title: Homology model-guided 3D-QSAR studies of HIV-1 integrase inhibitors.
abstract: In the present study, we report the exploration of binding modes of potent HIV-1 integrase (IN) inhibitors MK-0518 (raltegravir) and GS-9137 (elvitegravir) as well as chalcone and related amide IN inhibitors we recently synthesized and the development of 3D-QSAR models for integrase inhibition. Homology models of DNA-bound HIV-1 IN were constructed on the basis of the X-ray crystal structure of the foamy virus IN-DNA complex (PDB ID: 3L2T ) and used for docking. The binding modes of raltegravir and elvitegravir in our homology models are in accordance with those in the foamy virus structure revealing interactions important for inhibitor-IN binding. To gain further insights into the structural requirements for IN inhibition, three-dimensional quantitative structure activity relationship (3D-QSAR) studies were conducted using raltegravir, elvitegravir, and their analogs; our synthesized 3-keto salicylic acid IN inhibitor series; as well as other structurally related HIV-1 IN inhibitors. In the first part of the study with 103 compounds, atom-fit alignments, I and II, and docking-based alignment, III, were used to develop 3D-QSAR models 1, 2, and 3, respectively, each comprising comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) 3D-QSARs. This initial analysis indicated that the docking-based (structure-based) model 3 performed better than the atom-fit (ligand-based) models 1 and 2, in terms of statistical significance and robustness. Thus, the docking-based alignment was then subsequently used with an expanded data set of 296 compounds for building a more comprehensive 3D-QSAR, model 4. Model 4 afforded good q² values of 0.70 and 0.75 for CoMFA and CoMSIA 3D-QSARs, respectively, and showed good predictive performance on an external validation test set of 59 compounds with predictive r² values up to 0.71. The HIV IN-DNA homology model of biological relevance and the comprehensive 3D-QSAR models developed in the present study provide insights and new predictive tools for structure-based design and optimization of IN inhibitors.
authors.affiliation: Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee Health Science Center, Memphis, Tennessee 38163, USA.
authors.forename: Horrick
authors.initials: H
authors.lastname: Sharma
authors.forename: Xiaolin
authors.initials: X
authors.lastname: Cheng
authors.forename: John K
authors.initials: JK
authors.lastname: Buolamwini
mesh_terms: D015195:Drug Design; D019427:HIV Integrase / Q000737:chemistry*; D019428:HIV Integrase Inhibitors / Q000737:chemistry*; D006801:Humans; D008958:Models, Molecular; D011485:Protein Binding; D054730:Protein Interaction Domains and Motifs; D011760:Pyrrolidinones; D021281:Quantitative Structure-Activity Relationship; D015363:Quinolones; D000068898:Raltegravir Potassium
chemical_list: D019428:HIV Integrase Inhibitors; D011760:Pyrrolidinones; D015363:Quinolones; D000068898:Raltegravir Potassium; C509700:elvitegravir; D019427:HIV Integrase