In Silico Rational Design and Virtual Screening of Bioactive Peptides Based on QSAR Modeling
Mehri Mahmoodi-Reihani, Fatemeh Abbasitabar, Vahid Zare-Shahabadi
Abstract
) values were 0.855, 0.936, and 0.642 and the root-mean-square errors (RMSEs) were 0.450, 0.149, and 0.461. Our results revealed that the new numerical descriptive vector can afford extensive characterization of peptide sequence so that it can be easily employed in peptide QSAR studies. Moreover, the proposed numerical descriptive vectors were able to determine hot spot residues in the peptides under study.
Topics & Concepts
Quantitative structure–activity relationshipPeptideIn silicoSequence (biology)Rational designChemistryPrincipal component analysisPeptide sequenceComputational biologyStereochemistryBiochemistryComputer scienceBiologyArtificial intelligenceGeneticsGeneProtein Hydrolysis and Bioactive PeptidesChemical Synthesis and AnalysisAntimicrobial Peptides and Activities