AIMC Topic: Protein Conformation

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Enhanced Exploration of Protein Conformational Space through Integration of Ultra-Coarse-Grained Models to Multiscale Workflows.

The journal of physical chemistry. B May 22, 2025
Computational techniques such as all-atom (AA) molecular dynamics (MD) simulations and coarse-grained (CG) models have been essential to study various biological problems over a wide range of scales. While AA simulations provide detailed insights, th...
Machine Learning Protein Conformation Proteins Molecular Dynamics Simulation
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Accurate Predictions of Molecular Properties of Proteins via Graph Neural Networks and Transfer Learning.

Journal of chemical theory and computation May 13, 2025
Machine learning has emerged as a promising approach for predicting molecular properties of proteins, as it addresses limitations of experimental and traditional computational methods. Here, we introduce GSnet, a graph neural network (GNN) trained to...
Machine Learning Proteins Protein Conformation Graph Neural Networks Neural Networks, Computer
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NCPepFold: Accurate Prediction of Noncanonical Cyclic Peptide Structures via Cyclization Optimization with Multigranular Representation.

Journal of chemical theory and computation May 13, 2025
Artificial intelligence-based peptide structure prediction methods have revolutionized biomolecular science. However, restricting predictions to peptides composed solely of 20 natural amino acids significantly limits their practical application; as s...
Cyclization Models, Molecular Amino Acids Deep Learning Peptides, Cyclic Protein Conformation
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Small Molecules Targeting the Structural Dynamics of AR-V7 Partially Disordered Proteins Using Deep Ensemble Docking.

Journal of chemical theory and computation May 13, 2025
The extensive conformational dynamics of partially disordered proteins hinders the efficiency of traditional in-silico structure-based drug discovery approaches due to the challenge of screening large chemical spaces of compounds, albeit with an exce...
Molecular Docking Simulation Molecular Dynamics Simulation Protein Conformation Humans Intrinsically Disordered Proteins Binding Sites Receptors, Androgen Small Molecule Libraries
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Scoring protein-ligand binding structures through learning atomic graphs with inter-molecular adjacency.

PLoS computational biology May 1, 2025
With a burgeoning number of artificial intelligence (AI) applications in various fields, biomolecular science has also given a big welcome to advanced AI techniques in recent years. In this broad field, scoring a protein-ligand binding structure to o...
Computational Biology Protein Conformation Proteins Deep Learning Models, Molecular Binding Sites Algorithms Protein Binding Ligands Drug Discovery
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PackPPI: An integrated framework for protein-protein complex side-chain packing and ΔΔG prediction based on diffusion model.

Protein science : a publication of the Protein Society May 1, 2025
Deep learning methods have played an increasingly pivotal role in advancing side-chain packing and mutation effect prediction (ΔΔG) for protein complexes. Although these two tasks are inherently closely related, they are typically treated separately ...
Deep Learning Computational Biology Software Algorithms Models, Molecular Protein Conformation Proteins Databases, Protein
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Multiscale Differential Geometry Learning for Protein Flexibility Analysis.

Journal of computational chemistry Mar 15, 2025
Protein structural fluctuations, measured by Debye-Waller factors or B-factors, are known to be closely associated with protein flexibility and function. Theoretical approaches have also been developed to predict B-factor values, which reflect protei...
Protein Conformation Machine Learning Proteins
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TopoQA: a topological deep learning-based approach for protein complex structure interface quality assessment.

Briefings in bioinformatics Mar 4, 2025
Even with the significant advances of AlphaFold-Multimer (AF-Multimer) and AlphaFold3 (AF3) in protein complex structure prediction, their accuracy is still not comparable with monomer structure prediction. Efficient and effective quality assessment ...
Protein Conformation Databases, Protein Models, Molecular Software Molecular Docking Simulation Computational Biology Neural Networks, Computer Deep Learning Proteins
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CaML: Chemistry-informed machine learning explains mutual changes between protein conformations and calcium ions in calcium-binding proteins using structural and topological features.

Protein science : a publication of the Protein Society Feb 1, 2025
Proteins' flexibility is a feature in communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression...
Machine Learning Algorithms Protein Conformation Calcium-Binding Proteins Models, Molecular Calcium
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AFFIPred: AlphaFold2 structure-based Functional Impact Prediction of missense variations.

Protein science : a publication of the Protein Society Feb 1, 2025
Protein structure holds immense potential for pathogenicity prediction, albeit structure-based predictors are limited compared to the sequence-based counterparts due to the "structure knowledge gap" between large number of available protein sequences...
Databases, Protein Models, Molecular Protein Conformation Mutation, Missense Computational Biology Humans Proteins Machine Learning Software
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