AIMC Topic: Protein Conformation

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Estimating protein complex model accuracy based on ultrafast shape recognition and deep learning in CASP15.

Proteins Aug 8, 2023
This article reports and analyzes the results of protein complex model accuracy estimation by our methods (DeepUMQA3 and GraphGPSM) in the 15th Critical Assessment of techniques for protein Structure Prediction (CASP15). The new deep learning-based m...
Proteins Protein Conformation Neural Networks, Computer Deep Learning Computational Biology
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Mapping HDX-MS Data to Protein Conformations through Training Ensemble-Based Models.

Journal of the American Society for Mass Spectrometry Aug 7, 2023
An original approach that adopts machine learning inference to predict protein structural information using hydrogen-deuterium exchange mass spectrometry (HDX-MS) is described. The method exploits an in-house optimization program that increases the r...
Artificial Intelligence Mass Spectrometry Hydrogen Deuterium Exchange-Mass Spectrometry Deuterium Exchange Measurement Proteins Protein Conformation
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Improving protein structure prediction with extended sequence similarity searches and deep-learning-based refinement in CASP15.

Proteins Jul 24, 2023
The human predictor team PEZYFoldings got first place with the assessor's formulae (3rd place with Global Distance Test Total Score [GDT-TS]) in the single-domain category and 10th place in the multimer category in Critical Assessment of Structure Pr...
Protein Conformation Deep Learning Computational Biology Proteins Models, Molecular Humans
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More than just pattern recognition: Prediction of uncommon protein structure features by AI methods.

Proceedings of the National Academy of Sciences of the United States of America Jul 3, 2023
The CASP14 experiment demonstrated the extraordinary structure modeling capabilities of artificial intelligence (AI) methods. That result has ignited a fierce debate about what these methods are actually doing. One of the criticisms has been that the...
Artificial Intelligence Proteins Neural Networks, Computer Protein Structure, Secondary Amino Acid Sequence Protein Conformation
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AlphaFold and the future of structural biology.

Acta crystallographica. Section D, Structural biology Jul 1, 2023
This editorial acknowledges the transformative impact of new machine-learning methods, such as the use of AlphaFold, but also makes the case for the continuing need for experimental structural biology.
Machine Learning Cryoelectron Microscopy Crystallography, X-Ray Protein Conformation Biology
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DeepBindGCN: Integrating Molecular Vector Representation with Graph Convolutional Neural Networks for Protein-Ligand Interaction Prediction.

Molecules (Basel, Switzerland) Jun 10, 2023
The core of large-scale drug virtual screening is to select the binders accurately and efficiently with high affinity from large libraries of small molecules in which non-binders are usually dominant. The binding affinity is significantly influenced ...
Protein Conformation Ligands Neural Networks, Computer Protein Binding Proteins Drug Evaluation, Preclinical
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An end-to-end deep learning method for protein side-chain packing and inverse folding.

Proceedings of the National Academy of Sciences of the United States of America May 30, 2023
Protein side-chain packing (PSCP), the task of determining amino acid side-chain conformations given only backbone atom positions, has important applications to protein structure prediction, refinement, and design. Many methods have been proposed to ...
Protein Folding Molecular Conformation Protein Conformation Amino Acids Deep Learning Proteins
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Residue-level error detection in cryoelectron microscopy models.

Structure (London, England : 1993) May 29, 2023
Building accurate protein models into moderate resolution (3-5 Å) cryoelectron microscopy (cryo-EM) maps is challenging and error prone. We have developed MEDIC (Model Error Detection in Cryo-EM), a robust statistical model that identifies local back...
Proteins Protein Conformation Machine Learning Models, Molecular Cryoelectron Microscopy
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EvoRator2: Predicting Site-specific Amino Acid Substitutions Based on Protein Structural Information Using Deep Learning.

Journal of molecular biology May 23, 2023
Multiple sequence alignments (MSAs) are the workhorse of molecular evolution and structural biology research. From MSAs, the amino acids that are tolerated at each site during protein evolution can be inferred. However, little is known regarding the ...
Proteins Deep Learning Algorithms Protein Conformation Amino Acid Substitution Amino Acids Computational Biology
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Predicting Protein-Peptide Interactions: Benchmarking Deep Learning Techniques and a Comparison with Focused Docking.

Journal of chemical information and modeling May 11, 2023
The accurate prediction of protein structures achieved by deep learning (DL) methods is a significant milestone and has deeply impacted structural biology. Shortly after its release, AlphaFold2 has been evaluated for predicting protein-peptide intera...
Software Peptides Molecular Docking Simulation Proteins Deep Learning Protein Conformation Protein Binding
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