AIMC Topic: Molecular Dynamics Simulation

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Predicting Saturation Concentrations of Phase-Separating Proteins via Thermodynamic Integration.

Journal of chemical theory and computation Sep 19, 2025
Phase separation of proteins and nucleic acids into biomolecular condensates contributes to the regulation of cellular compartmentalization in membrane-less environments. A key parameter controlling the onset of biomolecular condensate formation is t...
Molecular Dynamics Simulation Thermodynamics Biomolecular Condensates Humans Proteins
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Mechanism-Driven Features Enable Asn Deamidation Reactivity Prediction via Machine Learning Methods.

Journal of chemical information and modeling Sep 19, 2025
The spontaneous deamidation of Asparagine (Asn) residues is a common post-translational modification of proteins that can occur on disparate time scales, ranging from hours to thousands of years. This variability in the reaction rate reflects the inf...
Asparagine Hydrogen Bonding Thermodynamics Amides Molecular Dynamics Simulation Machine Learning
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Machine learning-assisted detection of single-point mutations DNA-templated gold nanoparticle growth.

Nanoscale Sep 18, 2025
Detecting single point mutations, such as PIK3CA mutations, is vital for precision diagnostics but remains challenging due to subtle sequence differences. This study introduces a machine learning-assisted colorimetric biosensor that utilizes DNA-temp...
Class I Phosphatidylinositol 3-Kinases Colorimetry DNA DNA Probes Metal Nanoparticles Point Mutation Gold Humans Biosensing Techniques Molecular Dynamics Simulation Machine Learning
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Leveraging Transformer Models to Capture Multi-Scale Dynamics in Biomolecules by Nano-GPT.

Journal of chemical theory and computation Sep 17, 2025
Long-term biomolecular dynamics is critical for understanding key evolutionary transformations in molecular systems. However, capturing these processes requires extended simulation timescales that often exceed the practical limits of conventional mod...
Deep Learning Molecular Dynamics Simulation Dipeptides Nanotechnology
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CGBack: Diffusion Model for Backmapping Large-Scale and Complex Coarse-Grained Molecular Systems.

Journal of chemical information and modeling Sep 17, 2025
Molecular dynamics simulations based on coarse-grained (CG) models are used to accelerate conformational dynamics of biomolecules and other chemical systems with reduced computational costs. CG models achieve this by discarding atomic information nec...
Diffusion Protein Conformation Proteins Molecular Dynamics Simulation
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Machine Learning Navigated Allosteric Network to Unveil Biased Allosteric Modulation of GPCRs.

Journal of chemical theory and computation Sep 16, 2025
Biased allosteric modulators (BAMs) offer a promising avenue for developing safer and more selective therapeutics for G protein-coupled receptors (GPCRs). However, their molecular mechanisms remain unclear due to the complex combination of biased and...
Humans Molecular Dynamics Simulation Ligands Allosteric Regulation Machine Learning Receptors, G-Protein-Coupled
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MOLECULE: Molecular-dynamics and Optimized deep Learning for Entropy-regularized Classification and Uncertainty-aware Ligand Evaluation.

Journal of chemical theory and computation Sep 11, 2025
Machine learning (ML) and deep learning (DL) methodologies have significantly advanced drug discovery and design in several aspects. Additionally, the integration of structure-based data has proven to successfully support and improve the models' pred...
Ligands Protein Kinase Inhibitors Uncertainty Entropy Deep Learning Molecular Dynamics Simulation Drug Discovery
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Development of Coarse-Grained Lipid Force Fields Based on a Graph Neural Network.

Journal of chemical theory and computation Sep 10, 2025
Coarse-grained (CG) lipid models enable efficient simulations of large-scale membrane events. However, achieving both speed and atomic-level accuracy remains challenging. Graph neural networks (GNNs) trained on all-atom (AA) simulations can serve as ...
Lipid Bilayers Graph Neural Networks Lipids Molecular Dynamics Simulation Neural Networks, Computer
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Integrated machine learning, molecular dynamics, and DFT-based approach to elucidate the inhibitory effect of Ciprofloxacin analogues against fluoroquinolone-resistant Salmonella Typhi.

Archives of microbiology Sep 8, 2025
Salmonella enterica serovar Typhi, the etiological agent of Typhoid fever, remains a critical public health concern associated with high morbidity in many developing countries. The widespread emergence of multidrug-resistant (MDR) Salmonella Typhi st...
DNA Gyrase Machine Learning Drug Resistance, Bacterial Molecular Docking Simulation Anti-Bacterial Agents Ciprofloxacin Density Functional Theory Salmonella typhi Molecular Dynamics Simulation Fluoroquinolones Microbial Sensitivity Tests Typhoid Fever Bacterial Proteins Drug Resistance, Multiple, Bacterial Mutation
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Curcumenol exerts anti-pulmonary fibrosis effects through modulation of the immune signature target SPP1: based on comprehensive bioinformatics and experiments validation.

International immunopharmacology Sep 7, 2025
BACKGROUND: The efficacy of Curcuma wenyujin (C. wenyujin) volatile oil components in the treatment of lung diseases, including pulmonary fibrosis (PF), is gradually being recognized. However, the anti-PF potential and underlying mechanisms of curcum...
Curcuma Osteopontin Sesquiterpenes Humans Pulmonary Fibrosis Animals Molecular Dynamics Simulation Molecular Docking Simulation Mice Gene Expression Profiling Computational Biology Transcriptome Databases, Genetic
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