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CovalentDock: Automated covalent docking with parameterized covalent linkage energy estimation and molecular geometry constraints

Authors

  • Xuchang Ouyang,

    1. BioInformatics Research Centre, School of Computer Engineering, Nanyang Technological University, Singapore 639798
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    • These authors contributed equally to this work.

  • Shuo Zhou,

    1. State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing, China 100191
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    • These authors contributed equally to this work.

  • Chinh Tran To Su,

    1. BioInformatics Research Centre, School of Computer Engineering, Nanyang Technological University, Singapore 639798
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  • Zemei Ge,

    1. State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing, China 100191
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  • Runtao Li,

    Corresponding author
    1. State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing, China 100191
    • State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing, China 100191
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  • Chee Keong Kwoh

    Corresponding author
    1. BioInformatics Research Centre, School of Computer Engineering, Nanyang Technological University, Singapore 639798
    • BioInformatics Research Centre, School of Computer Engineering, Nanyang Technological University, Singapore 639798
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Abstract

Covalent linkage formation is a very important mechanism for many covalent drugs to work. However, partly due to the limitations of proper computational tools for covalent docking, most covalent drugs are not discovered systematically. In this article, we present a new covalent docking package, the CovalentDock, built on the top of the source code of Autodock. We developed an empirical model of free energy change estimation for covalent linkage formation, which is compatible with existing scoring functions used in docking, while handling the molecular geometry constrains of the covalent linkage with special atom types and directional grid maps. Integrated preparation scripts are also written for the automation of the whole covalent docking workflow. The result tested on existing crystal structures with covalent linkage shows that CovalentDock can reproduce the native covalent complexes with significant improved accuracy when compared with the default covalent docking method in Autodock. Experiments also suggest that CovalentDock is capable of covalent virtual screening with satisfactory enrichment performance. In addition, the investigation on the results also shows that the chirality and target selectivity along with the molecular geometry constrains are well preserved by CovalentDock, showing great capability of this method in the application for covalent drug discovery. © 2012 Wiley Periodicals, Inc.

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