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Template-Based Modeling of Protein Complexes Using the PPI3D Web Server

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Protein Structure Prediction

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2165))

Abstract

There is a large gap between the numbers of known protein–protein interactions and the corresponding experimentally solved structures of protein complexes. Fortunately, this gap can be in part bridged by computational structure modeling methods. Currently, template-based modeling is the most accurate means to predict both individual protein structures and protein complexes. One of the major issues in template-based modeling is to identify homologous structures that could be utilized as templates. To simplify this task, we have developed the PPI3D web server. The server is not only able to search for homologous protein complexes, but also provides means to analyze identified interactions and to model protein complexes. In recent CASP and CAPRI experiments, PPI3D proved to be a useful tool for homology modeling of multimeric proteins. In this chapter, we provide a brief description of the PPI3D web server capabilities and how to use the server for modeling of protein complexes.

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Acknowledgments

This work was supported by the Research Council of Lithuania [S-MIP-17-60].

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Authors and Affiliations

  1. Institute of Biotechnology, Life Sciences Center, Vilnius University, Vilnius, Lithuania

    Justas Dapkūnas & Česlovas Venclovas

Authors
  1. Justas Dapkūnas
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  2. Česlovas Venclovas
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Correspondence to Česlovas Venclovas .

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Editors and Affiliations

  1. Department of Computer Science, Purdue University, West Lafayette, IN, USA

    Daisuke Kihara

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Dapkūnas, J., Venclovas, Č. (2020). Template-Based Modeling of Protein Complexes Using the PPI3D Web Server. 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_8

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  • DOI: https://doi.org/10.1007/978-1-0716-0708-4_8

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-0707-7

  • Online ISBN: 978-1-0716-0708-4

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