Comparative study of innovative computational methods for identifying cryptic pockets.

Abstract

Cryptic pockets are crucial targets in drug discovery, yet their transient and concealed nature makes experimental detection challenging. Computational methods have proven highly effective for identifying and characterizing these elusive sites. Here, we systematically summarize and analyze state-of-the-art computational methods for cryptic pocket detection. Specifically, we examine their nature, mechanisms of formation, and functions, and review computational methods for cryptic pocket detection. To illustrate their practical utility, we present a case study of TEM-1 β-lactamase. This review aims to guide researchers in harnessing these computational tools to uncover cryptic pockets and promote their application in drug discovery.