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Better Partitions of Protein Graphs for Subsystem Quantum Chemistry

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Experimental Algorithms (SEA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9685))

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Abstract

Determining the interaction strength between proteins and small molecules is key to analyzing their biological function. Quantum-mechanical calculations such as Density Functional Theory (DFT) give accurate and theoretically well-founded results. With common implementations the running time of DFT calculations increases quadratically with molecule size. Thus, numerous subsystem-based approaches have been developed to accelerate quantum-chemical calculations. These approaches partition the protein into different fragments, which are treated separately. Interactions between different fragments are approximated and introduce inaccuracies in the calculated interaction energies.

To minimize these inaccuracies, we represent the amino acids and their interactions as a weighted graph in order to apply graph partitioning. None of the existing graph partitioning work can be directly used, though, due to the unique constraints in partitioning such protein graphs. We therefore present and evaluate several algorithms, partially building upon established concepts, but adapted to handle the new constraints. For the special case of partitioning a protein along the main chain, we also present an efficient dynamic programming algorithm that yields provably optimal results. In the general scenario our algorithms usually improve the previous approach significantly and take at most a few seconds.

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Notes

  1. 1.

    https://algohub.iti.kit.edu/parco/NetworKit/NetworKit-chemfork/.

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Authors and Affiliations

  1. Institute of Theoretical Informatics Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany

    Moritz von Looz & Henning Meyerhenke

  2. Institute of Physical and Theoretical Chemistry, TU Braunschweig, Braunschweig, Germany

    Mario Wolter & Christoph R. Jacob

Authors
  1. Moritz von Looz
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  2. Mario Wolter
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  3. Christoph R. Jacob
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  4. Henning Meyerhenke
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Corresponding author

Correspondence to Moritz von Looz .

Editor information

Editors and Affiliations

  1. Amazon.com, Inc., Palo Alto, California, USA

    Andrew V. Goldberg

  2. Russian Academy of Sciences, St. Petersburg, Russia

    Alexander S. Kulikov

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von Looz, M., Wolter, M., Jacob, C.R., Meyerhenke, H. (2016). Better Partitions of Protein Graphs for Subsystem Quantum Chemistry. In: Goldberg, A., Kulikov, A. (eds) Experimental Algorithms. SEA 2016. Lecture Notes in Computer Science(), vol 9685. Springer, Cham. https://doi.org/10.1007/978-3-319-38851-9_24

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  • DOI: https://doi.org/10.1007/978-3-319-38851-9_24

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-38850-2

  • Online ISBN: 978-3-319-38851-9

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