Review on molecular modelling studies of anti-cancer drugs

Kunal Raut , Tejas Ghige , Gautam Adhav , Shital Gadakh , Pallavi Gawate

Anticancer , Molecular Docking , Molecular Modeling ,QSAR Studies , 2D QSAR, 3D QSAR , Pharmacophore Modeling

Caner remains a serious threat to global public health, responsible for an estimated 1.5 million mortalities in 2021. While there are available therapeutics for this infection, slow-acting drugs, poor patient compliance, drug toxicity, and drug resistance require the discovery of novel anticancer drugs. Discovering new and more potent drugs that target novel cancer cell line, enzymes is an attractive strategy towards controlling the global cancer epidemic. There has been a need to develop drugs that are less toxic and do not provide resistance in the long run. Thus, this need-based development of anticancer drugs through the use of different molecule has gained its pace since last two decades and there has been a gush among the researchers to apply various approaches in designing anticancer molecules. More specifically, research is being targeted on the utilization of molecular modeling techniques for developing new anticancer agents specifically targeting various cancer cell lines, specific enzymes and tissues. Some of the important and conclusive findings using this approach have been presented in this report.

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"Review on molecular modelling studies of anti-cancer drugs", IJSDR - International Journal of Scientific Development and Research (www.IJSDR.org), ISSN:2455-2631, Vol.8, Issue 3, page no.1116 - 1124, March-2023, Available :https://ijsdr.org/papers/IJSDR2303185.pdf

Volume 8 Issue 3, March-2023

Pages : 1116 - 1124

Paper Reg. ID: IJSDR_204712

Published Paper Id: IJSDR2303185

Downloads: 000347277

Research Area: Pharmacy

Country: Ahmednagar, Maharashtra, India

Published Paper PDF: https://ijsdr.org/papers/IJSDR2303185

Published Paper URL: https://ijsdr.org/viewpaperforall?paper=IJSDR2303185

ISSN: 2455-2631 | IMPACT FACTOR: 9.15 Calculated By Google Scholar | ESTD YEAR: 2016

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 9.15 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Publisher: IJSDR(IJ Publication) Janvi Wave

This work is licensed under a Creative Commons Attribution 4.0 International License and The Open Definition