Validation of Formylchromane Derivatives as Protein Tyrosine Phosphatase 1B Inhibitors by Pharmacophore Modeling, Atom‐Based 3D‐QSAR and Docking Studies

Abstract

Formylchromane derivatives were reported to possess irreversible and selective inhibition on human protein tyrosine phosphatase 1B (PTP 1B). Inhibition of PTP 1B is a molecular level legitimate approach for the management of type 2 diabetes mellitus (T2DM). 3D-QSAR studies were performed on a series of formylchromane derivatives using partial least square (PLS) analysis for correlating molecular architecture of the analogs with their PTP 1B inhibitory activity. A five-point pharmacophore hypothesis with three hydrogen bond acceptors (A) and two aromatic rings (R) as pharmacophoric features was developed using phase module of Schrödinger suite. The hypothesis AAARR.160 was considered as best hypothesis in this study characterized by survival score (3.483), the best cross-validated r² (Q²) (0.774), regression coefficient (0.960), Pearson-R (0.891), and F value (100.3). The results of hypothesis AAARR.160 complimented very closely to interactions witnessed in active site of the ligand-bound complex. The molecular docking simulations into PTP 1B active site also highlighted that biphenyl moiety favorably interacted with amino acid residues lining the lipophilic pocket, and provided hydrophobic interactions with receptor active site. These observations might be useful for further development and optimization of new chemical entities as potential PTP 1B inhibitors prior to its synthesis.

In silico research to assist the investigation of carboxamide derivatives as potent TRPV1 antagonists

“…50 As a comparison, atom-based superimposition CoMSIA models obtain better statistical results than those obtained from the receptor-based superimposition. 50 As a comparison, atom-based superimposition CoMSIA models obtain better statistical results than those obtained from the receptor-based superimposition.…”

“…[27][28][29][30][31][32][33][34][35] The biological activities of these TRPV1 antagonists are expressed in IC 50 (nM) values, which were converted into log IC 50 (pIC 50 ) in order to make normal distribution of the biological data for use in 3D-QSAR studies. [27][28][29][30][31][32][33][34][35] The biological activities of these TRPV1 antagonists are expressed in IC 50 (nM) values, which were converted into log IC 50 (pIC 50 ) in order to make normal distribution of the biological data for use in 3D-QSAR studies.…”

“…[27][28][29][30][31][32][33][34][35] The biological activities of these TRPV1 antagonists are expressed in IC 50 (nM) values, which were converted into log IC 50 (pIC 50 ) in order to make normal distribution of the biological data for use in 3D-QSAR studies. The selection of the test set was made based on the fact that they can appropriately represent the structural diversity of the whole data set and cover the range of pIC 50 values. The data set of 236 compounds as TRPV1 antagonists was divided into a training set and a test set by using random and SOM splitting methods.…”

“…The results from the CoMSIA analysis are given in In addition, the graph of actual activity versus predicted pIC 50 of the training and test sets is illustrated in Fig. The purpose of this study is also to determine whether the random division method leads to more predictive models when compared with the SOM division approach.…”

Biological evaluation of 2,3-dioxoindolin-N-phenylacetamide derivatives as potent CDC25B and PTP1B phosphatase inhibitors

“…PTP1B is also as key player in cancer serving as both tumor promoter and tumor suppressor depending on the cellular context. (Shi et al, 2008;Barr, 2010;Feldhammer et al, 2013;Malla, Kumar, Kumar, 2013;Reddy et al, 2014).…”