Robust Modeling and Scaffold Hopping: Case Study Based on HIV Reverse Transcriptase Inhibitors Type-1 Data

Title:Robust Modeling and Scaffold Hopping: Case Study Based on HIV Reverse Transcriptase Inhibitors Type-1 Data

Volume: 12 Issue: 6

Author(s): Girinath G. Pillai, Laznier Mederos, Chandramukhi S. Panda, Amber Gronski, Peeter Burk, Charles D. Hall, Alan R. Katritzky, Kaido Tämm and Mati Karelson

Affiliation:

Keywords: Global QSAR, applicability domain, diverse scaffolds, field points, scaffold hopping.

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 (N_training = 111, R² = 0.85, Q²_lmo = 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.

Cite this article as:

Pillai G. Girinath, Mederos Laznier, Panda S. Chandramukhi, Gronski Amber, Burk Peeter, Hall D. Charles, Katritzky R. Alan, Tämm Kaido and Karelson Mati, Robust Modeling and Scaffold Hopping: Case Study Based on HIV Reverse Transcriptase Inhibitors Type-1 Data, Medicinal Chemistry 2016; 12 (6) . https://dx.doi.org/10.2174/1573406411666151005110141