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Current Signal Transduction Therapy

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ISSN (Print): 1574-3624
ISSN (Online): 2212-389X

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Research Article

An Identification of RET Inhibitor: A Computational Study

Author(s): Anil Verma and Pankaj Wadhwa*

Volume 18, Issue 2, 2023

Published on: 29 August, 2023

Article ID: e170823219883 Pages: 14

DOI: 10.2174/1574362418666230817100406

Price: $65

Abstract

Introduction: RET (Rearranged during transcription) kinase is one of the key targets for anticancer drug development. Understanding the real mechanism of pharmacological action is aided by the protein-ligand interaction. The purpose of this study is to find the most effective RET inhibitors.

Methods: Firstly, through a literature survey, we understood that tetrazole is useful nuclei to provide anticancer activity. Hence, a molecule was drawn containing tetrazole ring using Chemdraw 16.0. This drawn compound was used to determine further ligands employing Zincpharmer. Then, the 3D energy minimized structure of proposed ligands and positive control (selpercatinib and pralsetinib) were drawn using Chem3D. Further, docking was performed for all the ligands with phosphorylated RET kinase (PDB ID - 2IVU) using trial version of Molegro virtual docker 7.0.

Results: Determined ligands were docked with the help of Molegro virtual Docker (MVD) 7.0 employing RET kinase (2ivu) as protein.

Conclusion: Top 10 compounds were selected and their drug-like properties along with their oral bioavailability were also determined. ZINC12180698, ZINC12180696, ZINC09616526, ZINC12180701, ZINC09616182, ZINC09616145, ZINC17052231, ZINC17052262, ZINC12180700, and ZINC0961 6518 were among the top ten compounds that showed the strongest affinity for the target for RETmediated cancer in this study.

Graphical Abstract

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