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

Author:

Garg Parth1,Sacher Sukriti1,  Mrinal1,  Atul2,Gautam Prutyay1,Ray Arjun1ORCID

Affiliation:

1. Department of Computational Biology, Indraprastha Institute of Information Technology , Delhi, India

2. Department of Computer Science and Engineering, Indraprastha Institute of Information Technology , Delhi, India

Abstract

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. Availability and implementation CICLOP is available at http://ciclop.raylab.iiitd.edu.in/. A compiled Linux executable can be downloaded from https://ciclop.raylab.iiitd.edu.in/standalone/. Supplementary information Supplementary data are available at Bioinformatics online.

Funder

University Grants Commision (UGC) funding agency

Initiation Research Grant by IIIT Delhi

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

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