Abstract
Protein–peptide interactions mediate a wide range of important cellular tasks. In silico prediction of protein–peptide complex structure is highly desirable for mechanistic investigation of these processes and for therapeutic design. Recently, we developed a docking-based method for predicting protein–peptide complex structures, which starts with the peptide sequence and globally docks the all-atom, flexible peptide onto the protein structure. The produced modes are then evaluated with a statistical potential-based scoring function. The method has been implemented into an online server, MDockPeP server, which is freely available at http://zougrouptoolkit.missouri.edu/mdockpep. The server can be used for protein–peptide complex structure prediction. The server can also be used for initial-stage sampling of the protein–peptide binding modes for computational-demanding simulation or docking methods.
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Acknowledgments
This work was supported by NIH R01GM109980 (PI: XZ), NIH R01HL126774, and NIH R01HL142301 (PI: Cui) 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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Xu, X., Zou, X. (2020). MDockPeP: A Web Server for Blind Prediction of Protein–Peptide Complex Structures. In: Kihara, D. (eds) Protein Structure Prediction. Methods in Molecular Biology, vol 2165. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-0708-4_15
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DOI: https://doi.org/10.1007/978-1-0716-0708-4_15
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