AI Medical Compendium Topic:
Protein Binding

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Machine learning reveals a non-canonical mode of peptide binding to MHC class II molecules.

Immunology Jun 19, 2017
MHC class II molecules play a fundamental role in the cellular immune system: they load short peptide fragments derived from extracellular proteins and present them on the cell surface. It is currently thought that the peptide binds lying more or les...
Computational Biology Databases, Protein Antibodies, Monoclonal Machine Learning Peptides Protein Binding Ligands Binding Sites Protein Interaction Domains and Motifs Histocompatibility Antigens Class II Structure-Activity Relationship Humans Mutation Neural Networks, Computer Epitopes
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Editorial-Sequences and topology.

Current opinion in structural biology Jun 4, 2017
Humans Machine Learning Animals Protein Interaction Mapping Proteins Protein Multimerization Binding Sites Protein Interaction Domains and Motifs Thermodynamics Molecular Docking Simulation Protein Binding Protein Conformation, alpha-Helical Computational Biology Protein Conformation, beta-Strand
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Protein-Protein Interaction Interface Residue Pair Prediction Based on Deep Learning Architecture.

IEEE/ACM transactions on computational biology and bioinformatics May 19, 2017
MOTIVATION: Proteins usually fulfill their biological functions by interacting with other proteins. Although some methods have been developed to predict the binding sites of a monomer protein, these are not sufficient for prediction of the interactio...
Deep Learning Protein Binding Computational Biology Molecular Docking Simulation Binding Sites Proteins Surface Properties Protein Conformation
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Predicting Protein-protein Association Rates using Coarse-grained Simulation and Machine Learning.

Scientific reports Apr 18, 2017
Protein-protein interactions dominate all major biological processes in living cells. We have developed a new Monte Carlo-based simulation algorithm to study the kinetic process of protein association. We tested our method on a previously used large ...
Models, Chemical Monte Carlo Method Multiprotein Complexes Machine Learning Protein Binding Predictive Value of Tests
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Structural and Sequence Similarity Makes a Significant Impact on Machine-Learning-Based Scoring Functions for Protein-Ligand Interactions.

Journal of chemical information and modeling Apr 5, 2017
The prediction of protein-ligand binding affinity has recently been improved remarkably by machine-learning-based scoring functions. For example, using a set of simple descriptors representing the atomic distance counts, the RF-Score improves the Pea...
Amino Acid Sequence Ligands Computational Biology Proteins Machine Learning Protein Binding
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Improving the accuracy of high-throughput protein-protein affinity prediction may require better training data.

BMC bioinformatics Mar 23, 2017
BACKGROUND: One goal of structural biology is to understand how a protein's 3-dimensional conformation determines its capacity to interact with potential ligands. In the case of small chemical ligands, deconstructing a static protein-ligand complex i...
Humans Machine Learning Models, Molecular Models, Statistical Data Accuracy Proteins Protein Conformation Animals Protein Binding
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Staged heterogeneity learning to identify conformational B-cell epitopes from antigen sequences.

BMC genomics Mar 14, 2017
BACKGROUND: The broad heterogeneity of antigen-antibody interactions brings tremendous challenges to the design of a widely applicable learning algorithm to identify conformational B-cell epitopes. Besides the intrinsic heterogeneity introduced by di...
Humans Protein Binding Epitope Mapping Supervised Machine Learning Models, Statistical Antigens B-Lymphocytes Epitopes, B-Lymphocyte Binding Sites Antigen-Antibody Complex Protein Conformation, alpha-Helical Protein Interaction Domains and Motifs Protein Conformation, beta-Strand
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Study of Structure-active Relationship for Inhibitors of HIV-1 Integrase LEDGF/p75 Interaction by Machine Learning Methods.

Molecular informatics Feb 28, 2017
HIV-1 integrase (IN) is a promising target for anti-AIDS therapy, and LEDGF/p75 is proved to enhance the HIV-1 integrase strand transfer activity in vitro. Blocking the interaction between IN and LEDGF/p75 is an effective way to inhibit HIV replicati...
Protein Binding Structure-Activity Relationship Humans Models, Molecular Computer Simulation Molecular Conformation Machine Learning Molecular Structure Reproducibility of Results Intercellular Signaling Peptides and Proteins HIV Integrase ROC Curve HIV Integrase Inhibitors
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RNA-protein binding motifs mining with a new hybrid deep learning based cross-domain knowledge integration approach.

BMC bioinformatics Feb 28, 2017
BACKGROUND: RNAs play key roles in cells through the interactions with proteins known as the RNA-binding proteins (RBP) and their binding motifs enable crucial understanding of the post-transcriptional regulation of RNAs. How the RBPs correctly recog...
Data Mining RNA Binding Sites Nucleotide Motifs Protein Binding Neural Networks, Computer RNA-Binding Proteins Machine Learning Sequence Analysis, RNA Algorithms
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A Hybrid Knowledge-Based and Empirical Scoring Function for Protein-Ligand Interaction: SMoG2016.

Journal of chemical information and modeling Feb 27, 2017
We present the third generation of our scoring function for the prediction of protein-ligand binding free energy. This function is now a hybrid between a knowledge-based potential and an empirical function. We constructed a diversified set of ∼1000 c...
Entropy Ligands Probability Protein Conformation Databases, Protein Protein Binding Models, Molecular Proteins Knowledge Bases
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