AIMC Topic: Peptides

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An Artificial Neural Network Based Analysis of Factors Controlling Particle Size in a Virgin Coconut Oil-Based Nanoemulsion System Containing Copper Peptide.

PloS one Jul 6, 2016
A predictive model of a virgin coconut oil (VCO) nanoemulsion system for the topical delivery of copper peptide (an anti-aging compound) was developed using an artificial neural network (ANN) to investigate the factors that influence particle size. F...
Humans Neural Networks, Computer Software Algorithms Copper Emulsions Coconut Oil Polysaccharides, Bacterial Nanoparticles Polysorbates Peptides Plant Oils Oxidative Stress Particle Size
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Protease Inhibitors in View of Peptide Substrate Databases.

Journal of chemical information and modeling Jun 9, 2016
Protease substrate profiling has nowadays almost become a routine task for experimentalists, and the knowledge on protease peptide substrates is easily accessible via the MEROPS database. We present a shape-based virtual screening workflow using vROC...
Models, Molecular Drug Evaluation, Preclinical Ligands Peptides User-Computer Interface Small Molecule Libraries Peptide Hydrolases Databases, Pharmaceutical Protein Conformation Substrate Specificity Protease Inhibitors Machine Learning
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Machine learning approaches for discrimination of Extracellular Matrix proteins using hybrid feature space.

Journal of theoretical biology May 11, 2016
Extracellular Matrix (ECM) proteins are the vital type of proteins that are secreted by resident cells. ECM proteins perform several significant functions including adhesion, differentiation, cell migration and proliferation. In addition, ECM protein...
Algorithms Peptides Databases, Protein Amino Acids Machine Learning Extracellular Matrix Proteins
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A Web Server and Mobile App for Computing Hemolytic Potency of Peptides.

Scientific reports Mar 8, 2016
Numerous therapeutic peptides do not enter the clinical trials just because of their high hemolytic activity. Recently, we developed a database, Hemolytik, for maintaining experimentally validated hemolytic and non-hemolytic peptides. The present stu...
Humans Support Vector Machine Databases, Protein Internet Computer Simulation Peptides Mobile Applications Sequence Analysis, Protein Amino Acid Sequence Hemolytic Agents Hemolysis
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Sequence-based prediction of protein-peptide binding sites using support vector machine.

Journal of computational chemistry Feb 2, 2016
Protein-peptide interactions are essential for all cellular processes including DNA repair, replication, gene-expression, and metabolism. As most protein-peptide interactions are uncharacterized, it is cost effective to investigate them computational...
Proteins Binding Sites Peptides Support Vector Machine
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Exploiting non-linear relationships between retention time and molecular structure of peptides originating from proteomes and comparing three multivariate approaches.

Journal of pharmaceutical and biomedical analysis Jan 27, 2016
Peptides' retention time prediction is gaining increasing popularity in liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics. This is a promising approach for improving successful proteome mapping, useful both in identification ...
Models, Chemical Bacterial Proteins Tandem Mass Spectrometry HeLa Cells Quantitative Structure-Activity Relationship Protein Conformation Proteome Bacillus subtilis Chromatography, Liquid Artificial Intelligence Peptides Humans
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A two-layered machine learning method to identify protein O-GlcNAcylation sites with O-GlcNAc transferase substrate motifs.

BMC bioinformatics Dec 9, 2015
Protein O-GlcNAcylation, involving the β-attachment of single N-acetylglucosamine (GlcNAc) to the hydroxyl group of serine or threonine residues, is an O-linked glycosylation catalyzed by O-GlcNAc transferase (OGT). Molecular level investigation of t...
Internet Substrate Specificity Amino Acid Motifs Algorithms Acetylglucosamine Glycosylation Machine Learning N-Acetylglucosaminyltransferases Peptides Proteins Support Vector Machine User-Computer Interface Mass Spectrometry
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An adaptive classification model for peptide identification.

BMC genomics Nov 10, 2015
BACKGROUND: Peptide sequence assignment is the central task in protein identification with MS/MS-based strategies. Although a number of post-database search algorithms for filtering target peptide spectrum matches (PSMs) have been developed, the disc...
Peptides Humans Computational Biology Algorithms Support Vector Machine
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l2 Multiple Kernel Fuzzy SVM-Based Data Fusion for Improving Peptide Identification.

IEEE/ACM transactions on computational biology and bioinformatics Sep 18, 2015
SEQUEST is a database-searching engine, which calculates the correlation score between observed spectrum and theoretical spectrum deduced from protein sequences stored in a flat text file, even though it is not a relational and object-oriental reposi...
Fuzzy Logic Databases, Protein Peptides Software Proteomics Algorithms Mass Spectrometry
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Prediction of Nucleotide Binding Peptides Using Star Graph Topological Indices.

Molecular informatics Aug 5, 2015
The nucleotide binding proteins are involved in many important cellular processes, such as transmission of genetic information or energy transfer and storage. Therefore, the screening of new peptides for this biological function is an important resea...
Models, Molecular Machine Learning Nucleotides Peptides
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