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Description de l'espace conformationnel de peptides cycliques de la famille RGD par une approche inspirée de la robotique et par des simulations de dynamique moléculaire

Abstract : Small cyclic peptides represent an emerging and promising class of therapeutic molecules. However, the lack of knowledge on their conformational space makes their design difficult as well as the prediction of their structure. In order to improve knowledge on these molecules with unique properties, we wanted to develop an alternative approach to those existing allowing the most exhaustive characterization of their conformational space. For that, we have developed EGSCyP method, based on a multi-level representation of the peptide: a mechanical representation and the use of robotics inspired algorithms allowing a global search and then a refinement in an all atom model. EGSCyP was developped to deal with D-amino acids and N-methylated residues. This method has been compared to replica exchange molecular dynamics simulations and experimental data to validate the approach. It has been applied to a set of cyclic pentapeptides RGD derived from Cilengitide, an anticancer drug. Our method has shown good performances, particularly with regard to the completeness of the conformational space of these peptides, and has made possible to evaluate the impact of the chemical modifications like the D-amino acids or N-methylated ones on this conformational landscape.
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Maud Jusot. Description de l'espace conformationnel de peptides cycliques de la famille RGD par une approche inspirée de la robotique et par des simulations de dynamique moléculaire. Chimie théorique et/ou physique. Sorbonne Université, 2018. Français. ⟨NNT : 2018SORUS201⟩. ⟨tel-02886210⟩

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