Robust Modeling and Scaffold Hopping: Case Study Based on HIV Reverse Transcriptase Inhibitors Type-1 Data.
Med Chem 2015;
12:513-26. [PMID:
26434799 DOI:
10.2174/1573406411666151005110141]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/08/2015] [Revised: 10/02/2015] [Accepted: 10/02/2015] [Indexed: 11/22/2022]
Abstract
BACKGROUND
Human immunodeficiency virus type 1 (HIV-1) is the causative agent of AIDS occurs across mucosal surfaces or by direct inoculation.
OBJECTIVE
The objective of this study was to consider chemically diverse scaffold sets of HIV-1 Reverse Transcriptase Inhibitors (HIV-1 RTI) subjected to ideal oriented QSAR with large descriptor space.
METHOD
We generated a four-parameter QSAR model based on 111 data points, which provided an optimum prediction of HIV-1 RTI for overall 367 experimentally measured compounds.
RESULTS
The robustness of the model is demonstrated by its statistical validation (Ntraining = 111, R2 = 0.85, Q2lmo = 0.84) and by the prediction of HIV-1 inhibition activity for experimentally measured compounds.
CONCLUSION
Finally, 5 novel hit compounds were designed in silico by using a virtual screening approach. The new hits met all the pharmacophore constraints and predicted pIC50 values within the binding ability of HIV-1 RT protein targets.
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