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Cosolvent Analysis Toolkit (CAT): A Robust Hotspot Identification Platform for Cosolvent Simulations of Proteins to Expand the Druggable Proteome

submitted on 11.02.2019 and posted on 12.02.2019 by Francesc Sabanés Zariquiey, Joao Victor de Souza Cunha, Agnieszka K. Bronowska
Cosolvent Molecular Dynamics (MD) simulations are increasingly popular techniques developed for prediction and characterisation of allosteric and cryptic binding sites, which can be rendered “druggable” by small molecule ligands. Despite their conceptual simplicity and effectiveness, the analysis of cosolvent MD trajectories relies on pocket volume data, which requires a high level of manual investigation and may introduce a bias. In this work, we present CAT (Cosolvent Analysis Toolkit): an open-source, freely accessible analytical tool, suitable for automated analysis of cosolvent MD trajectories. CAT is compatible with commonly used molecular graphics software packages such as UCSF Chimera and VMD. Using a novel hybrid empirical force field scoring function, CAT accurately ranks the dynamic interactions between the macromolecular target and cosolvent molecules. To benchmark, CAT was used for three validated protein targets with allosteric and orthosteric binding sites, using five chemically distinct cosolvent molecules. For all systems, CAT has accurately identified all known sites. CAT can thus assist in computational studies aiming at identification of protein “hotspots” in a wide range of systems. As an easy-to-use computational tool, we expect that CAT will contribute to an increase of the size of the potentially ‘druggable’ human proteome.


Email Address of Submitting Author


Newcastle University


United Kingdom

ORCID For Submitting Author


Declaration of Conflict of Interest

No conflict of Interest

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