Computer-aided Drug Discovery Approaches in the Identification of Anticancer Drugs from Natural Products: A Review

Overview

Journal Curr Comput Aided Drug Des

Publisher Bentham Science Publishers

Specialties Medical Informatics
Pharmacology

Date 2024 May 3

PMID 38698753

Authors

Muthiah Gnana Ruba Priya

Jessica Manisha

Lal Prasanth Mercy Lazar

Seema Singh Rathore

Viswas Raja Solomon

Affiliations

Soon will be listed here.

Abstract

Natural plant sources are essential in the development of several anticancer drugs, such as vincristine, vinblastine, vinorelbine, docetaxel, paclitaxel, camptothecin, etoposide, and teniposide. However, various chemotherapies fail due to adverse reactions, drug resistance, and target specificity. Researchers are now focusing on developing drugs that use natural compounds to overcome these issues. These drugs can affect multiple targets, have reduced adverse effects, and are effective against several cancer types. Developing a new drug is a highly complex, expensive, and time-consuming process. Traditional drug discovery methods take up to 15 years for a new medicine to enter the market and cost more than one billion USD. However, recent Computer Aided Drug Discovery (CADD) advancements have changed this situation. This paper aims to comprehensively describe the different CADD approaches in identifying anticancer drugs from natural products. Data from various sources, including Science Direct, Elsevier, NCBI, and Web of Science, are used in this review. techniques and optimization algorithms can provide versatile solutions in drug discovery ventures. The structure-based drug design technique is widely used to understand chemical constituents' molecular-level interactions and identify hit leads. This review will discuss the concept of CADD, tools, virtual screening in drug discovery, and the concept of natural products as anticancer therapies. Representative examples of molecules identified will also be provided.

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