Computational modelling of supramolecular metallopeptide assemblies

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Abstract

Among the important questions in supramolecular peptide self-assemblies are their interactions with metallic compounds and ions. In the last decade, intensive efforts have been devoted to understanding the structural properties of these interactions including their dynamical and catalytic impact in natural and de novo systems. Since structural insights from experimental approaches could be particularly challenging, computational chemistry methods are interesting complementary tools. Here, we present the general multiscale strategies we developed and applied for the study of metallopeptide assemblies. These strategies include prediction of metal binding site, docking of metallic moieties, classical and accelerated molecular dynamics and finally QM/MM calculations. The systems of choice for this chapter are, on one side, peptides involved in neurodegenerative diseases and, on the other, de novo fibrillar systems with catalytic properties. Both successes and remaining challenges are highlighted so that the protocol could be apply to other system of this kind.

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Martín, L. R., Santiago, L. R., Korendovych, I. V., Sodupe, M., & Maréchal, J. D. (2024). Computational modelling of supramolecular metallopeptide assemblies. In Methods in Enzymology (Vol. 697, pp. 211–245). Academic Press Inc. https://doi.org/10.1016/bs.mie.2024.03.021

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