natural sources. This study aims to identify novel angiotensin I-converting enzyme (ACE) inhibitors from bioactive peptides derived from f...

Angiotensin-Converting Enzyme Inhibitors Antihypertensive Agents Hordeum Humans Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Peptides Peptidyl-Dipeptidase A Plant Proteins

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Targeting Bacterial RNA Polymerase: Harnessing Simulations and Machine Learning to Design Inhibitors for Drug-Resistant Pathogens.

Biochemistry 40014017

The increase in antimicrobial resistance presents a major challenge in treating bacterial infections, underscoring the need for innovative drug discovery approaches and novel inhibitors. Bacterial RNA polymerase (RNAP) has emerged as a crucial target...

Anti-Bacterial Agents Bacteria Bacterial Proteins DNA-Directed RNA Polymerases Drug Design Drug Resistance, Bacterial Enzyme Inhibitors Humans Machine Learning Molecular Dynamics Simulation

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Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning.

Journal of chemical information and modeling 39984300

Proteins are inherently dynamic, and their conformational ensembles play a crucial role in biological function. Large-scale motions may govern the protein structure-function relationship, and numerous transient but stable conformations of intrinsical...

Amyloid beta-Peptides Deep Learning Intrinsically Disordered Proteins Molecular Dynamics Simulation Peptide Fragments Protein Conformation

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Deep learning-driven semi-rational design in phenylalanine ammonia-lyase for enhanced catalytic efficiency.

International journal of biological macromolecules 39984092

Phenylalanine ammonia-lyase (PAL) possesses significant potential in agriculture, industry, and the treatment of various diseases, including cancer. In particular, PAL derived from Anabaena variabilis (AvPAL) has been successfully utilized in clinica...

Anabaena variabilis Biocatalysis Catalysis Deep Learning Kinetics Molecular Dynamics Simulation Mutation Phenylalanine Ammonia-Lyase Protein Engineering

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A semiempirical and machine learning approach for fragment-based structural analysis of non-hydroxamate HDAC3 inhibitors.

Biophysical chemistry 39978120

Interest in HDAC3 inhibitors (HDAC3i) for pharmacological applications outside of cancer is growing. However, concerns regarding the possible mutagenicity of the commonly used hydroxamates (zinc-binding groups, ZBGs) are also increasing. Considering ...

Histone Deacetylase Inhibitors Histone Deacetylases Humans Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Molecular Structure Quantitative Structure-Activity Relationship Quantum Theory Thermodynamics

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Accelerated Missense Mutation Identification in Intrinsically Disordered Proteins Using Deep Learning.

Biomacromolecules 40072940

We use a combination of Brownian dynamics (BD) simulation results and deep learning (DL) strategies for the rapid identification of large structural changes caused by missense mutations in intrinsically disordered proteins (IDPs). We used ∼6500 IDP s...

Algorithms Deep Learning Humans Intrinsically Disordered Proteins Molecular Dynamics Simulation Mutation, Missense Neural Networks, Computer

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Insights into phosphorylation-induced influences on conformations and inhibitor binding of CDK6 through GaMD trajectory-based deep learning.

Physical chemistry chemical physics : PCCP 40072875

The phosphorylation of residue T177 produces a significant effect on the conformational dynamics of CDK6. Gaussian accelerated molecular dynamics (GaMD) simulations followed by deep learning (DL) are applied to explore the molecular mechanism of the ...

Cyclin-Dependent Kinase 6 Deep Learning Humans Molecular Dynamics Simulation Phosphorylation Protein Binding Protein Conformation Protein Kinase Inhibitors Thermodynamics

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Learning transition path and membrane topological signatures in the folding pathway of bacteriorhodopsin (BR) fragment with artificial intelligence.

The Journal of chemical physics 40067008

Membrane protein folding in the viscous microenvironment of a lipid bilayer is an inherently slow process that challenges experiments and computational efforts alike. The folding kinetics is moreover associated with topological modulations of the bio...

Algorithms Artificial Intelligence Bacteriorhodopsins Lipid Bilayers Molecular Dynamics Simulation Protein Folding Thermodynamics

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Identification of Novel Fourth-Generation Allosteric Inhibitors Targeting Inactive State of EGFR T790M/L858R/C797S and T790M/L858R Mutations: A Combined Machine Learning and Molecular Dynamics Approach.

The journal of physical chemistry. B 40053865

Targeted therapy with an allosteric inhibitor (AIs) is an important area of research in patients with epidermal growth factor receptor (EGFR) mutations. Current treatment of nonsmall cell lung cancer patients with EGFR mutations using orthosteric inh...

Allosteric Regulation ErbB Receptors Humans Machine Learning Molecular Dynamics Simulation Mutation Protein Kinase Inhibitors Quantitative Structure-Activity Relationship

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Geometry-encoded molecular dynamics enables deep learning insights into P450 regiospecificity control.

Scientific reports 40032954

Cytochrome P450 1A2, as many isoenzymes, can generate multiple metabolites from a single substrate. A loose coupling between substrate binding and oxygen activation makes possible substrate reorientations at the active site prior to catalysis. In the...

Caffeine Catalytic Domain Cytochrome P-450 CYP1A2 Deep Learning Humans Molecular Dynamics Simulation Oxidation-Reduction Oxygen Substrate Specificity

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AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Machine learning discovery of novel antihypertensive peptides from highland barley protein inhibiting angiotensin I-converting enzyme (ACE).

Targeting Bacterial RNA Polymerase: Harnessing Simulations and Machine Learning to Design Inhibitors for Drug-Resistant Pathogens.

Sampling Conformational Ensembles of Highly Dynamic Proteins via Generative Deep Learning.

Deep learning-driven semi-rational design in phenylalanine ammonia-lyase for enhanced catalytic efficiency.

A semiempirical and machine learning approach for fragment-based structural analysis of non-hydroxamate HDAC3 inhibitors.

Accelerated Missense Mutation Identification in Intrinsically Disordered Proteins Using Deep Learning.

Insights into phosphorylation-induced influences on conformations and inhibitor binding of CDK6 through GaMD trajectory-based deep learning.

Learning transition path and membrane topological signatures in the folding pathway of bacteriorhodopsin (BR) fragment with artificial intelligence.

Identification of Novel Fourth-Generation Allosteric Inhibitors Targeting Inactive State of EGFR T790M/L858R/C797S and T790M/L858R Mutations: A Combined Machine Learning and Molecular Dynamics Approach.

Geometry-encoded molecular dynamics enables deep learning insights into P450 regiospecificity control.

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