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, 9 (1), 19118

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

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

Francesc Sabanés Zariquiey et al. Sci Rep.

Abstract

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.

Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
Clustering scheme of CAT: A sphere is generated per residue, which encapsulates shells of interacting cosolvent molecules (yellow circular regions defined by the variable Rresidue). Afterwards, a secondary clustering region (blue shaded area, defined by the variable Rcluster) defines close side-chains centres of geometry, resulting in a series of representative clusters of interest.
Figure 2
Figure 2
Androgen receptor LBD hotspots found by CAT. Clusters have the following colors assigned: acetamide – blue, benzene – purple, acetanilide – orange, imidazole – yellow, and isopropanol – green. The crystallographic ligand is colored cyan. (a) Panoramic representation of LBD domain centered on the AF-2 site compromised around the H3 and the respective top cluster given by CAT; (b) Panoramic representation centered around the BF-3 region and the respective CAT clusters. Simulations with all 5 probes found the site with a high rank, as described in Table 1. For the second site, only acetamide and benzene show high ranks. (c) AF-2 site and its key residues; K720, V716 and H714, that form part of H3, are detected by simulations with all 5 fragments. (d) BF-3 and its key residues; simulations with acetamide detected N833 and N727 as key residues for the site, but with a lower ranking than the clusters found in AF-2 site.
Figure 3
Figure 3
PTP1B hotspots found by CAT. Clusters have the following colors assigned: acetamide – blue, benzene – purple, acetanilide – orange, imidazole – yellow, and isopropanol – green. The crystallographic ligand is colored cyan. (A) Panoramic view centered on the allosteric binding sites; (B) View centered on the orthosteric binding site. CAT performs well finding and scoring the binding site for PTP1B since 4 out of the 5 cosolvent molecules are able to interact with the site residues. Only isopropanol and benzene find the orthosteric binding site, and acetamide interacts with neighbor key residues. (C) BB allosteric binding site and its main residues; all cosolvent molecules but acetamide rank clusters in the allosteric binding site, principally isopropanol, which shows interactions with N193, F196 and F280. (D) 197 site recently identified by Keedy et al.. CAT maps the whole site, including K197.
Figure 4
Figure 4
HRas hotspots found by CAT. The clusters are colored as follows: acetamide – blue, benzene – purple, acetanilide – orange, imidazole – yellow, and isopropanol – green. The crystallographic fragment is colored cyan. (a) Panoramic view of the HRas and the highest-ranked cluster for each cosolvent molecule. (a) Depiction of Site 3, (b) Site 5, (c) Site 6 (d) Site 7 and (e) Site 8, Following the naming and numbering from Buhrman et al.. As shown, acetamide and benzene perform better than the other 3 cosolvent molecules, but the combination of the 5 different cosolvents are able to find most of the superficial binding sites and CAT score is able to find the interacting residues to different crystalized molecular fragments.
Figure 5
Figure 5
CDK2 Hotspots found by CAT. The clusters are colored as follows: acetamide – blue, benzene – purple, acetanilide – orange, imidazole – yellow, and isopropanol – green. The crystallographic fragment is colored cyan. (a) Panoramic view of the HRas and the highest ranked cluster for each cosolvent molecule. (a) Depiction of CDK2 and highest scored clusters, (b) Orthosteric site, (c) Site 1 (d) Site 2 (e) Site 3 (f) Site 4 (g) Site 5. As shown, acetamide and acetanilide perform better than the other 3 cosolvent molecules, given the nature of the experimental X-ray mapped crystallographic binding regions. Site 4 and 5 in specific shows high ranked clusters for these 2 probes, given by the high polarity of the site’s side chains.

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