On the simplification of dynamics in molecular systems

Sergei Grudinin

LJK CNRS, Grenoble, France

Simplification of dynamic systems has numerous biological applications, from protein domain detection [1] to automatic coarse-graining in molecular simulations [2, 3]. Various solutions have been proposed for this problem, such as using graph theory [4-5], examining the covariance patterns in elastic network models [6], employing machine-learning-based approaches [7], or developing specific techniques based on knowledge of multiple protein conformations [8]. I will present our approach based on nonlinear normal-mode analysis with several biological applications including fitting atomistic models into small-angle scattering (SAXS and SANS) and atomic force microscopy (AFM) data [9]. I will also present some results from the recent Elixir implementation study [10], where we examined existing strategies for dealing with multi-conformer proteins and compared motions and rigid domains predicted by different techniques.

[1] S. Jones, M. Stewart, A. Michie, M. B. Swindells, C. Orengo, and J. M. Thornton, “Domain assignment for protein structures using a consensus approach: characterization and analysis,” Protein Science, vol. 7, no. 2, pp. 233–242, 1998.
[2] Z. Zhang, L. Lu, W. G. Noid, V. Krishna, J. Pfaendtner, and G. A. Voth, “A systematic methodology for defining coarse-grained sites in large biomolecules,” Biophysical journal, vol. 95, no. 11, pp. 5073–5083, 2008.
[3] S. Kmiecik, D. Gront, M. Kolinski, L. Wieteska, A. E. Dawid, and A. Kolinski, “Coarse-grained protein models and their applications,” Chemical reviews, vol. 116, no. 14, pp. 7898–7936, 2016.
[4] J. Sim, J. Sim, E. Park, and J. Lee, “Method for identification of rigid domains and hinge residues in proteins based on exhaustive enumeration,” Proteins: Structure, Function, and Bioinformatics, vol. 83, no. 6, pp. 1054–1067, 2015.
[5] D. J. Jacobs, A. J. Rader, L. A. Kuhn, and M. F. Thorpe, “Protein flexibility predictions using graph theory,” Proteins: Structure, Function, and Bioinformatics, vol. 44, no. 2, pp. 150–165, 2001.
[6] O. Keskin, S. R. Durell, I. Bahar, R. L. Jernigan, and D. G. Covell, “Relating molecular flexibility to function: a case study of tubulin,” Biophysical journal, vol. 83, no. 2, pp. 663–680, 2002.
[7] J. Wells, A. Hawkins-Hooker, N. Bordin, C. Orengo, and B. Paige, “Chainsaw: protein domain segmentation with fully convolutional neural networks,” bioRxiv, pp. 2023–07, 2023.
[8] S. Hayward, & H. J. Berendsen, H. J. Systematic analysis of domain motions in proteins from conformational change: new results on citrate synthase and T4 lysozyme. Proteins: structure, function, and bioinformatics, 30(2), 144-154, 1998.
[9] A. Hoffmann, & S. Grudinin, NOLB: Nonlinear rigid block normal-mode analysis method. Journal of chemical theory and computation, 13(5), 2123-2134, 2017.

Comments are closed.