AIMC Topic: Protein Conformation

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Role of environmental specificity in CASP results.

BMC bioinformatics Nov 11, 2023
BACKGROUND: Recently, significant progress has been made in the field of protein structure prediction by the application of artificial intelligence techniques, as shown by the results of the CASP13 and CASP14 (Critical Assessment of Structure Predict...
Protein Conformation Protein Folding Artificial Intelligence Proteins Models, Molecular Hydrophobic and Hydrophilic Interactions
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Equivariant Flexible Modeling of the Protein-Ligand Binding Pose with Geometric Deep Learning.

Journal of chemical theory and computation Nov 8, 2023
Flexible modeling of the protein-ligand complex structure is a fundamental challenge for in silico drug development. Recent studies have improved commonly used docking tools by incorporating extra-deep learning-based steps. However, such strategies l...
Protein Conformation Deep Learning Proteins Protein Binding Ligands Molecular Docking Simulation
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The bad and the good of trends in model building and refinement for sparse-data regions: pernicious forms of overfitting versus good new tools and predictions.

Acta crystallographica. Section D, Structural biology Nov 3, 2023
Model building and refinement, and the validation of their correctness, are very effective and reliable at local resolutions better than about 2.5 Å for both crystallography and cryo-EM. However, at local resolutions worse than 2.5 Å both the procedu...
Artificial Intelligence Peptides Crystallography, X-Ray Protein Conformation Proteins Cryoelectron Microscopy Models, Molecular
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CSM-Potential2: A comprehensive deep learning platform for the analysis of protein interacting interfaces.

Proteins Oct 23, 2023
Proteins are molecular machinery that participate in virtually all essential biological functions within the cell, which are tightly related to their 3D structure. The importance of understanding protein structure-function relationship is highlighted...
Protein Interaction Mapping Protein Interaction Domains and Motifs Databases, Protein Models, Molecular Protein Conformation Binding Sites Ligands Computational Biology Proteins Deep Learning Protein Binding Humans Software
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Deep-LASI: deep-learning assisted, single-molecule imaging analysis of multi-color DNA origami structures.

Nature communications Oct 17, 2023
Single-molecule experiments have changed the way we explore the physical world, yet data analysis remains time-consuming and prone to human bias. Here, we introduce Deep-LASI (Deep-Learning Assisted Single-molecule Imaging analysis), a software suite...
Humans Deep Learning Fluorescence Resonance Energy Transfer Protein Conformation Single Molecule Imaging DNA Microscopy
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CryoREAD: de novo structure modeling for nucleic acids in cryo-EM maps using deep learning.

Nature methods Oct 2, 2023
DNA and RNA play fundamental roles in various cellular processes, where their three-dimensional structures provide information critical to understanding the molecular mechanisms of their functions. Although an increasing number of nucleic acid struct...
RNA DNA Cryoelectron Microscopy Nucleic Acids Models, Molecular Deep Learning Protein Conformation
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Folding and functions of knotted proteins.

Current opinion in structural biology Sep 29, 2023
Topologically knotted proteins have entangled structural elements within their native structures that cannot be disentangled simply by pulling from the N- and C-termini. Systematic surveys have identified different types of knotted protein structures...
Protein Conformation Artificial Intelligence Proteins Protein Folding
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Predicting pathogenic protein variants.

Science (New York, N.Y.) Sep 19, 2023
Machine-learning algorithm uses structure prediction to spot disease-causing mutations.
Mutant Proteins Machine Learning Algorithms Protein Conformation Sequence Analysis, DNA Disease Genetic Variation Mutation, Missense
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Protein remote homology detection and structural alignment using deep learning.

Nature biotechnology Sep 7, 2023
Exploiting sequence-structure-function relationships in biotechnology requires improved methods for aligning proteins that have low sequence similarity to previously annotated proteins. We develop two deep learning methods to address this gap, TM-Vec...
Algorithms Protein Conformation Sequence Alignment Sequence Analysis, Protein Deep Learning Proteins Computational Biology Databases, Protein
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Integrating deep learning, threading alignments, and a multi-MSA strategy for high-quality protein monomer and complex structure prediction in CASP15.

Proteins Aug 31, 2023
We report the results of the "UM-TBM" and "Zheng" groups in CASP15 for protein monomer and complex structure prediction. These prediction sets were obtained using the D-I-TASSER and DMFold-Multimer algorithms, respectively. For monomer structure pred...
Models, Molecular Sequence Alignment Software Protein Conformation Deep Learning Algorithms Proteins
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