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Tuning interval Branch-and-Prune for protein structure determination

Author

Listed:
  • Bradley Worley

    (CNRS UMR3528, Centre de Bioinformatique, Biostatistique et Biologie Intégrative, CNRS USR3756, Institut Pasteu)

  • Florent Delhommel

    (Institut Pasteur)

  • Florence Cordier

    (Institut Pasteur)

  • Thérèse E. Malliavin

    (CNRS UMR3528, Centre de Bioinformatique, Biostatistique et Biologie Intégrative, CNRS USR3756, Institut Pasteu)

  • Benjamin Bardiaux

    (CNRS UMR3528, Centre de Bioinformatique, Biostatistique et Biologie Intégrative, CNRS USR3756, Institut Pasteu)

  • Nicolas Wolff

    (Institut Pasteur)

  • Michael Nilges

    (CNRS UMR3528, Centre de Bioinformatique, Biostatistique et Biologie Intégrative, CNRS USR3756, Institut Pasteu)

  • Carlile Lavor

    (University of Campinas)

  • Leo Liberti

    (LIX, École Polytechnique)

Abstract

The interval Branch and Prune (iBP) algorithm for obtaining solutions to the interval Discretizable Molecular Distance Geometry Problem (iDMDGP) has proven itself as a powerful method for molecular structure determination. However, substantial obstacles still must be overcome before iBP may be employed as a tractable general-purpose alternative to existing structure determination algorithms. This work introduces an iterative variant of the iBP algorithm that leverages existing knowledge of protein structures in order to reduce the size of the effective search space by many orders of magnitude. These improvements are included in a newly released implementation of the iBP software that aims to provide a solid platform for both research and application of the iDMDGP.

Suggested Citation

  • Bradley Worley & Florent Delhommel & Florence Cordier & Thérèse E. Malliavin & Benjamin Bardiaux & Nicolas Wolff & Michael Nilges & Carlile Lavor & Leo Liberti, 2018. "Tuning interval Branch-and-Prune for protein structure determination," Journal of Global Optimization, Springer, vol. 72(1), pages 109-127, September.
    • Handle: RePEc:spr:jglopt:v:72:y:2018:i:1:d:10.1007_s10898-018-0635-0
    DOI: 10.1007/s10898-018-0635-0
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    References listed on IDEAS

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    1. Douglas S. Gonçalves & Antonio Mucherino & Carlile Lavor & Leo Liberti, 2017. "Recent advances on the interval distance geometry problem," Journal of Global Optimization, Springer, vol. 69(3), pages 525-545, November.
    2. Virginia Costa & Antonio Mucherino & Carlile Lavor & Andrea Cassioli & Luiz Carvalho & Nelson Maculan, 2014. "Discretization orders for protein side chains," Journal of Global Optimization, Springer, vol. 60(2), pages 333-349, October.
    3. Carlile Lavor & Leo Liberti & Antonio Mucherino, 2013. "The interval Branch-and-Prune algorithm for the discretizable molecular distance geometry problem with inexact distances," Journal of Global Optimization, Springer, vol. 56(3), pages 855-871, July.
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    Cited by:

    1. Lavor, Carlile & Souza, Michael & Carvalho, Luiz M. & Gonçalves, Douglas S. & Mucherino, Antonio, 2021. "Improving the sampling process in the interval Branch-and-Prune algorithm for the discretizable molecular distance geometry problem," Applied Mathematics and Computation, Elsevier, vol. 389(C).
    2. Phil Duxbury & Carlile Lavor & Leo Liberti & Luiz Leduino Salles-Neto, 2022. "Unassigned distance geometry and molecular conformation problems," Journal of Global Optimization, Springer, vol. 83(1), pages 73-82, May.
    3. Simon J. L. Billinge & Phillip M. Duxbury & Douglas S. Gonçalves & Carlile Lavor & Antonio Mucherino, 2018. "Recent results on assigned and unassigned distance geometry with applications to protein molecules and nanostructures," Annals of Operations Research, Springer, vol. 271(1), pages 161-203, December.

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