title: Computational Studies of Ligand Efficacy and Binding in G-protein Coupled Receptors
Creators: name: Calderón, Jacqueline
Publisher: name: Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)
Year: 2024
Subjects: subject: GPCRs, metadynamics simulations

description: Decoding the dynamic nature of membrane proteins and their various interconnections in the cell is becoming one of the key elements in understanding the colorful, intricate, and mysterious molecular machinery of life. Membrane proteins, such as G protein-coupled receptors (GPCRs), are present in the cell membranes of all living organisms and contribute to their biological and physicochemical properties. Understanding the dynamic nature of GPCRs requires methods able to capture an ensemble of structural conformers that represent the states of these proteins. In this sense, computational methods have proven useful in studying the dynamic functional behavior of GPCRs. This doctoral thesis offers several examples of how computational methods can be exploited in GPCR research and drug discovery. Here we present two protocols based on atomistic simulations whose sampling is enhanced with metadynamics to provide quantitative information on the states involved in the dynamic nature of GPCRs. We have considered two aspects of the conformational behavior of GPCRs: •The activation mechanism of class A GPCRs •Binding of peptide ligands to class A GPCRs The two main research branches addressed in this doctoral thesis resulted in five published research articles. To account for the different research areas studied here, this doctoral thesis is divided into six sections, as follows: Chapter 1 provides a general description of GPCRs and the theoretical background underlying computational methods applied in the original contributions reported in this thesis. In particular, the basic principles of docking and scoring, virtual screening, and simulation methods will be described briefly, with a focus on the specific techniques applied in this thesis (molecular dynamics and metadynamics). In Chapter 2, a generally applicable metadynamics protocol for characterizing the activation free-energy profiles of class A GPCRs is described. First, a proof-of-principle application on the serotonin receptor 5-HT<sub>1A</sub> is presented. For this purpose, an effective collective variable, the activation index (A<sup>100</sup>), and the methodological advancements offered by metadynamics as an enhanced sampling technique are combined. The A<sup>100</sup> index is a linear combination of five inter-helix distances between α-carbons that allows the activation state of class A GPCRs to be characterized. In order to make the best use of the computational resources, well-tempered metadynamics simulations in the multiple-walker scheme were carried out. Thus, sampling of the conformational space is accelerated, and the activation free-energy profiles are derived. Then, the metadynamics simulations are reweighted along a set of conserved microswitches to gain structural details on how ligands modulate the conformational equilibria of the serotonin receptor 5-HT<sub>1A</sub>. In Chapters 3 and 4, we applied and further validated the aforementioned metadynamics-based protocol to study the activation mechanism of a prototypical class A GPCR, the β<sub>2</sub>-adrenergic receptor. Our simulations provided structural insights that rationalize the mechanism of action of ligands with different efficacies. In particular, Chapter 3 presents direct evidence of structural requirements driving ligand efficacy and partial agonism at the β<sub>2</sub>-adrenergic receptor. Whereas Chapter 4 provides structural features relevant to basal activity and inverse agonism at the β<sub>2</sub>-adrenergic receptor. The effect of the G protein is also investigated. We showed that the G protein can allosterically induce conformational changes in microswitches located in the intracellular domain. Our results support the notion that inverse agonist ligands cannot recruit G-protein, while the agonistic activity shown by antagonists might be related to non-optimal G-protein recruitment. In Chapter 5, two new C-terminally amidated α,γ-hexapeptides are presented. Both peptides bind the neuropeptide Y<sub>4</sub>-receptor and act as partial agonists. To investigate the binding mode of these new α,γ-hexapeptides, induced fit docking and molecular dynamics simulations were performed. We found that the di-arginine motif R33-X-R35 of the peptide plays a prominent role in the interaction of the ligands with the Y<sub>4</sub>R. A more stable network of H-bond and salt bridge interactions was observed for the α,γ-peptide presenting higher binding affinity and potency. In Chapter 6, a metadynamics-based protocol to simulate the binding/unbinding of peptide ligands and to determine the free energies of binding is described. Here, exemplary simulations for subtypes Y<sub>1</sub>R, Y<sub>2</sub>R, and Y<sub>4</sub>R of the neuropeptide Y receptor family, vasopressin binding to the vasopressin V<sub>2</sub> receptor, and oxytocin binding to the oxytocin receptor are presented. The global free-energy minimum obtained corresponds well to the known binding poses and gives new insight into the binding sites of peptide ligands. These new approaches generate insights compatible with previous simulation and experimental studies at a relatively low computational cost. Our work also provides new insights into the structural basis underlying the mechanisms by which pharmacologically distinct ligands modulate the conformational landscape of GPCRs that decisively affect ligand efficacy and subsequent signaling responses. These studies provide a dynamic description of the GPCR function.