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Protein Conformation

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Exploring Protein Conformational Changes Using a Large-Scale Biophysical Sampling Augmented Deep Learning Strategy.

Advanced science (Weinheim, Baden-Wurttemberg, Germany) Oct 10, 2024
Inspired by the success of deep learning in predicting static protein structures, researchers are now actively exploring other deep learning algorithms aimed at predicting the conformational changes of proteins. Currently, a major challenge in the de...
Humans Molecular Dynamics Simulation Deep Learning Protein Conformation Proteins Algorithms
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AI Prediction of Structural Stability of Nanoproteins Based on Structures and Residue Properties by Mean Pooled Dual Graph Convolutional Network.

Interdisciplinary sciences, computational life sciences Oct 5, 2024
The structural stability of proteins is an important topic in various fields such as biotechnology, pharmaceuticals, and enzymology. Specifically, understanding the structural stability of protein is crucial for protein design. Artificial design, whi...
Neural Networks, Computer Protein Stability Protein Conformation Artificial Intelligence Proteins Thermodynamics Algorithms Models, Molecular
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Deep learning for discriminating non-trivial conformational changes in molecular dynamics simulations of SARS-CoV-2 spike-ACE2.

Scientific reports Sep 30, 2024
Molecular dynamics (MD) simulations produce a substantial volume of high-dimensional data, and traditional methods for analyzing these data pose significant computational demands. Advances in MD simulation analysis combined with deep learning-based a...
Binding Sites Protein Binding Protein Conformation SARS-CoV-2 Spike Glycoprotein, Coronavirus Humans Deep Learning Angiotensin-Converting Enzyme 2 Mutation COVID-19 Protein Domains Molecular Dynamics Simulation
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Exploring the potential of structure-based deep learning approaches for T cell receptor design.

PLoS computational biology Sep 30, 2024
Deep learning methods, trained on the increasing set of available protein 3D structures and sequences, have substantially impacted the protein modeling and design field. These advancements have facilitated the creation of novel proteins, or the optim...
Protein Engineering Humans Deep Learning Computational Biology Models, Molecular Protein Conformation Receptors, Antigen, T-Cell Protein Binding
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Enhanced Sampling of Biomolecular Slow Conformational Transitions Using Adaptive Sampling and Machine Learning.

Journal of chemical theory and computation Sep 20, 2024
Biomolecular simulations often suffer from the "time scale problem", hindering the study of rare events occurring over extended time scales. Enhanced sampling techniques aim to alleviate this issue by accelerating conformational transitions, yet they...
Protein Conformation Thermodynamics Alanine Machine Learning Markov Chains Molecular Dynamics Simulation Dipeptides
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A Mode Evolution Metric to Extract Reaction Coordinates for Biomolecular Conformational Transitions.

Journal of chemical theory and computation Sep 17, 2024
The complex, multidimensional energy landscape of biomolecules makes the extraction of suitable, nonintuitive collective variables (CVs) that describe their conformational transitions challenging. At present, dimensionality reduction approaches and m...
Monte Carlo Method Machine Learning Thermodynamics Molecular Dynamics Simulation Dipeptides Protein Conformation
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Combined Physics- and Machine-Learning-Based Method to Identify Druggable Binding Sites Using SILCS-Hotspots.

Journal of chemical information and modeling Sep 16, 2024
Identifying druggable binding sites on proteins is an important and challenging problem, particularly for cryptic, allosteric binding sites that may not be obvious from X-ray, cryo-EM, or predicted structures. The Site-Identification by Ligand Compet...
Proteins Molecular Dynamics Simulation Protein Conformation Binding Sites Ligands Machine Learning Drug Discovery Protein Binding
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Integrative residue-intuitive machine learning and MD Approach to Unveil Allosteric Site and Mechanism for β2AR.

Nature communications Sep 16, 2024
Allosteric drugs offer a new avenue for modern drug design. However, the identification of cryptic allosteric sites presents a formidable challenge. Following the allostery nature of residue-driven conformation transition, we propose a state-of-the-a...
Allosteric Site Allosteric Regulation Machine Learning Drug Design Protein Conformation Molecular Dynamics Simulation Humans Receptors, Adrenergic, beta-2
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Modelling protein complexes with crosslinking mass spectrometry and deep learning.

Nature communications Sep 9, 2024
Scarcity of structural and evolutionary information on protein complexes poses a challenge to deep learning-based structure modelling. We integrate experimental distance restraints obtained by crosslinking mass spectrometry (MS) into AlphaFold-Multim...
Deep Learning Bacillus subtilis Cross-Linking Reagents Mass Spectrometry Iron Models, Molecular Bacterial Proteins Protein Conformation
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Utilizing Molecular Dynamics Simulations, Machine Learning, Cryo-EM, and NMR Spectroscopy to Predict and Validate Protein Dynamics.

International journal of molecular sciences Sep 8, 2024
Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements in experimental techniques, computational methods, and artificial intelligence...
Proteins Molecular Dynamics Simulation Protein Conformation Humans Machine Learning Cryoelectron Microscopy Nuclear Magnetic Resonance, Biomolecular Magnetic Resonance Spectroscopy
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