QSAR rationales for the dipeptidyl peptidase-4 (DPP-4) inhibitors: The imidazolopyrimidine amides
Department of Chemistry, Government College, Bundi-323 001 (Rajasthan), India.
Research Article
GSC Biological and Pharmaceutical Sciences, 2020, 11(03), 130-144.
Article DOI: 10.30574/gscbps.2020.11.3.0169
Publication history:
Received on 09 June 2020; revised on 18 June 2020; accepted on 19 June 2020
Abstract:
The DPP4 inhibition activity of imidazolopyrimidine amides has been quantitatively analyzed in terms of chemometric descriptors. The statistically validated QSAR models provided rationales to explain the inhibition activity of these congeners. The descriptors identified through CP-MLR analysis have highlighted the role of mean electrotopological state (Ms), number of double bonds in molecular structure (nDB), 2D Petitijean shape index (PJI2), Moran autocorrelation of lag-2/weighted by atomic polarizabilities (MATS2p), Moran autocorrelation of lag-6 and lowest eigenvalue n.5 of Burden matrix /weighted by atomic Sanderson electronegativities (MATS6e and BELe5), lowest eigenvalue n.3 and highest eigenvalue n.1 of Burden matrix/weighted by atomic van der Waals volumes (BELv3 and BEHv1). In addition to these 2nd order mean Galvez topological charge index (JGI2), number of ring tertiary C(sp3) (nCrHR) and R--CR--X type structural fragments (C-028) have also shown prevalence to model the inhibitory activity.
From statistically validated models, positive contribution of descriptors Ms, PJI2, JGI2, MATS2p, BELe5, BELv3 and BEHv1 suggested that higher values of these are conducive in improving the DPP4 inhibition activity. On the other hand, negative contribution of descriptors nDB, C-028, nCrHR and MATS6e advocated that absence of number of double bonds (nDB), R--CR--X type structural fragment (C-028), number of ring tertiary C(sp3) (nCrHR) and lower value of descriptor MATS6e would be advantageous. PLS analysis has confirmed the dominance of the CP‐MLR identified descriptors and applicability domain analysis revealed the acceptable predictability of suggested models. All the compounds are within the applicability domain of the proposed models and were evaluated correctly.
Keywords:
Quantitative structure-activity relationship (QSAR); DPP-4 inhibitors; Combinatorial protocol in multiple linear regression (CP-MLR) analysis; Chemometric descriptors; Imidazolopyrimidine amides.
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