Cosolvent Analysis Toolkit (CAT): a robust hotspot identification platform for cosolvent simulations of proteins to expand the druggable proteome.

Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE

Original Publication: London : Nature Publishing Group, copyright 2011-

Ligands* ; Molecular Dynamics Simulation* ; Proteome* ; Software*; Macromolecular Substances/*chemistry ; Solvents/*chemistry; 2-Propanol/chemistry ; Acetamides/chemistry ; Acetanilides/chemistry ; Algorithms ; Benzene/chemistry ; Binding Sites ; Cluster Analysis ; Humans ; Imidazoles/chemistry ; Protein Domains ; Proteins/chemistry ; Receptors, Androgen/chemistry

Cosolvent Molecular Dynamics (MD) simulations are increasingly popular techniques developed for prediction and characterization 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 in the size of the potentially 'druggable' human proteome.

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0 (Acetamides)
0 (Acetanilides)
0 (Imidazoles)
0 (Ligands)
0 (Macromolecular Substances)
0 (Proteins)
0 (Proteome)
0 (Receptors, Androgen)
0 (Solvents)
7GBN705NH1 (imidazole)
8XOE1JSO29 (acetamide)
J64922108F (Benzene)
ND2M416302 (2-Propanol)
SP86R356CC (acetanilide)

Date Created: 20191215 Date Completed: 20201204 Latest Revision: 20210110

20250114

PMC6910964

10.1038/s41598-019-55394-2

31836830