Developing inhibitors of the enzyme ‘TRMT2a’ for the treatment of PolyQ diseases

Margreiter, Michael Alois; Bolm, Carsten (Thesis advisor); Weinhold, Elmar (Thesis advisor); Rossetti, Giulia (Thesis advisor); Niggemann, Meike (Thesis advisor)

Aachen (2020)
Dissertation / PhD Thesis

Dissertation, RWTH Aachen University, 2020

Abstract

Although the specific causes for all nine polyglutamine diseases were elucidated decades ago, treatment options remain scarce and predominantly focus on symptomatic relief. This is particularly striking as these neurodegenerative diseases are monogenetic. A common hallmark is the formation of mutant protein insoluble aggregates in vulnerable cell populations in the brain, often starting already at mid-life. Thus, there is a clear need for viable neuroprotective strategies that delay disease onset and progression of these fatal disorders. To this end, the protein tRNA methyltransferase 2 homolog A (TRMT2a) was discovered in earlier studies as a strong modulator of polyglutamine mediated toxicity (Dr. Voigt’s Lab, Institute of Neurology, RWTH University Hospital). Computational biology encompasses a wide range of computer-assisted biomodeling approaches. The resulting models aim to integrate often heterogeneous biological data and aid wet-lab experiments. This emerging field of research has contributed substantially to our understanding of the molecular foundations of health and pathogenesis, also in the context of polyglutamine diseases. Moreover, a detailed understanding of these processes can be leveraged to discover and design new drugs in silico- also known as computer-aided drug design (CADD). This thesis uses state-of-the-art CADD approaches to gain insights into TRMT2a at the sequence and structural level. First, I compared the sequence of TRMT2a with closely related ones to identify conserved residues. As I initially lacked structural information on TRMT2a, I generated comparative structural models that eventually enabled the selection of a suitable protein fragment corresponding to a protein domain of TRMT2a. This fragment was then successfully expressed/purified in Prof. Niessing‘s lab (University of Ulm), resulting in the first X-ray crystallographic structure of this domain. Subsequently, I investigated if a pharmaceutical inhibition of TRMT2a (function) might prove equally neuroprotective as silencing TRMT2a. Hence, I assessed whether TRMT2a is susceptible to small molecule modulators, e.g., if our recently crystallized TRMT2a domain would feature a binding site able to accommodate a small molecule ligand, ideally capable to cross the brain-blood-barrier. Unfortunately, I could not find such a site on the crystal structure of the domain. Nevertheless, proteins in solution typically explore vast conformational landscapes. Thus, after characterizing the crystallographic water network, I augmented my search for binding sites by also incorporating dynamical aspects of this domain into my models. (i) I employed machine-learning-based methods to predict residues giving rise to local flexibility in proteins (ii) allosteric communication networks within this domain, followed by (iii) molecular mechanics simulations in an implicit solvent with perturbation approaches. These analyses indicated a putative transient binding site capable of binding small molecules. (iv) To further understand the formation and collapse of such a transient pocket, I conducted molecular dynamics simulations in explicit solvent. Next, I selected a representative snapshot that featured the domain with a pocket conformation suitable to host a small molecule ligand and performed a virtual screening of commercially available compounds complementing this pocket. I prioritized multiple compounds, and these were tested by Dr. Voigt’s team in vitro on HEK cell lines. We found their efficacy in mitigating polyglutamine toxicity comparable to TRMT2a silenced cell lines, while not providing further benefits for already TRMT2a depleted cells lines. This indicates that these compounds might indeed interfere with TRMT2a. Moreover, for one compound, it was possible to show dose-dependent binding to the domain in surface plasmon resonance experiments (SPR). The latter analyses were performed in Prof. Niessing’s lab. Encouragingly, a few of these compounds also showed a rescuing effect on fibroblasts derived from patients, independent from their respective polyglutamine disorders. A worldwide patent application for these compounds involving the labs of Prof. Shah, Prof. Schulz (both Research Center Jülich), Dr. Voigt, and Prof. Niessing is currently underway. In the second part of my thesis, I explore the consequences of hampered TRMT2a activity and how this might give rise to reduced aggregate formation. I hypothesized that in the absence of TRMT2a, the translation of the polyglutamine tract becomes more error-prone and results in non-glutamine interruptions. Interrupted polyglutamine tracts are less toxic and result in fewer aggregates. To this end, I simulated uninterrupted and interrupted polyglutamine tract constructs with Replica Exchange Protein Monte Carlo methods and compared their respective physicochemical properties that give rise to their different aggregation propensities. In the third part of my thesis, I applied CADD techniques to two targets of interest for pain. Here, I investigated in collaboration with Prof. Gründer (University Clinic Aachen), how RPRFa, an RFamide peptide from the venom of a cone snail, binds to Acid-sensing ion channel 3 (ASIC3). This proton-gated Na channel plays a key role in neuropathic pain. Here, I build a comparative model and investigated in which conformation the peptide ligand could bind. Based on these models, I proposed several single-point mutants and Prof. Gründer's team assessed their effect with electrophysiology and UV-linking experiments. In a follow-up project with the same group, I mapped the binding site of Dynorphin A(1-14) to ASIC1 using a related approach augmented with explicit solvent simulations. Conclusively, the results presented in this thesis indicate that a computational approach to problems in the life sciences can not only facilitate the interpretation of experimental observations but also guide and augment them when they are introduced at the critical early stages of a project.

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