A group center overlap based approach for “3D QSAR” studies on TIBO derivatives

Abstract

Current challenges in drug designing and lead optimization has reached a bottle neck where the main onus lies on rigorous validation to afford robust and predictive models. In the present study, we have suggested that predictive structure-activity relationship (SAR) models based on robust statistical analyses can serve as effective screening tools for large volume of compounds present either in chemical databases or in virtual libraries. 3D descriptors derived from the similarity-based alignment of molecules with respect to group center overlap from each individual template point and other "alignment averaged," but significant descriptors (ClogP, molar refractivity, connolly accessible area) were used to generate QSAR models. The results indicated that the artificial neural network method (r(2) = 0.902) proved to be superior to the multiple linear regression method (r(2) = 0.810). Cross validation of the models with an external set was reasonably satisfactory. Screening PubChem compound database based on the models obtained, yielded 14 newer modified compounds belonging to the TIBO class of inhibitors, as well as, two novel scaffolds, with enhanced binding efficacy as hits. These hits may be targeted toward potent lead-optimization and help in designing and synthesizing new compounds with potential therapeutic utility.

In silico de novo design of novel NNRTIs: a bio-molecular modelling approach

“…7a shows the snapshot of the overall superimposition of compound no. 47 and the virtually designed compounds (54)(55)(56)(57)(58)(59). 7b shows the a The compounds whose activity is reported in approximate terms.…”

“…The three substituents R and X are attached to the pyrimidinone ring while R 0 is attached to the bridging CH group. 54 These templates basically accounts for vital contribution of the pharmacophores in the structural alignment of the ligand within the NNIBP. [43][44][45][46] The 3-dimensional RT complex-DABO crystal structure analysis has provided newer dimensions to interpretation of the drug-receptor interaction prole, and this has certainly aided in substantiating the SAR analyses for enhanced structural renement.…”

“…53 It is reported that docking templates can be very useful if 3D structural conformation of a ligand is evident. 54 These templates basically accounts for vital contribution of the pharmacophores in the structural alignment of the ligand within the NNIBP. These pharmacophore based templates assist in extracting requisite information based on similarity overlap for each individual template point.…”

Design of novel leads: ligand based computational modeling studies on non-nucleoside reverse transcriptase inhibitors (NNRTIs) of HIV-1

“…28 Docking templates can be implemented if 3D conformation of a ligand is known. 40 The template groups can be located as spheres, distinctly colored for different template groups. These templates signify crucial contribution of the chemical entities to the binding of the ligand in the binding site.…”

Computational modeling studies on anti-HIV-1 non-nucleoside reverse transcriptase inhibition by dihydroalkoxybenzyloxopyrimidines analogues: an electrotopological atomistic approach

“…[18] Since then three more NNRTIs-nevirapine, delavirdine and efavirenz have been approved for the treatment of HIV-1 and a few more are in clinical development, including rilpivirine, etravirine and dapivirine [19]. Till date various molecular modelling studies have been performed using QSAR [20], QSPR [21], Simple docking [22] and Template docking [23] on some NNRTIs.…”