AIMC Topic: Proteins

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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 ...
Protein Binding Proteins Deep Learning Protein Conformation Protein Folding Models, Molecular Ligands
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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...
Proteins Receptors, G-Protein-Coupled Machine Learning Molecular Dynamics Simulation Protein Conformation Structure-Activity Relationship Principal Component Analysis
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CoBdock-2: enhancing blind docking performance through hybrid feature selection combining ensemble and multimodel feature selection approaches.

Journal of computer-aided molecular design Jul 13, 2025
Identifying orthosteric binding sites and predicting small molecule affinities remains a key challenge in virtual screening. While blind docking explores the entire protein surface, its precision is hindered by the vast search space. Cavity detection...
Binding Sites Protein Binding Proteins Algorithms Ligands Machine Learning Protein Conformation Molecular Docking Simulation Software
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Rprot-Vec: a deep learning approach for fast protein structure similarity calculation.

BMC bioinformatics Jul 10, 2025
BACKGROUND: Predicting protein structural similarity and detecting homologous sequences remain fundamental and challenging tasks in computational biology. Accurate identification of structural homologs enables function inference for newly discovered ...
Protein Conformation Sequence Analysis, Protein Proteins Databases, Protein Software Deep Learning Computational Biology
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End looms for protein contest?

Science (New York, N.Y.) Jul 10, 2025
NIH has not committed to continuing support for contest that inspired AI tools for predicting how proteins would fold.
National Institutes of Health (U.S.) Artificial Intelligence United States Proteins Protein Folding
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Integrating Protein Language Models and Geometric Deep Learning for Peptide Toxicity Prediction.

Journal of chemical information and modeling Jul 8, 2025
Peptide toxicity prediction is a critical task in biomedical research, influencing drug safety and therapeutic development. Traditional methods, relying on sequence similarity or handcrafted features, struggle to capture the complex relationship betw...
Humans Neural Networks, Computer Peptides Protein Conformation Deep Learning Models, Molecular Proteins Amino Acid Sequence
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Comprehensive protein datasets and benchmarking for liquid-liquid phase separation studies.

Genome biology Jul 8, 2025
BACKGROUND: Proteins self-organize in dynamic cellular environments by assembling into reversible biomolecular condensates through liquid-liquid phase separation (LLPS). These condensates can comprise single or multiple proteins, with different roles...
Phase Separation Algorithms Benchmarking Biomolecular Condensates Proteins Databases, Protein
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Mapping the Conformational Heterogeneity Intrinsic to the Protein Native Ensemble.

Biochemistry Jul 4, 2025
In the AlphaFold era, there is a significant momentum in predicting protein structures, functionality, and mutational hotspots from deep learning approaches. In this review, we highlight how structural information is only a starting point in understa...
Humans Proteins Protein Folding Models, Molecular Protein Conformation
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MIC: A deep learning tool for assigning ions and waters in cryo-EM and crystal structures.

Nature communications Jul 4, 2025
At sufficiently high resolution, x-ray crystallography and cryogenic electron microscopy are capable of resolving small spherical map features corresponding to either water or ions. Correct classification of these sites provides crucial insight for u...
Crystallography, X-Ray Cryoelectron Microscopy Water Proteins Models, Molecular Deep Learning Ions
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Graph with Residue-Based Cross-Modal Framework Enhances Cell Function-Related Protein Properties Prediction.

Journal of chemical information and modeling Jul 3, 2025
Accurate prediction of protein properties that influence cellular functions is crucial for drug design, disease research, and guiding biological wet-lab experiments. Previous methods primarily relied on physicochemical property analysis and homologou...
Protein Conformation Neural Networks, Computer Proteins
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