Discovering Anti-Cancer Drugs via Computational Methods
Wenqiang Cui, Adnane Aouidate, Shouguo Wang, Qiuliyang Yu, Yan-Hua Li, Shuguang Yuan
Abstract
Developing a new drug is a complex, dangerous, expensive and time-consuming venture. The traditional drug development process is estimated to take 12 years on average and more than 2.5 billion USD to complete. Reducing the cost and speeding up the development of new drugs have become a challenging and urgent problem facing the pharmaceutical industry. Computer-aided drug discovery (CADD) combined with new experimental technologies promises to make finding new drugs faster, cheaper and more effective thanks to the reduced cost of computational methods and the increased availability of three-dimensional structural information. The application of computational tools to drug discovery, including anticancer therapies, has grown steadily for the past years, which has had a significant impact on the design of anticancer drugs and drug candidates over the years and has provided fruitful insights into the field of cancer. In this article, our objective is to provide an overview on the different subareas of the drug discovery process with a focus on anticancer drugs.