Computational Approaches to Identify Potential Inhibitors of Fibroblast Activation Protein for Cancer Therapeutics

Abstract

Cancer is the leading cause of mortality worldwide, accounting for nearly 10 million deaths in 2020, according to the World Health Organisation. Breast cancer, lung cancer, colon and rectal cancer, prostate cancer, non-melanoma skin cancer, and stomach cancer were the most prevalent new cancer cases in 2020. Many target cells, receptors, enzymes, and molecular markers are being identified for pharmacological targets that can suppress tumour growth, and one of them is fibroblast activation protein (FAP), which is overexpressed in many forms of cancer and hence can be an effective drug target. FAP has its resemblance to other family member proteins such as DPPIV and PREP. Therefore, it is challenging to find inhibitors for FAP in order to lessen the unwanted side effects. This study is primarily concerned with identifying inhibitors that inhibit FAP.