AIMC Topic: Protein Conformation

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Frustration in physiology and molecular medicine.

Molecular aspects of medicine Apr 23, 2025
Molecules provide the ultimate language in terms of which physiology and pathology must be understood. Myriads of proteins participate in elaborate networks of interactions and perform chemical activities coordinating the life of cells. To perform th...
Protein Conformation Protein Folding Molecular Medicine Gene Regulatory Networks Proteins Humans Animals
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Emerging frontiers in protein structure prediction following the AlphaFold revolution.

Journal of the Royal Society, Interface Apr 16, 2025
Models of protein structures enable molecular understanding of biological processes. Current protein structure prediction tools lie at the interface of biology, chemistry and computer science. Millions of protein structure models have been generated ...
Models, Molecular Protein Conformation Protein Folding Deep Learning Computational Biology Proteins
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Machine Learning and Structural Dynamics-Based Approach to Reveal Molecular Mechanism of PTEN Missense Mutations Shared by Cancer and Autism Spectrum Disorder.

Journal of chemical information and modeling Apr 14, 2025
Missense mutations in oncogenic proteins that are concurrently associated with neurodevelopmental disorders have garnered significant attention. Phosphatase and tensin homologue (PTEN) serves as a paradigmatic model for mapping its mutational landsca...
Mutation, Missense PTEN Phosphohydrolase Molecular Dynamics Simulation Protein Conformation Autism Spectrum Disorder Neoplasms Humans Machine Learning
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Advancing Molecular Simulations: Merging Physical Models, Experiments, and AI to Tackle Multiscale Complexity.

The journal of physical chemistry letters Apr 3, 2025
Proteins and protein complexes form adaptable networks that regulate essential biochemical pathways and define cell phenotypes through dynamic mechanisms and interactions. Advances in structural biology and molecular simulations have revealed how pro...
Protein Conformation Cryoelectron Microscopy Proteins Molecular Dynamics Simulation Machine Learning
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Can Deep Learning Blind Docking Methods be Used to Predict Allosteric Compounds?

Journal of chemical information and modeling Apr 1, 2025
Allosteric compounds offer an alternative mode of inhibition to orthosteric compounds with opportunities for selectivity and noncompetition. Structure-based drug design (SBDD) of allosteric compounds introduces complications compared to their orthost...
Molecular Docking Simulation Drug Design Deep Learning Protein Kinase Inhibitors Cyclin-Dependent Kinase 2 Allosteric Regulation Ligands Protein Conformation
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Predicting protein-protein interaction with interpretable bilinear attention network.

Computer methods and programs in biomedicine Mar 30, 2025
BACKGROUND AND OBJECTIVE: Protein-protein interactions (PPIs) play the key roles in myriad biological processes, helping to understand the protein function and disease pathology. Identification of PPIs and their interaction types through wet experime...
Protein Binding Computational Biology Proteins Algorithms Deep Learning Protein Conformation Protein Interaction Mapping Sequence Analysis, Protein Databases, Protein Amino Acid Sequence Humans Neural Networks, Computer
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Fitting Atomic Structures into Cryo-EM Maps by Coupling Deep Learning-Enhanced Map Processing with Global-Local Optimization.

Journal of chemical information and modeling Mar 28, 2025
With the breakthroughs in protein structure prediction technology, constructing atomic structures from cryo-electron microscopy (cryo-EM) density maps through structural fitting has become increasingly critical. However, the accuracy of the construct...
Protein Conformation Cryoelectron Microscopy Proteins Deep Learning Models, Molecular
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Atomic context-conditioned protein sequence design using LigandMPNN.

Nature methods Mar 28, 2025
Protein sequence design in the context of small molecules, nucleotides and metals is critical to enzyme and small-molecule binder and sensor design, but current state-of-the-art deep-learning-based sequence design methods are unable to model nonprote...
Amino Acid Sequence Protein Conformation Ligands Proteins Crystallography, X-Ray Deep Learning Protein Binding Models, Molecular
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Insights into phosphorylation-induced influences on conformations and inhibitor binding of CDK6 through GaMD trajectory-based deep learning.

Physical chemistry chemical physics : PCCP Mar 26, 2025
The phosphorylation of residue T177 produces a significant effect on the conformational dynamics of CDK6. Gaussian accelerated molecular dynamics (GaMD) simulations followed by deep learning (DL) are applied to explore the molecular mechanism of the ...
Protein Binding Phosphorylation Humans Protein Conformation Thermodynamics Deep Learning Molecular Dynamics Simulation Protein Kinase Inhibitors Cyclin-Dependent Kinase 6
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TopEC: prediction of Enzyme Commission classes by 3D graph neural networks and localized 3D protein descriptor.

Nature communications Mar 20, 2025
Tools available for inferring enzyme function from general sequence, fold, or evolutionary information are generally successful. However, they can lead to misclassification if a deviation in local structural features influences the function. Here, we...
Enzymes Neural Networks, Computer Graph Neural Networks Computational Biology Software Protein Conformation Algorithms Binding Sites
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