Hotspots API: A Python Package for the Detection of Small Molecule Binding Hotspots and Application to Structure-Based Drug Design

• Published in: Journal of chemical information and modeling Vol. 60; no. 4; pp. 1911 - 1916
• Main Authors: Curran, Peter R, Radoux, Chris J, Smilova, Mihaela D, Sykes, Richard A, Higueruelo, Alicia P, Bradley, Anthony R, Marsden, Brian D, Spring, David R, Blundell, Tom L, Leach, Andrew R, Pitt, William R, Cole, Jason C
• Format: Journal Article
• Language: English
• Published: United States American Chemical Society 27.04.2020
• Subjects: Algorithms; Application programming interface; Applications programs; Binding; Data mining; Hydrogen bonds; Molecular docking; Molecular structure; Proteins; Toolkits; Workflow
• ISSN: 1549-9596; 1549-960X; 1549-960X
• DOI: 10.1021/acs.jcim.9b00996

Methods that survey protein surfaces for binding hotspots can help to evaluate target tractability and guide exploration of potential ligand binding regions. Fragment Hotspot Maps builds upon interaction data mined from the CSD (Cambridge Structural Database) and exploits the idea of identifying hotspots using small chemical fragments, which is now widely used to design new drug leads. Prior to this publication, Fragment Hotspot Maps was only publicly available through a web application. To increase the accessibility of this algorithm we present the Hotspots API (application programming interface), a toolkit that offers programmatic access to the core Fragment Hotspot Maps algorithm, thereby facilitating the interpretation and application of the analysis. To demonstrate the package’s utility, we present a workflow which automatically derives protein hydrogen-bond constraints for molecular docking with GOLD. The Hotspots API is available from https://github.com/prcurran/hotspots under the MIT license and is dependent upon the commercial CSD Python API.