AIMC Topic: Protein Multimerization

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Machine Learning Enables Selection of Epistatic Enzyme Mutants for Stability Against Unfolding and Detrimental Aggregation.

Chembiochem : a European journal of chemical biology Nov 17, 2020
Machine learning (ML) has pervaded most areas of protein engineering, including stability and stereoselectivity. Using limonene epoxide hydrolase as the model enzyme and innov'SAR as the ML platform, comprising a digital signal process, we achieved h...
Limonene Protein Engineering Protein Folding Protein Multimerization Epoxide Hydrolases Machine Learning Mutation Molecular Dynamics Simulation Rhodococcus
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A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers.

Molecules (Basel, Switzerland) Sep 23, 2020
Study of interface residue pairs is important for understanding the interactions between monomers inside a trimer protein-protein complex. We developed a two-layer support vector machine (SVM) ensemble-classifier that considers physicochemical and ge...
Computational Biology Support Vector Machine Proteins Protein Multimerization Protein Structure, Quaternary
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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 Structural Homology, Protein Protein Conformation, alpha-Helical Protein Conformation, beta-Strand Proteins Benchmarking Amino Acid Sequence Ligands Binding Sites Thermodynamics Computer Graphics Protein Interaction Mapping Protein Multimerization Research Design Humans Software Peptides Molecular Docking Simulation Deep Learning Protein Binding
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Integrated structural modeling and super-resolution imaging resolve GPCR oligomers.

Progress in molecular biology and translational science Dec 6, 2019
Formation of G protein-coupled receptors (GPCRs) dimers and higher order oligomers represents a key mechanism in pleiotropic signaling, yet how individual protomers function within oligomers remains poorly understood. For the Class A/rhodopsin subfam...
Software Algorithms Animals Humans Neural Networks, Computer Protein Binding Machine Learning Computational Biology Support Vector Machine Receptors, G-Protein-Coupled Mutation Molecular Dynamics Simulation Protein Multimerization Allosteric Site Ligands Fluorescence Resonance Energy Transfer Crystallography, X-Ray Protein Interaction Mapping Protein Structure, Secondary
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modeling of the cryptic E2∼ubiquitin-binding site of E6-associated protein (E6AP)/UBE3A reveals the mechanism of polyubiquitin chain assembly.

The Journal of biological chemistry Sep 18, 2017
To understand the mechanism for assembly of Lys-linked polyubiquitin degradation signals, we previously demonstrated that the E6AP/UBE3A ligase harbors two functionally distinct E2∼ubiquitin-binding sites: a high-affinity Site 1 required for E6AP Cys...
Ubiquitin-Conjugating Enzymes Amino Acid Substitution Recombinant Fusion Proteins Binding Sites Mutagenesis, Site-Directed Ubiquitin Ubiquitination Protein Multimerization Isoenzymes Point Mutation Expert Systems Biocatalysis Protein Conformation Cysteine Ubiquitin-Protein Ligases Cattle Computational Biology Models, Molecular Iodine Radioisotopes Humans Animals Molecular Docking Simulation
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Editorial-Sequences and topology.

Current opinion in structural biology Jun 4, 2017
Thermodynamics Protein Interaction Mapping Protein Multimerization Protein Interaction Domains and Motifs Protein Conformation, alpha-Helical Protein Conformation, beta-Strand Molecular Docking Simulation Protein Binding Computational Biology Proteins Binding Sites Humans Machine Learning Animals
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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...
Computational Biology Models, Statistical Proteins Benchmarking Protein Conformation Dimensional Measurement Accuracy Binding Sites Thermodynamics Protein Multimerization Machine Learning Software Research Design Molecular Docking Simulation Protein Binding Structural Homology, Protein
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GGIP: Structure and sequence-based GPCR-GPCR interaction pair predictor.

Proteins Jun 8, 2016
G Protein-Coupled Receptors (GPCRs) are important pharmaceutical targets. More than 30% of currently marketed pharmaceutical medicines target GPCRs. Numerous studies have reported that GPCRs function not only as monomers but also as homo- or hetero-d...
Humans Animals Databases, Protein Receptors, G-Protein-Coupled Area Under Curve ROC Curve Models, Molecular Amino Acid Sequence Protein Binding Mice Support Vector Machine Binding Sites Protein Structure, Secondary Protein Multimerization Protein Interaction Domains and Motifs
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idDock+: Integrating Machine Learning in Probabilistic Search for Protein-Protein Docking.

Journal of computational biology : a journal of computational molecular cell biology Jul 29, 2015
Predicting the three-dimensional native structures of protein dimers, a problem known as protein-protein docking, is key to understanding molecular interactions. Docking is a computationally challenging problem due to the diversity of interactions an...
Protein Conformation Binding Sites Protein Multimerization Protein Binding Computational Biology Proteins Ligands Machine Learning Algorithms Molecular Docking Simulation
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The ligand binding mechanism to purine nucleoside phosphorylase elucidated via molecular dynamics and machine learning.

Nature communications Jan 27, 2015
The study of biomolecular interactions between a drug and its biological target is of paramount importance for the design of novel bioactive compounds. In this paper, we report on the use of molecular dynamics (MD) simulations and machine learning to...
Ligands Pyrimidinones Thermodynamics Pyrrolidines Protein Multimerization Purine-Nucleoside Phosphorylase Protein Binding Humans Cluster Analysis Machine Learning Kinetics Algorithms Molecular Dynamics Simulation Time Factors
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