Abstract
The study of the 3D structural details of protein interactions is essential to understand biomolecular functions at the molecular level. In this context, the limited availability of experimental structures of protein–protein complexes at atomic resolution is propelling the development of computational docking methods that aim to complement the current structural coverage of protein interactions. One of these docking approaches is pyDock, which uses van der Waals, electrostatics, and desolvation energy to score docking poses generated by a variety of sampling methods, typically FTDock or ZDOCK. The method has shown a consistently good prediction performance in community-wide assessment experiments like CAPRI or CASP, and has provided biological insights and insightful interpretation of experiments by modeling many biomolecular interactions of biomedical and biotechnological interest. Here, we describe in detail how to perform structural modeling of protein assemblies with pyDock, and the application of its modules to different biomolecular recognition phenomena, such as modeling of binding mode, interface, and hot-spot prediction, use of restraints based on experimental data, inclusion of low-resolution structural data, binding affinity estimation, or modeling of homo- and hetero-oligomeric assemblies.
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Acknowledgments
This work was supported by the Spanish Ministry of Science (grant BIO2016-79930-R).
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Rosell, M., Rodríguez-Lumbreras, L.A., Fernández-Recio, J. (2020). Modeling of Protein Complexes and Molecular Assemblies with pyDock. 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_10
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DOI: https://doi.org/10.1007/978-1-0716-0708-4_10
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