# Drug Discovery Strategies for Kallikrein-Related Peptidases

## TL;DR

This paper reviews modern drug discovery strategies for targeting kallikrein-related peptidases, which are linked to various diseases like cancer.

## Contribution

The paper provides an updated overview of innovative methods, including AI, for developing drugs targeting KLKs.

## Key findings

- Structure-based design and high-throughput screening are effective for finding KLK inhibitors.
- AI and in silico screening have accelerated drug discovery for KLK targets.
- Natural compounds and their derivatives remain a significant source of pharmaceuticals.

## Abstract

Kallikrein-related peptidases (KLKs) are hallmarks of higher vertebrates, in particular of mammals. While the 15 human KLKs occur in nearly all tissues and body fluids and participate in many physiological processes, they are also involved in severe diseases. Among them are prostate, ovarian and breast cancer, as well as inherited skin and neurological disorders. Thus, KLKs have become targets for inhibitory compounds in academic and commercial research. The most prominent clinical biomarker and anti-cancer target for various approaches is PSA/KLK3. Already in the distant past, natural crude extracts were the source of medicine, while purified natural compounds and their derivatives are still the basis of about 50% of all pharmaceuticals. Nevertheless, structure-based rational design and high-throughput screening of natural and synthetic compound libraries are highly effective approaches for discovering lead compounds in the development of new drugs. Recently, computer-aided virtual or in silico screening has become a rapid method for such discoveries when combined with in vitro assays using protein targets or tests in cell cultures. To date, the successful implementation of artificial intelligence (AI) in the biosciences has significantly contributed to drug discovery. Our review focuses on state-of-the-art strategies and techniques in the context of KLK targets.