Investigations toward the rational modulation of G protein-coupled receptor signalling pathways using in silico methods

G protein-coupled receptors (GPCRs) are one of the most important protein families and function as signal transducers located in the cell membrane. Currently, about one third of the marketed drugs target a GPCR, reflecting its importance in therapy and disease. Thus, it is not surprising that GPCRs...

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1. Verfasser: Scharf, Magdalena Martina
Beteiligte: Kolb, Peter (Prof. Dr.) (BetreuerIn (Doktorarbeit))
Format: Dissertation
Sprache:Englisch
Veröffentlicht: Philipps-Universität Marburg 2021
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Zusammenfassung:G protein-coupled receptors (GPCRs) are one of the most important protein families and function as signal transducers located in the cell membrane. Currently, about one third of the marketed drugs target a GPCR, reflecting its importance in therapy and disease. Thus, it is not surprising that GPCRs and their signalling are of major interest for researchers. In this thesis, in silico methods were used to investigate the modulation of GPCR signalling pathways. The modulation of GPCR signalling can take place on different levels, e.g. at the level of GPCR ligands or in the downstream signalling pathways. Interactions of the receptor with small molecules can result either in its inactivation or activation. The latter can lead to the intracellular recruitment of various effector proteins to the receptor which can then induce different signalling pathways inside the cell. Certain ligands can induce a stronger recruitment of one effector protein compared to other effector proteins. On a structural basis it is still unclear why and how these ligands induce such bias. Furthermore, there are many different proteins involved in the downstream signalling of GPCRs. One protein family are the Regulators for G protein Signalling (RGS) which are involved in the deactivation of the G protein and, hence, GPCR signalling. Although the members of this protein family are known to be involved in a variety of processes and diseases –many of which are also related to GPCR signalling– they are still not well understood. GPCR signalling needs to be comprehended better on all of these levels to be able to modulate them rationally. In this thesis, two GPCRs –the β2-adrenergic receptor (β2AR) and the Cannabinoid receptor 2 (CB2)– and one member of the RGS protein family –the RGS7– were targeted with in silico techniques in five studies to investigate their signalling and its modulation. Two of the studies described in this thesis targeted the β2AR. More than 30 structures of this class A GPCR in different activation states are available, allowing for more exhaustive structural investigations. This fact was used and three different structures of the β2AR in different activation states were targeted with a molecular library using a comparative docking approach. The aim was to predict novel agonists for this receptor based on the assumption that these should rather result from docking calculations against active conformations of the receptor. The selected molecules were then characterised pharmacologically, showing that this approach was very successful. Furthermore, a retrospective analysis of the docking approach showed up the optimal way to increase the chances to discover novel agonists for this receptor or other class A GPCRs. The aim of the second study targeting the β2AR was to predict antagonists with novel structural scaffolds for this receptor using docking calculations. The project was conducted in collaboration with InterAx Biotech AG who also characterised the selected ligands pharmacologically. An antagonist for the β2AR with a previously undescribed structural scaffold was successfully predicted in this study and a structure-activity relationship investigation showed the general affinity of this structural scaffold for this receptor. The second studied GPCR was the CB2. In one study, molecular docking was applied to find structurally novel ligands for the CB2. For that, the docking setups were first optimised using a set known reference ligands. The prediction of water positions in the orthosteric binding pocket was shown to be a useful tool to achieve optimised docking results. These docking setups were then targeted by a large molecular library docking screen and several re-ranking and filtering steps were used to achieve better enrichment, similar to one of the approaches targeting the β2AR. The selected molecules were then tested by collaboration partners from the Veprintsev lab at the University of Nottingham and preliminary results suggest that this screen was successful. In the second study, Molecular Dynamics simulations were applied to the CB2 to investigate the structural basis of ligands inducing a certain recruitment bias. The results showed that it might be difficult to track recruitment bias with this method, however, indicators for receptor activation and deactivation could be observed. In the last study, the RGS7-Gβ5 complex was targeted using docking calculations. The overall goal is to find small molecules that can bind to this complex, thereby modulating its conformation and possibly its function. However, no binding sites of small molecules on this complex are known. Therefore, the main part of the study consisted of the prediction and evaluation of possible binding sites. Promising cavities were identified and will be targeted in docking screens to investigate whether they can serve the proposed function. This project was conducted in collaboration with the Martemyanov lab at the Scripps Research Institute in Florida. Overall, the described studies were able to (1) show up ideas on how to best employ in silico tools to obtain the desired results, (2) find potential small molecule binding sites for a quite unexplored but therapeutically interesting target, (3) give insights on dynamic processes and structural rearrangements of receptor-ligand interactions leading to (biased) signalling and (4) successfully predict several novel ligands with different properties for two different GPCR targets with hit rates of up to 37%.
Umfang:243 Seiten
DOI:10.17192/z2021.0073