CICLOP: a robust and accurate computational framework for protein inner cavity detection

Abstract

Motivation: Internal cavities in proteins are of critical functional importance. They can serve as substrate/ligand-binding sites, pave path for movement of biomolecules and even mediate structural conformations occurring between domain interfaces during structural transitions. Yet, there is a paucity of computational tools that can accurately and reliably characterize the inner cavities of the proteins, a prerequisite for elucidating their functions. Results: We have developed a novel method, CICLOP, that can accurately identify these regions at an atomistic resolution. The method is able to accurately detect residues lining the inner cavity, the diameter and volume occupied by the cavity, as well as physico-chemical properties of residues lining the cavity, such as their hydrophobicity and secondary structure distribution in detail. Additionally, our method also provides an option for computing conservation scores for the residues detected on the inside, allowing for a thorough functional characterization of the cavity.