AIMC Topic: Protein Folding

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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 ...
Protein Folding Computational Biology Proteins Models, Molecular Protein Conformation Deep Learning
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Unsupervised Learning of Progress Coordinates during Weighted Ensemble Simulations: Application to NTL9 Protein Folding.

Journal of chemical theory and computation Mar 19, 2025
A major challenge for many rare-event sampling strategies is the identification of progress coordinates that capture the slowest relevant motions. Machine-learning methods that can identify progress coordinates in an unsupervised manner have therefor...
Deep Learning Unsupervised Machine Learning Protein Folding Molecular Dynamics Simulation Markov Chains
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Machine learning methods to study sequence-ensemble-function relationships in disordered proteins.

Current opinion in structural biology Mar 12, 2025
Recent years have seen tremendous developments in the use of machine learning models to link amino-acid sequence, structure, and function of folded proteins. These methods are, however, rarely applicable to the wide range of proteins and sequences th...
Intrinsically Disordered Proteins Machine Learning Protein Conformation Protein Folding Humans Models, Molecular Amino Acid Sequence Computational Biology
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AI protocol for retrieving protein dynamic structures from two-dimensional infrared spectra.

Proceedings of the National Academy of Sciences of the United States of America Feb 14, 2025
Understanding the dynamic evolution of protein structures is crucial for uncovering their biological functions. Yet, real-time prediction of these dynamic structures remains a significant challenge. Two-dimensional infrared (2DIR) spectroscopy is a p...
Proteins Protein Conformation Spectrophotometry, Infrared Protein Folding Machine Learning
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Severe deviation in protein fold prediction by advanced AI: a case study.

Scientific reports Feb 8, 2025
Artificial intelligence (AI) and deep learning are making groundbreaking strides in protein structure prediction. AlphaFold is remarkable in this arena for its outstanding accuracy in modelling proteins fold based solely on their amino acid sequences...
Computational Biology Proteins Artificial Intelligence Deep Learning Protein Folding Models, Molecular Protein Conformation
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Learning the language of life with AI.

Science (New York, N.Y.) Jan 30, 2025
In 2021, a year before ChatGPT took the world by storm amid the excitement about generative artificial intelligence (AI), AlphaFold 2 cracked the 50-year-old protein-folding problem, predicting three-dimensional (3D) structures for more than 200 mill...
Protein Folding Language Proteins Artificial Intelligence
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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 Nov 18, 2024
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,...
Models, Molecular Amino Acid Sequence Peptide Library Computational Biology Disulfides Protein Folding Machine Learning Peptides
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Ab initio characterization of protein molecular dynamics with AIBMD.

Nature Nov 6, 2024
Biomolecular dynamics simulation is a fundamental technology for life sciences research, and its usefulness depends on its accuracy and efficiency. Classical molecular dynamics simulation is fast but lacks chemical accuracy. Quantum chemistry methods...
Molecular Dynamics Simulation Quantum Theory Protein Conformation Nuclear Magnetic Resonance, Biomolecular Proteins Density Functional Theory Peptides Artificial Intelligence Time Factors Machine Learning Protein Unfolding Thermodynamics Protein Folding
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Exploring structural diversity across the protein universe with The Encyclopedia of Domains.

Science (New York, N.Y.) Nov 1, 2024
The AlphaFold Protein Structure Database (AFDB) contains more than 214 million predicted protein structures composed of domains, which are independently folding units found in multiple structural and functional contexts. Identifying domains can enabl...
Proteins Databases, Protein Deep Learning Protein Folding Protein Domains
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Unraveling dynamic protein structures by two-dimensional infrared spectra with a pretrained machine learning model.

Proceedings of the National Academy of Sciences of the United States of America Jun 25, 2024
Dynamic protein structures are crucial for deciphering their diverse biological functions. Two-dimensional infrared (2DIR) spectroscopy stands as an ideal tool for tracing rapid conformational evolutions in proteins. However, linking spectral charact...
Protein Conformation Protein Structure, Secondary Machine Learning Spectrophotometry, Infrared Protein Folding Proteins
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