STRUCTURE PREDICTION AND IN SILICO DESIGNING OF DRUGS AGAINST KALLIKREIN PROTEIN 12


Manish Devgan

Abstract


Objective: Human Kallikrein protein 12 (hK12) might serve as a novel diagnostic and prognostic biomarker, as well as a potential therapeutic target, in gastric cancer.

Methods: In this work, a theoretical model of hK12 receptor protein was generated using the concepts of homology modeling and loop modeling. The resulting model was validated with Ramachandran plot analysis. The ligands generated with the help of Drug bank were docked against hK12 receptor protein using AutoDock Vina in PyRx 0.8. The structure of ligand DB04786 (Suramin), with least binding energy, was varied by using ACD/ChemSketch 8.0 and the docking was done for the resulting 16 new ligands.

Results: The results indicated that the ligand10 bears the minimum binding energy (-12.3 Kcal/mol) with the target protein and thus the prospects of binding are high. The results also clearly demonstrated that the in silico molecular docking studies of selected ligands, i.e., suramin, ligands 5, 6, 10 and 16 with hK12 protein exhibited favourable binding interactions and warranted.

Conclusion: Further studies needed for the development of potent inhibitors for the overexpression of hK12 protein making the management of gastric cancer more efficient.


Keywords


Gastric cancer, Kallikrein protein, Docking, Homology modelling, Human kallikrein 12

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About this article

Title

STRUCTURE PREDICTION AND IN SILICO DESIGNING OF DRUGS AGAINST KALLIKREIN PROTEIN 12

Keywords

Gastric cancer, Kallikrein protein, Docking, Homology modelling, Human kallikrein 12

DOI

10.22159/ijcpr.2017v9i2.17387

Date

01-03-2017

Additional Links

Manuscript Submission

Journal

International Journal of Current Pharmaceutical Research
Vol 9, Issue 2, 2017 Page: 64-69

Online ISSN

0975-7066

Statistics

103 Views | 58 Downloads

Authors & Affiliations

Manish Devgan
Faculty of Pharmacy, R. P. Educational Trust Group of Institutions, Bastara, Karnal 132001, Haryana, India


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