CP-MLR derived QSAR study on the PPARγ agonists: The benzylpyrazole acylsulfonamide derivatives
Department of Chemistry, Government College, Bundi-323 001 (Rajasthan), India.
Research Article
GSC Advanced Research and Reviews, 2020, 04(02), 009-022.
Article DOI: 10.30574/gscarr.2020.4.2.0061
Publication history:
Received on 15 July 2020; revised on 29 July 2020; accepted on 30 July 2020
Abstract:
The PPARγ transactivation activity of benzylpyrazole acylsulfonamide derivatives have been quantitatively analyzed in terms of 0D- to 2D-Dragon descriptors. This study has provided a rational approach for the development of titled derivatives as PPARγ agonists. The descriptors identified in CP-MLR analysis for the PPARγ transactivation activity have highlighted the role of atomic properties (mass, electronegativity, van der Waals volumes and polarizability) in terms of weighted 2D autocorrelations and BCUT descriptors and electronic content in terms of Galvez charge indices and maximal electrotopological positive variation (MAXDP). Additionally, Balaban’s U and centric indices (Uindex and BAC, respectively), Lopping centric index (Lop), topological distance between N and O atom and hydrophobicity accounting parameter MLOGP have also shown prevalence to optimize the PPARγ transactivation of titled compounds. PLS analysis has further confirmed the dominance of the CP‐MLR identified descriptors and applicability domain analysis revealed that the suggested model matches the high quality parameters with good fitting power and the capability of assessing external data and all of the compounds was within the applicability domain of the proposed model and were evaluated correctly.
Keywords:
QSAR; PPARg transactivation; Combinatorial protocol in multiple linear regression (CP-MLR) analysis; Dragon descriptors; Benzylpyrazole acylsulfonamides.
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Copyright © 2020 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0
