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Evaluation of pyrrole-2,3-dicarboxylate derivatives: Synthesis, DFT analysis, molecular docking, virtual screening and in vitro anti-hepatic cancer study

Iqbal Azad, A. Jafri, T. Khan, Y. Akhter, M. Arshad, F. Hassan, N. Ahmad, AbdulR Khan et al.

Journal of Molecular Structure, 2019

29 citations

Abstract

Abstract Novel anti-hepatic carcinoma drugs are of great therapeutic significance in the treatment of different types of hepatic cancers. Since last decade, there has been a progressive improvement in computational drug designing strategies. Human topoisomerase-II (Topo-II) and human platelet derived growth factor receptor-α (PDGFR-α) have been identified as main enzymes involved in hepatic carcinoma. In the current work, we assessed novel pyrrole-2,3-dicarboxylate derivatives as potential anti-cancer agents using docking, virtual screening and experimental analyses. Pyrrole-2,3-dicarboxylate derivatives which we have evaluated in this study were synthesized and characterized by UV, IR, ESI-MS, 1H and 13C NMR spectroscopic techniques. Structural validation was done using quantum chemical calculations using Density Function Theory (DFT) employing B3LYP method and 6-311++G(d,p) basis set. Potential energy distribution (PED) for normal vibrational modes was computed by VEDA4. The HOMO and LUMO analysis was carried out to determine the charge transfer within the molecule. The synthesized compounds were tested in-silico and in-vitro for anti-cancer activity; Docking studies were performed against topo-II and PDGFR-α. By utilizing ligand based pharmacophore generation approach and virtual screening against control drugs (Doxorubicin Hydrochloride and Rituximab) fifty-one novel molecules have been proposed that displayed highest binding affinities, least binding energies and…

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Evidence Hub reads this as a simulation / modelling, done in computer models (in silico), not in people. Its evidence level is 5 of 5 (Very low · case / narrative / animal / in vitro / in silico). Case reports, narrative reviews, and animal, cell or computer-model studies give the weakest evidence for human health.

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