Computational Drug Discovery and Design

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covariance matrix (only with a correlation matrix in the case of
a normalized PCA).


  1. In addition to the 2D principal component plots, other types
    of graphic plot are of interest and provide for example an
    insight on protein regions whose movements contribute the
    most to explain the conformational diversity along each princi-
    pal component (residue wise loadings plot). All these analyses
    are well described in the section PCA of the online tutorial
    using bio3d R package at http://thegrantlab.org/bio3d/
    tutorials/trajectory-analysis.

  2. It should be taken into account that the energy used by
    reweight script is in kT units. In Amber 14 the energy unit is
    kcal/mol and must be converted.

  3. One has to be sure that the considered system has reached its
    equilibrium state before introducing a bias in the simulation.
    Indeed, if the system is not equilibrated enough, the estimated
    free energy variation could be the combination of the none-
    quilibrated part of the system and the bias introduced.

  4. The greater the force constant k, the smaller the region
    explored by the system. This results in narrower distributions
    ofζand therefore a smaller overlap between two successive
    windows. On the contrary, the lower the force constantk,the
    greater the region explored by the system. This can have the
    effect of exploring several stable states and therefore obtaining
    non-Gaussian multimodal distributions ofζ.

  5. The smaller the step size between windows, the greater the
    sampling. However the number of windows strongly impacts
    the amount of computing resources needed.


Acknowledgments


This work was supported by the Institut de Recherche Servier and
the French National Research Agency (ANR-13-JSV5-0001 and
ANR-15-CE20-0015). The authors wish to thank the Re ́gion
Centre Val de Loire and the Ligue contre le Cancer for financial
supports and the Orle ́ans-Tours CaSciModOT at the Centre de
Calcul Scientique de la Re ́gion Centre Val de Loire and the Centre
Re ́gional Informatique et d’Applications Nume ́riques de Norman-
die (CRIANN) for providing computer facilities.

References



  1. Du X, Li Y, Xia Y-L et al (2016) Insights into
    protein–ligand interactions: mechanisms,
    models, and methods. Int J Mol Sci 17:144.
    https://doi.org/10.3390/ijms17020144
    2. Changeux JP, Edelstein S (2011) Conforma-
    tional selection or induced fit? 50 years of
    debate resolved. F1000 Biol Rep.https://doi.
    org/10.3410/B3-19


424 Sonia Ziada et al.

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