Multi-Scale Theoretical Investigation of the Linear and Nonlinear Optical Responses of Di-8-ANEPPS Embedded in Complex Environments
: on the Way to Explore the Complexity of Cell Membranes

Student thesis: Doc typesDoctor of Sciences

Abstract

The aim of this work is to assess the effects of the environment on the nonlinear optical (NLO) responses of the di-8-ANEPPS chromophore by using newly-optimized theoretical chemistry methods. Two types of environments are considered: solutions for a general characterization of its NLO responses, and lipid bilayers to describe its sensor capacities. A two-step molecular mechanics-quantum mechanics approach is used and validated. It is shown that the di-8-ANEPPS NLO responses decrease with increasing the solvent polarity, in agreement with new experimental data. For biological systems, due to their enormous complexity, the strategy was to decompose the chemical diversity found in a plasma membrane (PM) into several one-component lipid bilayers, allowing to disentangle the effects of each lipid species. Starting from a pure DPPC bilayer, collections of systems varying either in the nature of the polar head or in the fatty acids were considered, showing that changes in the hydrophobic head modulate the NLO responses more than the variations in the hydrocarbon core. Mixed systems were then introduced by adding cholesterol molecules at different concentrations in DPPC bilayers, highlighting the condensing effect of cholesterol, inducing an increase in NLO responses.
Finally, the system complexity was taken to a new level with the study of a multi-million atom PM. It showcases what is now possible to do in terms of computational resources and emphasizes the appeal of data mining tools in such complex investigations.
These different contributions deepen our knowledge of the structural organization of increasingly complex systems. As this information is difficult to obtain experimentally, this work truly demonstrates the key role of computational chemistry in inferring structure-property relationships and in helping to unravel the complexity of biological systems.
Date of Award11 Oct 2023
Original languageEnglish
Awarding Institution
  • University of Namur
SponsorsFund for Research Training in Industry and Agriculture (FRIA)
SupervisorBenoit CHAMPAGNE (Supervisor), Yoann Olivier (President), Francesca Cecchet (Jury), Tárcius N. Ramos (Jury), Magali Deleu (Jury), Laura Le Bras (Jury) & Frédéric Castet (Jury)

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