Abstract
Molecular docking is commonly used for identification of drug candidates targeting a specified protein of known structure. With the increasing emphasis on drug repurposing over recent decades, molecular inverse docking has been widely applied to prediction of the potential protein targets of a specified molecule. In practice, inverse docking has many advantages, including early supervision of drugs’ side effects and toxicity. MDock developed from our laboratory is a protein–ligand docking software based on a knowledge-based scoring function and has numerous applications to lead identification. In addition to its computational efficiency on ensemble docking for multiple protein conformations, MDock is well suited for inverse docking. In this chapter, we focus on introducing the protocol of inverse docking with MDock. For academic users, the MDock package is freely available at http://zoulab.dalton.missouri.edu/mdock.htm.
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Acknowledgments
Support to XZ from OpenEye Scientific Software Inc. (Santa Fe, NM, http://www.eyesopen.com) is gratefully acknowledged. This work was supported by NIH grants R01GM109980 (PI: XZ), R35GM136409 (PI: XZ), R01HL126774 (PI: Jianmin Cui), and R01HL142301 (PI: Jonathan Silva) to XZ. The computations were performed on the high performance computing infrastructure supported by NSF CNS-1429294 (PI: Chi-Ren Shyu) and the HPC resources supported by the University of Missouri Bioinformatics Consortium (UMBC).
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Ma, Z., Zou, X. (2021). MDock: A Suite for Molecular Inverse Docking and Target Prediction. In: Ballante, F. (eds) Protein-Ligand Interactions and Drug Design. Methods in Molecular Biology, vol 2266. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1209-5_18
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DOI: https://doi.org/10.1007/978-1-0716-1209-5_18
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