Application of nonlinear dimensionality reduction to characterize the conformational landscape of small peptides

Authors

  • Hernán Stamati,

    1. Department of Computer Science, Rice University, Houston, Texas 77005
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  • Cecilia Clementi,

    Corresponding author
    1. Department of Chemistry, Rice University, Houston, Texas 77005
    2. Structural and Computational Biology and Molecular Biophysics, Baylor College of Medicine, Houston, Texas 77030
    • Department of Chemistry, Rice University, 6100 Main Street, MS-60, Houston, TX 77005
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  • Lydia E. Kavraki

    Corresponding author
    1. Department of Computer Science, Rice University, Houston, Texas 77005
    2. Structural and Computational Biology and Molecular Biophysics, Baylor College of Medicine, Houston, Texas 77030
    3. Department of Bioengineering, Rice University, Houston, Texas 77005
    • Department of Computer Science, Rice University, 6100 Main Street, MS-132, Houston, TX 77005
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Abstract

The automatic classification of the wealth of molecular configurations gathered in simulation in the form of a few coordinates that help to explain the main states and transitions of the system is a recurring problem in computational molecular biophysics. We use the recently proposed ScIMAP algorithm to automatically extract motion parameters from simulation data. The procedure uses only molecular shape similarity and topology information inferred directly from the simulated conformations, and is not biased by a priori known information. The automatically recovered coordinates prove as excellent reaction coordinates for the molecules studied and can be used to identify stable states and transitions, and as a basis to build free-energy surfaces. The coordinates provide a better description of the free energy landscape when compared with coordinates computed using principal components analysis, the most popular linear dimensionality reduction technique. The method is first validated on the analysis of the dynamics of an all-atom model of alanine dipeptide, where it successfully recover all previously known metastable states. When applied to characterize the simulated folding of a coarse-grained model of β-hairpin, in addition to the folded and unfolded states, two symmetric misfolding crossings of the hairpin strands are observed, together with the most likely transitions from one to the other. Proteins 2010. © 2009 Wiley-Liss, Inc.

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