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High-Performance Hybrid Computing for Bioinformatic Analysis of Protein Superfamilies

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Supercomputing (RuSCDays 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1129))

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Abstract

Construction of a multiple alignment of proteins that implement different functions within a common structural fold of a superfamily is a valuable tool in bioinformatics, but represents a challenge. The process can be seen as a pipeline of independent sequential steps of an equivalent computational complexity each performed by a different set of algorithms. In this work the overall productivity of the corresponding Mustguseal protocol was significantly improved by selecting an appropriate optimization strategy for each step of the pipeline. This HPC-installation was used to collect and superimpose within 12 h a representative set of 299’976 sequences and structures of the fold-type I PLP-dependent enzymes what appears to be the largest alignment of a protein superfamily ever constructed. The use of hybrid acceleration strategies provided a routine access to a sequence/structure comparison of evolutionarily related proteins at a scale that would previously have been intractable to study the structure-function relationship and solve practically relevant problems, thus promoting the value of bioinformatics and HPC in protein engineering and drug discovery.

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Acknowledgements

This work was supported by the Russian Foundation for Basic Research grant #18-29-13060 and carried out using the equipment of the shared research facilities of HPC computing resources at Lomonosov Moscow State University supported by the project RFMEFI62117X0011 [47].

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Authors and Affiliations

  1. Lomonosov Moscow State University, Moscow, Russia

    Dmitry Suplatov, Yana Sharapova, Maxim Shegay, Nina Popova, Vladimir Voevodin & Vytas Švedas

  2. Institute of Organic Chemistry, Graz University of Technology, Graz, Austria

    Kateryna Fesko

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  1. Dmitry Suplatov
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  2. Yana Sharapova
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  3. Maxim Shegay
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  4. Nina Popova
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  7. Vytas Švedas
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Correspondence to Dmitry Suplatov .

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  1. Research Computing Center, Moscow State University, Moscow, Russia

    Vladimir Voevodin

  2. Research Computing Center, Moscow State University, Moscow, Russia

    Sergey Sobolev

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Suplatov, D. et al. (2019). High-Performance Hybrid Computing for Bioinformatic Analysis of Protein Superfamilies. In: Voevodin, V., Sobolev, S. (eds) Supercomputing. RuSCDays 2019. Communications in Computer and Information Science, vol 1129. Springer, Cham. https://doi.org/10.1007/978-3-030-36592-9_21

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  • DOI: https://doi.org/10.1007/978-3-030-36592-9_21

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