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PRR11 is a cell cycle regulator involved in pathogenesis of cancer. Therapeutically it has been identified as target to inhibit cancer growth. In this study, we employed in silico strategies for determining 3D structure of PRR11 and identification of lead molecules. Molecular modelling of PRR11 was carried out with the help of @TOME2, modeller 9.10 and ModLoop, further structure refinement conceded with SAVES server. ZINC database was virtually screened against reference marine natural compound and docking simulations were performed in AutoDock Vina. Pharmacokinetic properties of leads have been analysed in DataWarrior. Collectively, the results revealed that the 3D structure of target was successfully build with refinement of 30 loops, the reliable structure showed that 83.87% amino acid residues present in allowed regions of Ramachandran plot, Errat overall quality factor was 83.807, passed in Prove and more than 65% amino acids have scored >=0.2 in the 3D/1D plot of PRR11. Based on small molecule screening of ZINC database against PRR11 with resulted pharmacokinetic descriptors, 5 lead molecules (28863059, 79642438, 27766155, 27855322 and 28365298) have predicted as PRR11 inhibitors, which are very prominent in binding energy values, ADME and adverse effects (MTIR) calculations than reference marine natural compound. ZINC database has been given a choice to purchase lead molecules for further evaluations in in vitro/in vivo studies; it could be an opportunity to further prove of this in silico predictions.

indian journal of pharmaceutical education

Identification of Anticancer Lead Molecules against PRR11 Protein Target with Combination of Protein Modelling Through Threading Approach, Structure Based Chemical Screening of ZINC Database and Pharmacokinetic Properties