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Models, Molecular

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Accurate RNA 3D structure prediction using a language model-based deep learning approach.

Nature methods 39572716
Accurate prediction of RNA three-dimensional (3D) structures remains an unsolved challenge. Determining RNA 3D structures is crucial for understanding their functions and informing RNA-targeting drug development and synthetic biology design. The stru...
Computational Biology Deep Learning Humans Models, Molecular Nucleic Acid Conformation RNA Software
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ProAffinity-GNN: A Novel Approach to Structure-Based Protein-Protein Binding Affinity Prediction via a Curated Data Set and Graph Neural Networks.

Journal of chemical information and modeling 39558674
Protein-protein interactions (PPIs) are crucial for understanding biological processes and disease mechanisms, contributing significantly to advances in protein engineering and drug discovery. The accurate determination of binding affinities, essenti...
Databases, Protein Models, Molecular Neural Networks, Computer Protein Binding Protein Conformation Protein Interaction Mapping Proteins
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Rapid prediction of key residues for foldability by machine learning model enables the design of highly functional libraries with hyperstable constrained peptide scaffolds.

PLoS computational biology 39556614
Peptides are an emerging modality for developing therapeutics that can either agonize or antagonize cellular pathways associated with disease, yet peptides often suffer from poor chemical and physical stability, which limits their potential. However,...
Amino Acid Sequence Computational Biology Disulfides Machine Learning Models, Molecular Peptide Library Peptides Protein Folding
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A Divide-and-Conquer Approach to Nanoparticle Global Optimisation Using Machine Learning.

Journal of chemical information and modeling 39546324
Global optimization of the structure of atomic nanoparticles is often hampered by the presence of many funnels on the potential energy surface. While broad funnels are readily encountered and easily exploited by the search, narrow funnels are more di...
Machine Learning Metal Nanoparticles Models, Molecular Nanoparticles Thermodynamics
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Machine learning-based prediction of bioactivity in HIV-1 protease: insights from electron density analysis.

Future medicinal chemistry 39533796
To develop a model for predicting the biological activity of compounds targeting the HIV-1 protease and to establish factors influencing enzyme inhibition. Machine learning models were built based on a combination of Richard Bader's theory of Atoms ...
Electrons HIV Protease HIV Protease Inhibitors HIV-1 Humans Hydrogen Bonding Ligands Machine Learning Models, Molecular
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Deep learning for intrinsically disordered proteins: From improved predictions to deciphering conformational ensembles.

Current opinion in structural biology 39522439
Intrinsically disordered proteins (IDPs) lack a stable three-dimensional structure under physiological conditions, challenging traditional structure-based prediction methods. This review explores how modern deep learning approaches, which have revolu...
Deep Learning Humans Intrinsically Disordered Proteins Models, Molecular Protein Conformation
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Integration of molecular coarse-grained model into geometric representation learning framework for protein-protein complex property prediction.

Nature communications 39511202
Structure-based machine learning algorithms have been utilized to predict the properties of protein-protein interaction (PPI) complexes, such as binding affinity, which is critical for understanding biological mechanisms and disease treatments. While...
Algorithms Computational Biology Machine Learning Models, Molecular Neural Networks, Computer Protein Binding Protein Interaction Mapping Proteins
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GeoNet enables the accurate prediction of protein-ligand binding sites through interpretable geometric deep learning.

Structure (London, England : 1993) 39488202
The identification of protein binding residues is essential for understanding their functions in vivo. However, it remains a computational challenge to accurately identify binding sites due to the lack of known residue binding patterns. Local residue...
Binding Sites Computational Biology Deep Learning DNA Ligands Models, Molecular Protein Binding Proteins RNA
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Challenge for Deep Learning: Protein Structure Prediction of Ligand-Induced Conformational Changes at Allosteric and Orthosteric Sites.

Journal of chemical information and modeling 39484820
In the realm of biomedical research, understanding the intricate structure of proteins is crucial, as these structures determine how proteins function within our bodies and interact with potential drugs. Traditionally, methods like X-ray crystallogra...
Allosteric Site Databases, Protein Deep Learning Ligands Models, Molecular Protein Conformation Proteins
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ASpdb: an integrative knowledgebase of human protein isoforms from experimental and AI-predicted structures.

Nucleic acids research 39530217
Alternative splicing is a crucial cellular process in eukaryotes, enabling the generation of multiple protein isoforms with diverse functions from a single gene. To better understand the impact of alternative splicing on protein structures, protein-p...
Alternative Splicing Databases, Protein Humans Knowledge Bases Models, Molecular Molecular Sequence Annotation Protein Conformation Protein Isoforms
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