Enzyme Inhibitors

Integrated machine learning and physics-based methods assisted de novo design of Fatty Acyl-CoA synthase inhibitors.

Expert opinion on drug discovery 39587794

BACKGROUND: Tuberculosis is an infectious disease that has become endemic worldwide. The causative bacteria (Mtb) is targeted via several exciting drug targets. One newly discovered target is the Fatty Acyl-CoA synthase, which plays a significant ro...

Algorithms Antitubercular Agents Coenzyme A Ligases Drug Design Enzyme Inhibitors Humans Lipid Metabolism Machine Learning Molecular Docking Simulation Mycobacterium tuberculosis Tuberculosis

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Study on SHP2 Conformational Transition and Structural Characterization of Its High-Potency Allosteric Inhibitors by Molecular Dynamics Simulations Combined with Machine Learning.

Molecules (Basel, Switzerland) 39795072

The src-homology 2 domain-containing phosphatase 2 (SHP2) is a human cytoplasmic protein tyrosine phosphatase that plays a crucial role in cellular signal transduction. Aberrant activation and mutations of SHP2 are associated with tumor growth and im...

Allosteric Regulation Enzyme Inhibitors Humans Machine Learning Molecular Dynamics Simulation Protein Binding Protein Conformation Protein Tyrosine Phosphatase, Non-Receptor Type 11

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Enhanced prediction of beta-secretase inhibitory compounds with mol2vec technique and machine learning algorithms.

SAR and QSAR in environmental research 39704060

A comprehensive computational strategy that combined QSAR modelling, molecular docking, and ADMET analysis was used to discover potential inhibitors for β-secretase 1 (BACE-1). A dataset of 1,138 compounds with established BACE-1 inhibitory activitie...

Algorithms Amyloid Precursor Protein Secretases Enzyme Inhibitors Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Quantitative Structure-Activity Relationship

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Integration of 3D-QSAR, molecular docking, and machine learning techniques for rational design of nicotinamide-based SIRT2 inhibitors.

Computational biology and chemistry 39405774

Selective inhibitors of sirtuin-2 (SIRT2) are increasingly recognized as potential therapeutics for cancer and neurodegenerative diseases. Derivatives of 5-((3-amidobenzyl)oxy)nicotinamides have been identified as some of the most potent and selectiv...

Drug Design Enzyme Inhibitors Humans Machine Learning Molecular Docking Simulation Molecular Structure Niacinamide Quantitative Structure-Activity Relationship Sirtuin 2

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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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Graph and Multi-Level Sequence Fusion Learning for Predicting the Molecular Activity of BACE-1 Inhibitors.

International journal of molecular sciences 40004143

The development of BACE-1 (β-site amyloid precursor protein cleaving enzyme 1) inhibitors is a crucial focus in exploring early treatments for Alzheimer's disease (AD). Recently, graph neural networks (GNNs) have demonstrated significant advantages i...

Alzheimer Disease Amyloid Precursor Protein Secretases Aspartic Acid Endopeptidases Enzyme Inhibitors Humans Machine Learning Neural Networks, Computer

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Mechanistic Study of Protein Interaction with Natto Inhibitory Peptides Targeting Xanthine Oxidase: Insights from Machine Learning and Molecular Dynamics Simulations.

Journal of chemical information and modeling 40125929

Bioactive peptides from food sources offer a safe and biocompatible approach to enzyme inhibition, with potential applications in managing metabolic disorders such as hyperuricemia and gout, conditions linked to excessive xanthine oxidase activity. U...

Bacillus subtilis Enzyme Inhibitors Humans Machine Learning Molecular Dynamics Simulation Peptides Protein Binding Xanthine Oxidase

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Machine Learning-Based Discovery of a Novel Noncovalent MurA Inhibitor as an Antibacterial Agent.

Chemical biology & drug design 40077992

The bacterial cell wall is crucial for maintaining the integrity of bacterial cells. UDP-N-acetylglucosamine 1-carboxyethylene transferase (MurA) is an important enzyme involved in bacterial cell wall synthesis. Therefore, it is an important target f...

Alkyl and Aryl Transferases Anti-Bacterial Agents Drug Discovery Enzyme Inhibitors Humans Machine Learning Microbial Sensitivity Tests Molecular Docking Simulation Molecular Dynamics Simulation Transferases

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Bioactive structures for inhibitors of polymerase enzyme by artificial intelligence.

Future medicinal chemistry 40247646

AIMS: Present new bioactive compounds, created by De novo Drug Design and artificial intelligence (AI), as possible inhibitors of polymerase.

Antifungal Agents Artificial Intelligence Candida Drug Design Enzyme Inhibitors Humans Molecular Docking Simulation Molecular Dynamics Simulation Molecular Structure

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Computational screening of natural products as tryptophan 2,3-dioxygenase inhibitors: Insights from CNN-based QSAR, molecular docking, ADMET, and molecular dynamics simulations.

Computers in biology and medicine 40233673

Parkinson's disease (PD) is characterised by a complex array of motor, psychiatric, and gastrointestinal symptoms, many of which are linked to disruptions in neuroactive metabolites. Dysregulated activity of tryptophan 2,3-dioxygenase (TDO), a key en...

Biological Products Enzyme Inhibitors Humans Machine Learning Molecular Docking Simulation Molecular Dynamics Simulation Neural Networks, Computer Parkinson Disease Quantitative Structure-Activity Relationship Tryptophan Oxygenase

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

Integrated machine learning and physics-based methods assisted de novo design of Fatty Acyl-CoA synthase inhibitors.

Study on SHP2 Conformational Transition and Structural Characterization of Its High-Potency Allosteric Inhibitors by Molecular Dynamics Simulations Combined with Machine Learning.

Enhanced prediction of beta-secretase inhibitory compounds with mol2vec technique and machine learning algorithms.

Integration of 3D-QSAR, molecular docking, and machine learning techniques for rational design of nicotinamide-based SIRT2 inhibitors.

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

Graph and Multi-Level Sequence Fusion Learning for Predicting the Molecular Activity of BACE-1 Inhibitors.

Mechanistic Study of Protein Interaction with Natto Inhibitory Peptides Targeting Xanthine Oxidase: Insights from Machine Learning and Molecular Dynamics Simulations.

Machine Learning-Based Discovery of a Novel Noncovalent MurA Inhibitor as an Antibacterial Agent.

Bioactive structures for inhibitors of polymerase enzyme by artificial intelligence.

Computational screening of natural products as tryptophan 2,3-dioxygenase inhibitors: Insights from CNN-based QSAR, molecular docking, ADMET, and molecular dynamics simulations.

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