Targeting breast cancer: Unveiling FN3K enzyme inhibitors via structure-based virtual screening and molecular dynamic simulation

Registration ID: IJNRD_223638

Published ID: IJNRD2406239

DOI: http://doi.one/10.1729/Journal.39997

Erica Alves , Gurupadayya Bannimath , Prabitha Prabhakaran , Saravanan Parameswaran , Abhimanyu Awasthi

Nuclear factor erythroid-2-related factor-2 (Nrf2), Fructosamine-3-kinase (FN3K), Structure based virtual screening (SBVS), molecular dynamics (MD).

Breast cancer is a complex and multidimensional illness that significantly impacts women's health worldwide. Challenges associated with chemotherapy due to drug resistance and toxicity have led to the rise in the complexity of cancers globally by 20 million cases being reported by IARC 2022 among which breast cancer accounts for 11.6% of the reported cancer cases (GLOBACON 2022). A major development has been the discovery of oncoproteins that regulate treatment resistance in addition to controlling the proliferation and spread of cancer cells. Research has demonstrated that Nuclear factor erythroid-2-related factor-2 (Nrf2), a transcription factor, has an oncogenic function in the process of carcinogenesis. However, because of its significance in cell development and proliferation, this is linked to rising levels of oxidative stress. Thus, a feasible strategy would be to inhibit an oncoprotein that controls Nrf2 function and is overexpressed in cancer cells. Sanghvi et al. (2019) have reported that Fructosamine-3-kinase enzyme (FN3K) drives oncogenesis and promotes deglycation by phosphorylating vital amino acids like arginine and lysine inside Nrf2. Using structure-based virtual screening (SBVS) and molecular dynamics simulation (MD) research, the study aimed to discover prospective FN3K inhibitors by investigating a sizable dataset of FDA-approved kinase inhibitors in addition to anti-cancer drugs of both natural and synthetic origin. Through a meticulous approach, the structure of the FN3K protein was crafted using Swiss Modeler for homology modeling. Following this, a comprehensive screening of 330 molecules was conducted using AutoDock Vina, leveraging structure-based techniques. From this extensive screening, eight promising compounds emerged as potential hits, exhibiting favorable ADMET characteristics. This marks a significant step forward in the quest to identify effective inhibitors for FN3K enzyme. Re-docking with Schrödinger suite's 2023-3 Maestro version 13.7 verified the docking findings of the eight hit compounds. Based on the docking score, a single molecule was ultimately determined to be a possible lead chemical for the study. MD-Simulation investigations during a 200-ns period were used to demonstrate the complex's stability.

Published Paper   E-Certificate

Erica Alves, Gurupadayya Bannimath, Prabitha Prabhakaran , Saravanan Parameswaran, & Abhimanyu Awasthi (June-2024). Targeting breast cancer: Unveiling FN3K enzyme inhibitors via structure-based virtual screening and molecular dynamic simulation. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(6), c356-c384. http://doi.one/10.1729/Journal.39997

Volume 9 Issue 6, June-2024

Pages : c356-c384

Paper Reg. ID: IJNRD_223638

Published Paper Id: IJNRD2406239

Downloads: 000121981

Research Area: Computer Aided Process Design 

Country: Loutulim, Goa, India

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Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2406239

Crossref DOI: http://doi.one/10.1729/Journal.39997

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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