Quantitative Structure–Activity Relationship and Quantitative Structure–Pharmacokinetics Relationship of 1,4-Dihydropyridines and Pyridines as Multidrug Resistance Modulators
Autor: | Xiao-fei Zhou, Marilyn E. Morris, Robert A. Coburn, Qingxiang Shao |
---|---|
Rok vydání: | 2005 |
Předmět: |
Models
Molecular Dihydropyridines Quantitative structure–activity relationship Chemical Phenomena Molecular model Pyridines Stereochemistry Quantitative Structure-Activity Relationship Pharmaceutical Science DHPS Vinblastine Pharmacokinetics Molecular descriptor Linear regression Pharmacology (medical) ATP Binding Cassette Transporter Subfamily B Member 1 Pharmacology Chemistry Physical Chemistry Organic Chemistry Quantitative structure Calcium Channel Blockers Antineoplastic Agents Phytogenic Drug Resistance Multiple Multiple drug resistance Molecular Medicine Calcium Channels Algorithms Biotechnology |
Zdroj: | Pharmaceutical Research. 22:1989-1996 |
ISSN: | 1573-904X 0724-8741 |
DOI: | 10.1007/s11095-005-8112-0 |
Popis: | The aim of this study was to develop quantitative structure–activity/pharmacokinetic relationships (QSAR/QSPKR) for a series of synthesized 1,4-dihydropyridines (DHPs) and pyridines as P-glycoprotein (P-gp) inhibitors. Molecular descriptors of test compounds were generated by 3D molecular modeling using SYBYL and KowWin programs. Forward inclusion coupled with multiple linear regression (MLR) was used to derive a QSAR equation for Ca2+ channel binding. A multivariate statistical technique, partial least square (PLS) regression, was applied to derive a QSAR model for P-gp inhibition and QSPKR models. Cross-validation using the “leave-one-out” method was performed to evaluate the predictive performance of models. For Ca2+ channel binding, the MLR equation indicated a good correlation between observed and predicted values (R2 = 0.90), and cross-validation confirmed the predictive ability of the model (Q2 = 0.67). For P-gp reversal, the model obtained by PLS could account for most of the variation in P-gp inhibition (R2 = 0.76) with fair predictive performance (Q2 = 0.62). Nine structurally related 1,4-DHP drugs were used for QSPKR analysis. The models could explain the majority of the variation in clearance (R2 = 0.90), and cross-validation confirmed the prediction ability (Q2 = 0.69). QSAR/QSPKR models were developed, and the QSAR models were capable of identifying synthesized 1,4-DHPs and pyridines with potent P-gp inhibition and reduced Ca2+ channel binding. The QSPKR models provide insight into the contribution of electronic, steric, and lipophilic factors to the clearance of DHPs. |
Databáze: | OpenAIRE |
Externí odkaz: |