AIMC Topic: Protein Conformation

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Predicting the conformations of the silk protein through deep learning.

The Analyst Apr 26, 2021
As with other proteins, the conformation of the silk protein is critical for determining the mechanical, optical and biological performance of materials. However, an efficient, accurate and time-efficient method for evaluating the protein conformatio...
Protein Conformation Deep Learning Silk Neural Networks, Computer Algorithms
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Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences.

Proceedings of the National Academy of Sciences of the United States of America Apr 13, 2021
In the field of artificial intelligence, a combination of scale in data and model capacity enabled by unsupervised learning has led to major advances in representation learning and statistical generation. In the life sciences, the anticipated growth ...
Unsupervised Machine Learning Sequence Homology, Amino Acid Sequence Analysis, Protein Amino Acids Protein Conformation
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Protein sequence design by conformational landscape optimization.

Proceedings of the National Academy of Sciences of the United States of America Mar 16, 2021
The protein design problem is to identify an amino acid sequence that folds to a desired structure. Given Anfinsen's thermodynamic hypothesis of folding, this can be recast as finding an amino acid sequence for which the desired structure is the lowe...
Neural Networks, Computer Thermodynamics Protein Folding Models, Molecular Proteins Protein Conformation
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Confronting pitfalls of AI-augmented molecular dynamics using statistical physics.

The Journal of chemical physics Dec 21, 2020
Artificial intelligence (AI)-based approaches have had indubitable impact across the sciences through the ability to extract relevant information from raw data. Recently, AI has also found use in enhancing the efficiency of molecular simulations, whe...
Protein Conformation Peptides Entropy Models, Statistical Ligands Proteins Molecular Dynamics Simulation Artificial Intelligence
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'The game has changed.' AI triumphs at protein folding.

Science (New York, N.Y.) Dec 4, 2020
Artificial Intelligence Software Protein Conformation Protein Folding
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'It will change everything': DeepMind's AI makes gigantic leap in solving protein structures.

Nature Dec 1, 2020
Proteins Models, Molecular Deep Learning Time Factors Protein Conformation Caspases Crystallography, X-Ray
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MusiteDeep: a deep-learning based webserver for protein post-translational modification site prediction and visualization.

Nucleic acids research Jul 2, 2020
MusiteDeep is an online resource providing a deep-learning framework for protein post-translational modification (PTM) site prediction and visualization. The predictor only uses protein sequences as input and no complex features are needed, which res...
Protein Processing, Post-Translational Proteins Sequence Analysis, Protein Software Models, Molecular Protein Conformation Deep Learning Internet Computer Graphics
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Geometric potentials from deep learning improve prediction of CDR H3 loop structures.

Bioinformatics (Oxford, England) Jul 1, 2020
MOTIVATION: Antibody structure is largely conserved, except for a complementarity-determining region featuring six variable loops. Five of these loops adopt canonical folds which can typically be predicted with existing methods, while the remaining l...
Antibodies Complementarity Determining Regions Deep Learning Protein Conformation Models, Molecular
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A Web-Based Protocol for Interprotein Contact Prediction by Deep Learning.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2020
Identifying residue-residue contacts in protein-protein interactions or complex is crucial for understanding protein and cell functions. DCA (direct-coupling analysis) methods shed some light on this, but they need many sequence homologs to yield acc...
Protein Conformation Sequence Analysis, Protein Computational Biology Proteins Deep Learning Protein Interaction Maps
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evERdock BAI: Machine-learning-guided selection of protein-protein complex structure.

The Journal of chemical physics Dec 7, 2019
Computational techniques for accurate and efficient prediction of protein-protein complex structures are widely used for elucidating protein-protein interactions, which play important roles in biological systems. Recently, it has been reported that s...
Molecular Dynamics Simulation Protein Binding Machine Learning Protein Conformation Proteins
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