Exploring molecular shape analysis of styrylquinoline derivatives as HIV-1 integrase inhibitors.
HIV-1 integrase inhibitory activity data of styrylquinoline derivatives have been subjected to 3D-QSAR study by molecular shape analysis (MSA) technique using Cerius(2) version 4.8 software (Accelrys). For the selection of test set compounds, initially a QSAR analysis was done based on topological and structural descriptors and K-means clustering technique was used to classify the entire data set (n=36). Clusters were formed from the factor scores of the whole data set comprising of topological and structural descriptors without the biological activity, and based on the clusters, the data set was divided into training and test sets (n=26 and n=10, respectively) so that all clusters are properly represented in both training and test sets. In the molecular shape analysis, the major steps were (1) generation of conformers and energy minimization; (2) hypothesizing an active conformer (global minimum of the most active compound); (3) selecting a candidate shape reference compound (based on active conformation); (4) performing pair-wise molecular superimposition using maximum common subgroup [MCSG] method; (5) measuring molecular shape commonality using MSA descriptors; (6) determination of other molecular features by calculating spatial and conformational parameters; (7) selection of conformers; (8) generation of QSAR equations by standard statistical techniques. The best model obtained from stepwise regression and GFA techniques shows 51.6% predicted variance (leave-one-out) and 57.3% explained variance. In case of FA-PLS regression, the best relation shows 54.0% predicted variance and 57.9% explained variance. The R(2)(pred) and R(2)(test) values for the GFA derived model are 0.611 and 0.664, respectively, while the best FA-PLS model has R(2)(pred) and R(2)(test) values of 0.602 and 0.656, respectively. These models show the importance of Jurs descriptors (total polar surface area, relative polar surface area, relative hydrophobic surface area, relative positive charge), fraction area of the molecular shadow in the XZ plane (ShadowXZfrac), common overlap steric volume and the ratio of common overlap steric volume to volume of individual molecules. Statistically reliable MSA models obtained from this study suggest that this technique could be useful to design potent HIV-1 integrase inhibitors.
Leonard
J Thomas
JT
Drug Theoretics and Cheminformatics Lab, Division of Medicinal and Pharmaceutical Chemistry, Department of Pharmaceutical Technology, Jadavpur University, Raja S C Mullick Road, Kolkata, West Bengal 700 032, India.
Roy
Kunal
K
D005163:Factor Analysis, Statistical; D019427:HIV Integrase / Q000378:metabolism*; D019428:HIV Integrase Inhibitors / Q000737:chemistry* / Q000378:metabolism / Q000494:pharmacology*; D006801:Humans; D016018:Least-Squares Analysis; D008958:Models, Molecular; D008968:Molecular Conformation; D021281:Quantitative Structure-Activity Relationship; D011804:Quinolines / Q000737:chemistry* / Q000378:metabolism / Q000494:pharmacology*; D012984:Software
D019428:HIV Integrase Inhibitors; D011804:Quinolines; C481600:styrylquinoline; D019427:HIV Integrase; C514801:p31 integrase protein, Human immunodeficiency virus 1