CICLOP: A Robust, Faster, and Accurate Computational Framework for Protein Inner Cavity Detection

Abstract

Internal cavities in proteins are of critical functional importance. They can serve as substrate/ligand binding sites, pave path for movement of bio-molecules 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. We have developed a novel method, CICLOP, that can accurately identify these regions at an atomic resolution. The method is able to accurately detect residues lining the inner cavity, the diameter and volume occupied by the cavity, as well as physicochemical 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. AvailabilityCICLOP is available at http://ciclop.raylab.iiitd.edu.in/. A compiled Linux executable can be downloaded from https://ciclop.raylab.iiitd.edu.in/standalone/