AIMC Topic: Molecular Dynamics Simulation

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Repurposing FDA-approved drugs as NLRP3 inhibitors against inflammatory diseases: machine learning and molecular simulation approaches.

Journal of biomolecular structure & dynamics May 1, 2025
Activation of NLRP3 (NOD-like receptor family, pyrin domain-containing protein 3) has been associated with multiple chronic pathologies, including diabetes, atherosclerosis, and rheumatoid arthritis. Moreover, histone deacetylases (HDACs), specifical...
Molecular Dynamics Simulation Inflammasomes United States Food and Drug Administration Drug Approval United States Molecular Docking Simulation Drug Repositioning NLR Family, Pyrin Domain-Containing 3 Protein Protein Binding Inflammation Humans Machine Learning
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Bioactivity predictions and virtual screening using machine learning predictive model.

Journal of biomolecular structure & dynamics May 1, 2025
Recently, there has been significant attention on machine learning algorithms for predictive modeling. Prediction models for enzyme inhibitors are limited, and it is essential to account for chemical biases while developing them. The lack of repeatab...
Algorithms Molecular Dynamics Simulation Dipeptidyl-Peptidase IV Inhibitors Molecular Docking Simulation Drug Discovery Humans Drug Evaluation, Preclinical Dipeptidyl Peptidase 4 Machine Learning
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Discovery of hematopoietic progenitor kinase 1 inhibitors using machine learning-based screening and free energy perturbation.

Journal of biomolecular structure & dynamics May 1, 2025
Hematopoietic progenitor kinase 1 (HPK1) is a key negative regulator of T-cell receptor (TCR) signaling and a promising target for cancer immunotherapy. The development of novel HPK1 inhibitors is challenging yet promising. In this study, we used a c...
Protein Binding Signal Transduction Thermodynamics Protein Serine-Threonine Kinases Structure-Activity Relationship Humans T-Lymphocytes Molecular Dynamics Simulation Molecular Docking Simulation Machine Learning Protein Kinase Inhibitors Drug Discovery
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Study on the mechanism of action of the active ingredient of Calculus Bovis in the treatment of sepsis by integrating single-cell sequencing and machine learning.

Medicine Apr 18, 2025
BACKGROUND: Sepsis, a complex inflammatory condition with high mortality rates, lacks effective treatments. This study explores the therapeutic mechanisms of Calculus Bovis in sepsis using network pharmacology and RNA sequencing.
Molecular Docking Simulation China Sepsis Humans Machine Learning Drugs, Chinese Herbal Molecular Dynamics Simulation Network Pharmacology Single-Cell Analysis Protein Interaction Maps Sequence Analysis, RNA
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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 Mar 14, 2025
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...
Bacteriorhodopsins Artificial Intelligence Algorithms Molecular Dynamics Simulation Lipid Bilayers Thermodynamics Protein Folding
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Machine Learning-Based Discovery of a Novel Noncovalent MurA Inhibitor as an Antibacterial Agent.

Chemical biology & drug design Mar 1, 2025
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...
Machine Learning Anti-Bacterial Agents Molecular Docking Simulation Humans Drug Discovery Enzyme Inhibitors Microbial Sensitivity Tests Molecular Dynamics Simulation Transferases Alkyl and Aryl Transferases
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Leveraging Artificial Intelligence in GPCR Activation Studies: Computational Prediction Methods as Key Drivers of Knowledge.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2025
G protein-coupled receptors (GPCRs) are key molecules involved in cellular signaling and are attractive targets for pharmacological intervention. This chapter is designed to explore the range of algorithms used to predict GPCRs' activation states, wh...
Signal Transduction Databases, Protein Receptors, G-Protein-Coupled Artificial Intelligence Algorithms Computational Biology Molecular Dynamics Simulation Ligands Humans
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Grand canonical Monte Carlo and deep learning assisted enhanced sampling to characterize the distribution of Mg2+ and influence of the Drude polarizable force field on the stability of folded states of the twister ribozyme.

The Journal of chemical physics Dec 14, 2024
Molecular dynamics simulations are crucial for understanding the structural and dynamical behavior of biomolecular systems, including the impact of their environment. However, there is a gap between the time scale of these simulations and that of rea...
Magnesium Molecular Dynamics Simulation Nucleic Acid Conformation Monte Carlo Method Deep Learning RNA, Catalytic
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An Integrated Approach to Develop a Potent Vaccine Candidate Construct Against Prostate Cancer by Utilizing Machine Learning and Bioinformatics.

Cancer reports (Hoboken, N.J.) Dec 1, 2024
BACKGROUND: Prostate cancer is the most common malignancy among males. Prostaglandin G/H synthase (PGHS) is an essential enzyme in the synthesis of prostaglandins, and its activation has been linked to many malignancies, including colorectal cancer.
Vaccine Development Prostatic Neoplasms Molecular Dynamics Simulation Epitopes, B-Lymphocyte Vaccines, Subunit Molecular Docking Simulation Computational Biology Cancer Vaccines Machine Learning Humans Male Epitopes, T-Lymphocyte
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Machine learning-enabled virtual screening indicates the anti-tuberculosis activity of aldoxorubicin and quarfloxin with verification by molecular docking, molecular dynamics simulations, and biological evaluations.

Briefings in bioinformatics Nov 22, 2024
Drug resistance in Mycobacterium tuberculosis (Mtb) is a significant challenge in the control and treatment of tuberculosis, making efforts to combat the spread of this global health burden more difficult. To accelerate anti-tuberculosis drug discove...
Humans Machine Learning Molecular Dynamics Simulation Molecular Docking Simulation Mycobacterium tuberculosis Microbial Sensitivity Tests Antitubercular Agents
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