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TTClust: A Versatile Molecular Simulation Trajectory Clustering Program with Graphical Summaries

  • Thibault Tubiana*
    Thibault Tubiana
    Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, University Paris-Sud, Université Paris-Saclay, 91198 Gif sur Yvette cedex, France
    *E-mail: [email protected] (T.T.).
  • Jean-Charles Carvaillo
    Jean-Charles Carvaillo
    Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, University Paris-Sud, Université Paris-Saclay, 91198 Gif sur Yvette cedex, France
  • Yves Boulard
    Yves Boulard
    Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, University Paris-Sud, Université Paris-Saclay, 91198 Gif sur Yvette cedex, France
    More by Yves Boulard
  • , and 
  • Stéphane Bressanelli
    Stéphane Bressanelli
    Institute for Integrative Biology of the Cell (I2BC), CEA, CNRS, University Paris-Sud, Université Paris-Saclay, 91198 Gif sur Yvette cedex, France
Cite this: J. Chem. Inf. Model. 2018, 58, 11, 2178–2182
Publication Date (Web):October 17, 2018
https://doi.org/10.1021/acs.jcim.8b00512
Copyright © 2018 American Chemical Society

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    Abstract

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    It is extremely helpful to be able to partition the thousands of frames produced in molecular dynamics simulations into a limited number of most dissimilar conformations. While robust clustering algorithms are already available to do so, there is a distinct need for an easy-to-use clustering program with complete user control, taking as input a trajectory from any molecular dynamics (MD) package and outputting an intuitive display of results with plots allowing at-a-glance analysis. We present TTClust (for Trusty Trajectory Clustering), a python program that uses the MDTraj package to fill this need.

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