AIMC Topic: Binding Sites

Clear Filters Showing 331 to 340 of 500 articles

In silico identification of milk antihypertensive di- and tripeptides involved in angiotensin I-converting enzyme inhibitory activity.

Nutrition research (New York, N.Y.) Jul 28, 2017
Identification of bioactive milk peptides could improve food technology through improved selection of food supplements with a focus on antihypertensive properties. We hypothesized that angiotensin I-converting enzyme (ACE) inhibitory activities of mi...
Hydrophobic and Hydrophilic Interactions Expert Systems Catalytic Domain Oligopeptides Models, Molecular Peptide Fragments Dipeptides Peptidyl-Dipeptidase A Proteolysis Binding Sites Milk Proteins Angiotensin-Converting Enzyme Inhibitors Quantitative Structure-Activity Relationship Protein Conformation Hydrogen Bonding Cattle Computational Biology Humans Dietary Supplements Animals Antihypertensive Agents Molecular Docking Simulation
View on PubMed DOI

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...
Peptides Protein Binding Computational Biology Databases, Protein Humans Neural Networks, Computer Machine Learning Epitopes Histocompatibility Antigens Class II Ligands Binding Sites Protein Interaction Domains and Motifs Antibodies, Monoclonal Structure-Activity Relationship Mutation
View on PubMed DOI

Editorial-Sequences and topology.

Current opinion in structural biology Jun 4, 2017
Protein Interaction Mapping Protein Multimerization Protein Interaction Domains and Motifs Protein Conformation, alpha-Helical Proteins Binding Sites Thermodynamics Protein Conformation, beta-Strand Humans Machine Learning Animals Molecular Docking Simulation Protein Binding Computational Biology
View on PubMed DOI

TIGERi: modeling and visualizing the responses to perturbation of a transcription factor network.

BMC bioinformatics May 31, 2017
BACKGROUND: Transcription factor (TF) networks play a key role in controlling the transfer of genetic information from gene to mRNA. Much progress has been made on understanding and reverse-engineering TF network topologies using a range of experimen...
Machine Learning Animals Transcriptome Mice, Knockout Gene Regulatory Networks Binding Sites Mice Mitogen-Activated Protein Kinase 14 Transcription Factors
View on PubMed DOI

pDHS-SVM: A prediction method for plant DNase I hypersensitive sites based on support vector machine.

Journal of theoretical biology May 26, 2017
DNase I hypersensitive sites (DHSs) are accessible chromatin regions hypersensitive to cleavages by DNase I endonucleases. DHSs are indicative of cis-regulatory DNA elements (CREs), all of which play important roles in global gene expression regulati...
Support Vector Machine Oryza Binding Sites Genome, Plant Arabidopsis Algorithms Regulatory Sequences, Nucleic Acid Deoxyribonuclease I Dinucleotide Repeats
View on PubMed DOI

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...
Binding Sites Computational Biology Proteins Surface Properties Protein Conformation Molecular Docking Simulation Deep Learning Protein Binding
View on PubMed DOI

Discriminating between HuR and TTP binding sites using the k-spectrum kernel method.

PloS one Mar 23, 2017
BACKGROUND: The RNA binding proteins (RBPs) human antigen R (HuR) and Tristetraprolin (TTP) are known to exhibit competitive binding but have opposing effects on the bound messenger RNA (mRNA). How cells discriminate between the two proteins is an in...
Catalytic Domain Humans Binding Sites Models, Theoretical ELAV-Like Protein 1 Support Vector Machine Tristetraprolin
View on PubMed DOI

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...
Epitope Mapping Humans Protein Interaction Domains and Motifs Protein Binding Epitopes, B-Lymphocyte Supervised Machine Learning Models, Statistical Protein Conformation, alpha-Helical Antigens B-Lymphocytes Protein Conformation, beta-Strand Binding Sites Antigen-Antibody Complex
View on PubMed DOI

Active learning for computational chemogenomics.

Future medicinal chemistry Mar 6, 2017
AIM: Computational chemogenomics models the compound-protein interaction space, typically for drug discovery, where existing methods predominantly either incorporate increasing numbers of bioactivity samples or focus on specific subfamilies of protei...
Models, Chemical Ligands Databases, Chemical Binding Sites Drug Discovery Genomics Computational Biology Proteins Machine Learning Computer Simulation
View on PubMed DOI

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...
RNA Binding Sites Nucleotide Motifs Neural Networks, Computer Machine Learning Protein Binding Algorithms RNA-Binding Proteins Sequence Analysis, RNA Data Mining
View on PubMed DOI
Popular Topics
Recent Journals