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Research project (§ 26 & § 27)
Duration : 2020-04-01 - 2020-09-30

The initial interaction of SARS-CoV-2 with human cells results from a protein-protein interaction between the SARS-CoV-2 Spike protein and the human ACE2 receptor. Promising novel pharmaceutics are based on solubilized versions of the ACE2 receptor, potentially blocking the virus proteins and hindering an interaction with human ACE2 present on the cells. Atomistic models of the Spike proteins and the ACE2 receptor are available, with the glycan structures reduced to the first 1-2 sugar residues. We have created a complete model of the Spike-ACE2 interaction, with full glycosylation. The model confirms that the glycans can play a significant role in the interaction. In particular, there is evidence that removal of the N90 glycan strengthens the interaction. This offers possibilities to engineer the therapeutic proteins to show stronger interactions with Spike and therefore be more effective. We will create computer models of Spike – ACE2 interactions with different variants of ACE2. This includes species-specific variations (mouse ACE2 does not interact with Spike), naturally occurring genetic modifications, and alternative therapeutic formats.
Research project (§ 26 & § 27)
Duration : 2020-05-01 - 2023-04-30

Intrinsically disordered proteins (IDPs) or proteins containing disordered regions (IDRs) are interesting both biophysically and physiologically, but remain difficult to study by current methods in structural biology and biophysics. IDPs and IDRs cannot be described by a single representative structure, but are best characterized by ensembles of conformations that are distinctly different from a random coil. The regulatory domain (RD) of human tyrosine hydroxylase (TyrH) is an example of hybrid protein containing structured and IDR region. TyrH is regulated by phosphorylation of RD-TyrH within the IDR and subsequent interaction with 14-3-3 proteins. As an example of IDPs for this proposal we selected the microtubule associated protein 2c (Map2c) and its homologous tau protein containing highly similar C-terminal disordered regions. Yet, the experimentally observed phosphorylation pattern is very different for the two IDPs, suggesting that residual structural preferences govern the phosphorylation propensity. We will characterize the conformational ensembles of RD-TyrH, Map2c and tau. We hypothesize that shifts in the conformational ensembles of these IDPs/IDRs are crucial to understand their function and will further develop integrative experimental and computational approaches to characterize these shifts. We will study our model proteins using a wide range of techniques to characterize the shifts in the conformational ensembles. Computer simulations and nuclear magnetic resonance (NMR) spectroscopy are key techniques to study IDPs/IDRs at an atomic resolution. The applicability of both methods is limited by the potential size of the conformational ensembles. We will develop and merge the necessary methodologies. Computationally, we will use enhanced sampling of backbone degrees of freedom of fragments and merge these fragments to construct a large number of viable IDP conformations. Experimental data from NMR will be used to guide the formation of representative ensembles. Innovation The direct interplay of experimental and computational techniques is the key point of this proposal. While both approaches individually cannot be expected to understand the function of IDPs at a detailed level, their combination will. We will develop novel enhanced sampling methods to generate realistic conformations and use the experimental data to form realistic ensembles. We bring together two groups with highly complementing expertises in both areas.
Research project (§ 26 & § 27)
Duration : 2018-07-01 - 2021-06-30

It has been proven difficult to obtain experimental structures of protein-protein complexes. Computational methods like protein-protein docking attempt to overcome the mismatch between the number of available complex structures and single protein structures by the prediction of binding interfaces. However, the binding free-energy estimates given by the scoring algorithms used in such approaches show only poor correlation with experimentally determined binding strengths. Molecular dynamics (MD) simulations are a premier computational technique which allows for the atomistic modeling of the interactions, structures and motions of (bio-)molecular systems. Very recently, we calculated the binding free energy of two small proteins, namely Ubiquitin and the very flexible Ubiquitin-binding domain of the human DNA Polymerase ι (UBM2), using an MD simulation-based approach. Our results were in very good agreement with experimentally determined values (the mean unsigned error to experimentally determined values was 2.5 kJ/mol or lower) and the statistical errors of the calculations were also mostly in the order of thermal noise. In the proposed project, we aim to develop more efficient approaches that can be readily used on a wide variety of protein-protein complexes. In particular, the project addresses three aims. The first aim is the generation of reference data on the calculation of biomolecular binding affinity using the previously described approach for validation and subsequent optimization. The second aim is the optimization of the simulation method to efficiently score a high number of possible protein docking poses for similarity to the canonical complex structure. Preliminary analyses suggest that we can reduce the overall simulation time by two to three orders of magnitude, which with current computational resources makes a more high-throughput approach feasible, while simultaneously retaining sufficient accuracy to provide binding affinity estimates that can be compared to experimental values. In a more independent part of the project we will focus on a specific aspect of the binding affinity calculation, namely the contribution of conformational preferences of biomolecules. To avoid adverse effects upon administering e.g. mouse-derived antibodies for therapeutic purposes, the framework regions of a mouse antibody are being mutated to become (more) human-like. Such mutations do not affect the antibody-antigen interface directly, but are often seen to negatively influence the binding affinity due to altered conformational preferences of the antibody. As a third aim, we will develop a method to predict the binding free-energy change upon antibody framework mutation based on the conformational preferences of the antibody molecules.

Supervised Theses and Dissertations

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