1College of Medical and Health Sciences, Liwa University, Abu Dhabi, United Arab Emirates
2Thumbay College of Management and AI in Healthcare, Gulf Medical University, Ajman, United Arab Emirates
3Department of Health Research Methods, Evidence and Impact, McMaster University, Hamilton, Canada
4Department of Medical and Surgical Nursing, College of Nursing, Princess Nourah Bint Abdulrahman University, Riyadh, 13412, Saudi Arabia
5College of Health Sciences, Dubai Medical University, Dubai, United Arab Emirates
6Director and HOD – Nephrology, Paras HMRI, Patna, India
7Head, Centre for Nanoscience and Nanotechnology, Aryabhatta Knowledge University, Patna, India
8Medical Student, College of Medicine, October 6 University, Egypt
*Corresponding Author E-mail: mjamali68@gmail.com
**********rakeshsinghpu@gmail.com
***********adham.elsonbaty@gmail.com
******belala@mcmaster.ca
*******malyami@pnu.edu.sa
********maxime.merheb@dmu.ae
*********shashigmc@yahoo.co.in
A new era in drug discovery must start. Almost all pharmaceutical development methods use computer-based data and findings. This article highlights advanced simulation techniques for drug development. By 2040, the worldwide cancer burden will reach 30 million new cases, with the highest growth in low—and middle-income nations. By 2040, cancer diagnoses are predicted to grow by 55 percent, reaching 6.23 million in the Americas. Kinetic profiles of ligand binding mechanisms and drug-target affinities must be investigated.
A systematic literature review was conducted using multiple academic and scientific databases, including ResearchGate, ScienceDirect, CORE Library, Google, Web of Science, Google Scholar, and Scientific Digital Library Online (SciELO). The search covered publications from August 2009 to August 2024 to ensure the inclusion of foundational and recent studies.
Plant-derived drugs include methyl transferase inhibitors, DNA damage inhibitors, HDAC inhibitors, and mitotic disruptors—the compounds’ anticancer effectiveness and clinical trial development. MTAs are currently used in cancer detection since they target specific driver genes or diagnostics. This method is constrained by the high gene alterations in multiple driving genes in each tumor. Digital drug assignment (DDA) method that prioritizes potential.
Computational drug discovery, Multi-target drug development, Cancer treatment, Natural compounds in drug discovery, Ligand binding kinetics, Computer-aided drug design (CADD)
