AIMC Topic: Protein Conformation

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Next generation technologies for protein structure determination: challenges and breakthroughs in plant biology applications.

Journal of plant physiology Jul 1, 2025
Advancements in structural biology have significantly deepened our understanding of plant proteins, which are central to critical biological functions such as photosynthesis, metabolism, signal transduction, and structural architechture. Gaining insi...
Plants Plant Proteins Mass Spectrometry Magnetic Resonance Spectroscopy Cryoelectron Microscopy Crystallography, X-Ray Protein Conformation
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Extracting Residue Solvent Exposure from Covalent Labeling Data with Machine Learning: A Hybrid Approach for Protein Structure Prediction.

Journal of the American Society for Mass Spectrometry Jun 4, 2025
Hydroxyl radical protein footprinting (HRPF) coupled with mass spectrometry yields information about residue solvent exposure and protein topology. However, data from these experiments are sparse and require computational interpretation to generate u...
Protein Conformation Hydroxyl Radical Models, Molecular Solvents Protein Footprinting Machine Learning Algorithms Mass Spectrometry Proteins
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Characterization of conformational flexibility in protein structures by applying artificial intelligence to molecular modeling.

Journal of structural biology Jun 1, 2025
Recent AI applications have revolutionized the modeling of structurally unresolved protein regions, thereby complementing traditional computational methods. These state-of-the-art techniques can generate numerous candidate structures, significantly e...
Proteins Models, Molecular Artificial Intelligence Protein Folding Ubiquitin Thermodynamics Molecular Dynamics Simulation Protein Conformation
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AI-Assisted Protein-Peptide Complex Prediction in a Practical Setting.

Journal of computational chemistry May 30, 2025
Accurate prediction of protein-peptide complex structures plays a critical role in structure-based drug design, including antibody design. Most peptide-docking benchmark studies were conducted using crystal structures of protein-peptide complexes; as...
Proteins Protein Conformation Peptides Molecular Docking Simulation Machine Learning
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for Investigating Conformational Transitions and Environmental Interactions of Proteins.

Journal of chemical theory and computation May 27, 2025
Proteins are inherently dynamic molecules, and their conformational transitions among various states are essential for numerous biological processes, which are often modulated by their interactions with surrounding environments. Although molecular dy...
Proteins Thermodynamics Molecular Dynamics Simulation Protein Conformation
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TIDGN: A Transfer Learning Framework for Predicting Interactions of Intrinsically Disordered Proteins with High Conformational Dynamics.

Journal of chemical information and modeling May 26, 2025
Interactions between intrinsically disordered proteins (IDPs) are crucial for biological processes, such as intracellular liquid-liquid phase separation (LLPS). Experiments (e.g., NMR) and simulations used to study IDP interactions encounter a variet...
Molecular Dynamics Simulation Intrinsically Disordered Proteins Protein Conformation Machine Learning Protein Binding
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AbSet: A Standardized Data Set of Antibody Structures for Machine Learning Applications.

Journal of chemical information and modeling May 26, 2025
Machine learning algorithms have played a fundamental role in the development of therapeutic antibodies by being trained on data sets of sequences and/or structures. However, structural data sets remain limited, especially those that include antibody...
Protein Conformation Machine Learning Databases, Protein Molecular Docking Simulation Antibodies
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Integrating Machine Learning-Based Pose Sampling with Established Scoring Functions for Virtual Screening.

Journal of chemical information and modeling May 26, 2025
Physics-based docking methods have long been the cornerstone of structure-based virtual screening (VS). However, the emergence of machine learning (ML)-based docking approaches has opened new possibilities for enhancing VS technologies. In this study...
Drug Evaluation, Preclinical Protein Conformation Machine Learning Molecular Docking Simulation Proteins
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Machine Learning of Molecular Dynamics Simulations Provides Insights into the Modulation of Viral Capsid Assembly.

Journal of chemical information and modeling May 26, 2025
An effective approach in the development of novel antivirals is to target the assembly of viral capsids by using capsid assembly modulators (CAMs). CAMs targeting hepatitis B virus (HBV) have two major modes of function: they can either accelerate nu...
Capsid Proteins Capsid Protein Conformation Machine Learning Protein Multimerization Hepatitis B virus Virus Assembly Molecular Dynamics Simulation
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Deep learning-guided design of dynamic proteins.

Science (New York, N.Y.) May 22, 2025
Deep learning has advanced the design of static protein structures, but the controlled conformational changes that are hallmarks of natural signaling proteins have remained inaccessible to de novo design. Here, we describe a general deep learning-gui...
Protein Engineering Allosteric Regulation Ligands Protein Conformation Mutation Molecular Dynamics Simulation Deep Learning Proteins
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