AIMC Topic: Structural Homology, Protein

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Uncovering new families and folds in the natural protein universe.

Nature Sep 13, 2023
We are now entering a new era in protein sequence and structure annotation, with hundreds of millions of predicted protein structures made available through the AlphaFold database. These models cover nearly all proteins that are known, including thos...
Amino Acid Sequence Molecular Sequence Annotation Protein Folding Structural Homology, Protein Deep Learning Proteins Databases, Protein Internet
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Simultaneous prediction of antibody backbone and side-chain conformations with deep learning.

PloS one Jun 15, 2022
Antibody engineering is becoming increasingly popular in medicine for the development of diagnostics and immunotherapies. Antibody function relies largely on the recognition and binding of antigenic epitopes via the loops in the complementarity deter...
Deep Learning Protein Conformation Antigen-Antibody Complex Structural Homology, Protein
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When homologous sequences meet structural decoys: Accurate contact prediction by tFold in CASP14-(tFold for CASP14 contact prediction).

Proteins Sep 23, 2021
In this paper, we report our tFold framework's performance on the inter-residue contact prediction task in the 14th Critical Assessment of protein Structure Prediction (CASP14). Our tFold framework seamlessly combines both homologous sequences and st...
Models, Molecular Protein Folding Sequence Analysis, Protein Structural Homology, Protein Neural Networks, Computer Software Reproducibility of Results Computational Biology Proteins
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Protein structure search to support the development of protein structure prediction methods.

Proteins Feb 2, 2021
Protein structure prediction is a long-standing unsolved problem in molecular biology that has seen renewed interest with the recent success of deep learning with AlphaFold at CASP13. While developing and evaluating protein structure prediction metho...
Structural Homology, Protein Protein Conformation, alpha-Helical Protein Conformation, beta-Strand Proteins Benchmarking Sequence Alignment Amino Acid Motifs Humans Research Design Deep Learning
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Deep Learning Based Drug Screening for Novel Coronavirus 2019-nCov.

Interdisciplinary sciences, computational life sciences Jun 1, 2020
A novel coronavirus, called 2019-nCoV, was recently found in Wuhan, Hubei Province of China, and now is spreading across China and other parts of the world. Although there are some drugs to treat 2019-nCoV, there is no proper scientific evidence abou...
Coronavirus Infections Ligands Catalytic Domain Oligopeptides Models, Molecular Molecular Dynamics Simulation Drug Evaluation, Preclinical Amino Acid Sequence Databases, Pharmaceutical Structural Homology, Protein Betacoronavirus Pneumonia, Viral Viral Nonstructural Proteins Databases, Nucleic Acid Sequence Alignment Cysteine Endopeptidases Humans Pandemics COVID-19 SARS-CoV-2 Drug Design Deep Learning User-Computer Interface Antiviral Agents Coronavirus 3C Proteases
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Energy-based graph convolutional networks for scoring protein docking models.

Proteins Mar 16, 2020
Structural information about protein-protein interactions, often missing at the interactome scale, is important for mechanistic understanding of cells and rational discovery of therapeutics. Protein docking provides a computational alternative for su...
Protein Interaction Domains and Motifs Deep Learning Structural Homology, Protein Computer Graphics Protein Binding Protein Conformation, alpha-Helical Software Protein Interaction Mapping Protein Conformation, beta-Strand Proteins Research Design Protein Multimerization Benchmarking Peptides Amino Acid Sequence Molecular Docking Simulation Ligands Humans Binding Sites Thermodynamics
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Recent developments in deep learning applied to protein structure prediction.

Proteins Oct 14, 2019
Although many structural bioinformatics tools have been using neural network models for a long time, deep neural network (DNN) models have attracted considerable interest in recent years. Methods employing DNNs have had a significant impact in recent...
Neural Networks, Computer Deep Learning Computational Biology Proteins Models, Molecular Protein Conformation Structural Homology, Protein
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Gene ontology improves template selection in comparative protein docking.

Proteins Dec 27, 2018
Structural characterization of protein-protein interactions is essential for our ability to study life processes at the molecular level. Computational modeling of protein complexes (protein docking) is important as the source of their structure and a...
Gene Ontology Binding Sites Protein Interaction Mapping Structural Homology, Protein Proteins Databases, Protein Models, Molecular Protein Conformation Molecular Docking Simulation Protein Interaction Maps Humans Protein Binding Software Computational Biology
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A machine learning approach for ranking clusters of docked protein-protein complexes by pairwise cluster comparison.

Proteins Jan 20, 2017
Reliable identification of near-native poses of docked protein-protein complexes is still an unsolved problem. The intrinsic heterogeneity of protein-protein interactions is challenging for traditional biophysical or knowledge based potentials and th...
Protein Binding Computational Biology Cluster Analysis Proteins Protein Interaction Mapping Machine Learning Benchmarking Structural Homology, Protein Software Protein Conformation Research Design Binding Sites Molecular Docking Simulation Thermodynamics
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Predicting protein conformational changes for unbound and homology docking: learning from intrinsic and induced flexibility.

Proteins Dec 5, 2016
Predicting protein conformational changes from unbound structures or even homology models to bound structures remains a critical challenge for protein docking. Here we present a study directly addressing the challenge by reducing the dimensionality a...
Proteins Molecular Docking Simulation Machine Learning Benchmarking Binding Sites Software Protein Binding Protein Conformation Thermodynamics Research Design Computational Biology Dimensional Measurement Accuracy Protein Multimerization Models, Statistical Structural Homology, Protein
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