6533b833fe1ef96bd129c44b

RESEARCH PRODUCT

A Multivariate Analysis of HIV-1 Protease Inhibitors and Resistance Induced by Mutation

Alessandra MontalbanoMarco TutoneGirolamo CirrincioneGaetano DattoloAnna Maria AlmericoPaola BarrajaAntonino LauriaPatrizia Diana

subject

STRUCTURE-BASED DESIGNMultivariate analysisGeneral Chemical Engineeringmedicine.medical_treatmentMutantComputational biologyLibrary and Information SciencesModels BiologicalStructure-Activity RelationshipHIV-1 proteaseMolecular descriptorDrug Resistance ViralmedicineHIV Protease InhibitorBIOLOGICAL EVALUATIONGeneticschemistry.chemical_classificationProteasebiologyWild typeBiological activityANTIVIRAL ACTIVITYGeneral ChemistryHIV Protease InhibitorsGeneral MedicineD-AMINO ACIDSIN-VITROComputer Science ApplicationsORALLY BIOAVAILABLE INHIBITOREnzymechemistryRAY CRYSTAL-STRUCTUREMultivariate AnalysisMutationHUMAN-IMMUNODEFICIENCY-VIRUSHIV-1biology.proteinTYPE-1 PROTEASEQUANTITATIVE STRUCTURESoftware

description

This paper describes the use of the multivariate statistical procedure principal component analysis as a tool to explore the inhibitory activity of classes of protease inhibitors (PIs) against HIV-1 viruses (wild type and more-frequent single mutants, V82A, V82F, and I84V) and against protease enzymes. The analysis of correlations between biological activity and molecular descriptors or similarity indexes allowed a reliable classification of the 51 derivatives considered in this study. The best results were obtained in the case of the I84V mutant for which a high number of predictions was achieved. On this basis, this statistical approach is proposed as a reliable method for the prediction of the activity of PIs, for which the data against mutant strains have not been reported.

yearjournalcountryeditionlanguage
2005-11-12
10.1021/ci050139zhttp://hdl.handle.net/10447/5793