Exploring the Application of SiteMap and Site Finder for Focused Cryptic Pocket Identification

The characterization of cryptic pockets
has been elusive, despite
substantial efforts. Computational modeling approaches, such as molecular
dynamics (MD) simulations, can provide atomic-level details of binding
site motions and binding pathways. However, the time scale that MD
can achieve at a reasonable cost often limits its application for
cryptic pocket identification. Enhanced sampling techniques can improve
the efficiency of MD simulations by focused sampling of important
regions of the protein, but prior knowledge of the simulated system
is required to define the appropriate coordinates. In the case of
a novel, unknown cryptic pocket, such information is not available,
limiting the application of enhanced sampling techniques for cryptic
pocket identification. In this work, we explore the ability of SiteMap
and Site Finder, widely used commercial packages for pocket identification,
to detect focus points on the protein and further apply other advanced
computational methods. The information gained from this analysis enables
the use of computational modeling, including enhanced MD sampling
techniques, to explore potential cryptic binding pockets suggested
by SiteMap and Site Finder. Here, we examined SiteMap and Site Finder
results on 136 known cryptic pockets from a combination of the PocketMiner
dataset (a recently curated set of cryptic pockets), the Cryptosite
Set (a classic set of cryptic pockets), and Natural killer group 2D
(NKG2D, a protein target where a cryptic pocket is confirmed). Our
findings demonstrate the application of existing, well-studied tools
in efficiently mapping potential regions harboring cryptic pockets.