AIMC Topic: Protein Conformation

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Computer-Aided Techniques in the Engineering of Enzyme Binding Pockets: New Perspectives and Frontiers.

Journal of agricultural and food chemistry Aug 11, 2025
Enzymes, recognized for their remarkable catalytic efficiency, play a crucial role in a myriad of biochemical reactions. However, the catalytic performance of natural enzymes frequently does not meet the demands of specific applications. To address t...
Protein Engineering Enzymes Protein Conformation Binding Sites Biocatalysis
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MEGDTA: multi-modal drug-target affinity prediction based on protein three-dimensional structure and ensemble graph neural network.

BMC genomics Aug 11, 2025
BACKGROUND: Drug development is a time-consuming and costly endeavor, and utilizing computer-aided methods to predict drug-target affinity (DTA) can significantly accelerate this process. The key to accurate DTA prediction lies in selecting appropria...
Protein Conformation Graph Neural Networks Computational Biology Proteins Neural Networks, Computer
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PreMode predicts mode-of-action of missense variants by deep graph representation learning of protein sequence and structural context.

Nature communications Aug 5, 2025
Accurate prediction of the functional impact of missense variants is important for disease gene discovery, clinical genetic diagnostics, therapeutic strategies, and protein engineering. Previous efforts have focused on predicting a binary pathogenici...
Humans Neural Networks, Computer Proteins Amino Acid Sequence Protein Conformation Deep Learning Computational Biology Mutation, Missense
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Sequence-based virtual screening using transformers.

Nature communications Jul 28, 2025
Protein-ligand interactions play central roles in myriad biological processes and are of key importance in drug design. Deep learning approaches are becoming cost-effective alternatives to high-throughput experimental methods for ligand identificatio...
Humans Amino Acid Sequence Protein Kinase Inhibitors Ligands Protein Binding Protein Conformation Drug Design Proto-Oncogene Proteins c-abl Drug Evaluation, Preclinical ErbB Receptors Deep Learning
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Utilizing protein structure graph embeddings to predict the pathogenicity of missense variants.

NAR genomics and bioinformatics Jul 24, 2025
Genetic variants can impact the structure of the corresponding protein, which can have detrimental effects on protein function. While the effect of protein-truncating variants is often easier to evaluate, most genetic variants that affect the protein...
Computational Biology Proteins Machine Learning Mutation, Missense Humans Protein Conformation Algorithms
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Navigating protein landscapes with a machine-learned transferable coarse-grained model.

Nature chemistry Jul 18, 2025
The most popular and universally predictive protein simulation models employ all-atom molecular dynamics, but they come at extreme computational cost. The development of a universal, computationally efficient coarse-grained (CG) model with similar pr...
Thermodynamics Protein Folding Molecular Dynamics Simulation Protein Conformation Machine Learning Proteins
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Assisting and accelerating NMR assignment with restrained structure prediction.

Communications biology Jul 18, 2025
Accurate dynamic protein structures are essential for drug design. NMR experiments can detect protein structures and potential dynamics, but the spectrum assignment and structure determination requires expertise and is time-consuming, while deep-lear...
Proteins Models, Molecular Nuclear Magnetic Resonance, Biomolecular Magnetic Resonance Spectroscopy Protein Conformation Protein Folding
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AF3Score: A Score-Only Adaptation of AlphaFold3 for Biomolecular Structure Evaluation.

Journal of chemical information and modeling Jul 16, 2025
Scoring biomolecular complexes remains central to structural modeling efforts. Recent studies suggest that AlphaFold (AF) - a revolutionary deep learning model for biomolecular structure prediction - has implicitly learned an approximate biophysical ...
Deep Learning Protein Binding Ligands Proteins Protein Conformation Models, Molecular Protein Folding
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Consensus structure prediction of A. thaliana's MCTP4 structure using prediction tools and coarse grained simulations of transmembrane domain dynamics.

PloS one Jul 15, 2025
Multiple C2 Domains and Transmembrane region Proteins (MCTPs) in plants have been identified as important functional and structural components of plasmodesmata cytoplasmic bridges, which are vital for cell-cell communication. MCTPs are endoplasmic re...
Molecular Dynamics Simulation Protein Conformation Membrane Proteins Deep Learning Endoplasmic Reticulum Arabidopsis Proteins Protein Domains Arabidopsis
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Protein Structure-Function Relationship: A Kernel-PCA Approach for Reaction Coordinate Identification.

Journal of chemical theory and computation Jul 14, 2025
In this study, we propose a Kernel-PCA model designed to capture structure-function relationships in a protein. This model also enables the ranking of reaction coordinates according to their impact on protein properties. By leveraging machine learnin...
Principal Component Analysis Molecular Dynamics Simulation Protein Conformation Receptors, G-Protein-Coupled Machine Learning Proteins Structure-Activity Relationship
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