AIMC Topic: Molecular Dynamics Simulation

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Rational design of potent phosphopeptide binders to endocrine Snk PBD domain by integrating machine learning optimization, molecular dynamics simulation, binding energetics rescoring, and in vitro affinity assay.

European biophysics journal : EBJ Nov 29, 2024
Human Snk is an evolutionarily conserved serine/threonine kinase essential for the maintenance of endocrine stability. The protein consists of a N-terminal catalytic domain and a C-terminal polo-box domain (PBD) that determines subcellular localizati...
Protein Binding Humans Protein Serine-Threonine Kinases Machine Learning Drug Design Amino Acid Sequence Thermodynamics Phosphopeptides Protein Domains Molecular Dynamics Simulation
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Machine Learning Models for Predicting Monoclonal Antibody Biophysical Properties from Molecular Dynamics Simulations and Deep Learning-Based Surface Descriptors.

Molecular pharmaceutics Nov 28, 2024
Monoclonal antibodies (mAbs) have found extensive applications and development in treating various diseases. From the pharmaceutical industry's perspective, the journey from the design and development of mAbs to clinical testing and large-scale produ...
Molecular Dynamics Simulation Solubility Viscosity Deep Learning Antibodies, Monoclonal Humans Machine Learning
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Augmenting Human Expertise in Weighted Ensemble Simulations through Deep Learning-Based Information Bottleneck.

Journal of chemical theory and computation Nov 26, 2024
The weighted ensemble (WE) method stands out as a widely used segment-based sampling technique renowned for its rigorous treatment of kinetics. The WE framework typically involves initially mapping the configuration space onto a low-dimensional colle...
Humans Oligopeptides Deep Learning Molecular Dynamics Simulation Dipeptides
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ConfRank: Improving GFN-FF Conformer Ranking with Pairwise Training.

Journal of chemical information and modeling Nov 20, 2024
Conformer ranking is a crucial task for drug discovery, with methods for generating conformers often based on molecular (meta)dynamics or sophisticated sampling techniques. These methods are constrained by the underlying force computation regarding r...
Machine Learning Drug Discovery Molecular Conformation Molecular Dynamics Simulation
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Deciphering Cas9 specificity: Role of domain dynamics and RNA:DNA hybrid interactions revealed through machine learning and accelerated molecular simulations.

International journal of biological macromolecules Nov 19, 2024
CRISPR/Cas9 technology is widely used for gene editing, but off-targeting still remains a major concern in therapeutic applications. Although Cas9 variants with better mismatch discrimination have been developed, they have significantly lower rates o...
CRISPR-Associated Protein 9 Francisella RNA Substrate Specificity DNA Machine Learning CRISPR-Cas Systems Protein Domains Bacterial Proteins Molecular Dynamics Simulation
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Emerging Frontiers in Conformational Exploration of Disordered Proteins: Integrating Autoencoder and Molecular Simulations.

ACS chemical neuroscience Nov 18, 2024
Intrinsically disordered proteins (IDPs) are closely associated with a number of neurodegenerative diseases, such as Alzheimer's disease and Parkinson's disease. Due to the highly dynamic nature of IDPs, their structural determination and conformatio...
Protein Conformation Molecular Dynamics Simulation Humans Intrinsically Disordered Proteins Machine Learning
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Estimating AChE inhibitors from MCE database by machine learning and atomistic calculations.

Journal of molecular graphics & modelling Nov 14, 2024
Acetylcholinesterase (AChE) is one of the most successful targets for the treatment of Alzheimer's disease (AD). Inhibition of AChE can result in preventing AD. In this context, the machine-learning (ML) model, molecular docking, and molecular dynami...
Protein Binding Molecular Dynamics Simulation Machine Learning Molecular Docking Simulation Cholinesterase Inhibitors Databases, Chemical Binding Sites Ligands Acetylcholinesterase Humans
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Investigating Ligand-Mediated Conformational Dynamics of Pre-miR21: A Machine-Learning-Aided Enhanced Sampling Study.

Journal of chemical information and modeling Nov 11, 2024
MicroRNAs (miRs) are short, noncoding RNA strands that regulate the activity of mRNAs by affecting the repression of protein translation, and their dysregulation has been implicated in several pathologies. miR21 in particular has been implicated in t...
Nucleic Acid Conformation RNA Precursors Ribonuclease III Ligands Peptides, Cyclic Humans MicroRNAs Machine Learning Molecular Dynamics Simulation
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AMARO: All Heavy-Atom Transferable Neural Network Potentials of Protein Thermodynamics.

Journal of chemical theory and computation Nov 8, 2024
All-atom molecular simulations offer detailed insights into macromolecular phenomena, but their substantial computational cost hinders the exploration of complex biological processes. We introduce Advanced Machine-learning Atomic Representation Omni-...
Proteins Neural Networks, Computer Molecular Dynamics Simulation Machine Learning Thermodynamics
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Molecular mechanism underlying effect of D93 and D289 protonation states on inhibitor-BACE1 binding: exploration from multiple independent Gaussian accelerated molecular dynamics and deep learning.

SAR and QSAR in environmental research Nov 8, 2024
BACE1 has been regarded as an essential drug design target for treating Alzheimer's disease (AD). Multiple independent Gaussian accelerated molecular dynamics simulations (GaMD), deep learning (DL), and molecular mechanics general Born surface area (...
Molecular Dynamics Simulation Aspartic Acid Endopeptidases Drug Design Hydrogen Bonding Protons Deep Learning Quantitative Structure-Activity Relationship Amyloid Precursor Protein Secretases
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