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dc.contributor.advisor Grubmüller, Helmut Prof. Dr.
dc.contributor.author Heinz, Leonard
dc.date.accessioned 2021-03-18T15:49:29Z
dc.date.issued 2021-03-18
dc.identifier.uri http://hdl.handle.net/21.11130/00-1735-0000-0005-15AF-F
dc.language.iso eng de
dc.relation.uri http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject.ddc 571.4 de
dc.title Spatially Resolved Hydration Statistical Mechanics at Biomolecular Surfaces from Atomistic Simulations de
dc.type cumulativeThesis de
dc.contributor.referee Grubmüller, Helmut Prof. Dr.
dc.date.examination 2020-12-15
dc.description.abstracteng The statistical mechanics of the first few hydration layers is vital for many biophysical processes, such as protein folding and unfolding, protein function, lipid bilayer self-assembly, and ligand binding. These processes are governed by a fine-tuned free energy balance of competing enthalpy and entropy contributions. Despite extensive experimental and theoretical efforts, the molecular mechanisms of solvent-related free energy contributions are often elusive, especially at topologically and chemically heterogeneous surfaces like proteins or lipid bilayers. To better understand, e.g., the effects of individual amino acids on the solvent-related free energy contributions, a spatial resolution of both solvent enthalpy and entropy is necessary. Whereas the enthalpy component can be readily calculated from a molecular dynamics force field, sampling the entropy contribution presents a significant challenge. In the first part of this thesis, I therefore develop and present a new method, Per|Mut, to calculate spatially resolved solvent entropies from atomistic simulations. The method uses a permutation reduction to increase sampling by the Gibbs factor N! without changing the physics. In addition, Per|Mut employs a third-order mutual information expansion to decompose the solvent entropy into physically interpretable contributions from individual molecules as well as from two- and three-body correlations. The method yielded accurate entropies for test systems with argon and solvated alkanes. When applied to the solvation statistical mechanics of hydrated octanol and the protein crambin, the method revealed the local effects of individual chemical groups or side chains on the solvent entropy. Comparing native-fold crambin and a molten-globule-like conformation, I identified a strongly stabilizing solvent entropy contribution of almost 500 kJ/mol to the total free energy difference of 53 kJ/mo. Remarkably, more than half of the solvent entropy contribution arose from induced water correlations. In addition to understanding protein stability, Per|Mut could prove useful to understand and predict the solvent contributions to ligand binding, which is especially relevant in the realm of computational drug design. The energetics of lipid headgroup dehydration is furthermore expected to play a major role in the free energy landscape of membrane fusion, a process vital for, e.g., exocytosis during synaptic transmission or fusion of enveloped viruses into the host plasma membrane. As revealed by collaborators, pre-fusion lipid membranes at <1 nm distances experience a divalent cation-independent, metastable, protein-free fusion intermediate, characterized by local membrane thickening. In the second part of this thesis, I carry out molecular dynamics simulations of double-membrane systems to identify the molecular causes of the structural changes. Through non-equilibrium simulations and response-time analyses, I demonstrate that the lipid bilayer thickening results from an electrostatically favorable lateral area shrinkage, attributed to dehydration-driven lipid headgroup tilting. de
dc.contributor.coReferee Müller, Marcus Prof. Dr.
dc.subject.eng entropy de
dc.subject.eng hydration de
dc.subject.eng protein folding de
dc.subject.eng protein stability de
dc.subject.eng membrane fusion de
dc.subject.eng membrane thickness de
dc.subject.eng nearest neighbor search de
dc.subject.eng hydrophobic effect de
dc.subject.eng molecular dynamics simulation de
dc.subject.eng MD simulation de
dc.subject.eng mutual information expansion de
dc.subject.eng hydration shell de
dc.subject.eng mutual information de
dc.identifier.urn urn:nbn:de:gbv:7-21.11130/00-1735-0000-0005-15AF-F-4
dc.date.embargoed 2021-12-13
dc.affiliation.institute Göttinger Graduiertenschule für Neurowissenschaften, Biophysik und molekulare Biowissenschaften (GGNB) de
dc.subject.gokfull Biologie (PPN619462639) de
dc.description.embargoed 2021-12-13
dc.identifier.ppn 1751838676

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