Computational design of G Protein-Coupled Receptor allosteric signal transductions

Membrane receptors sense and transduce extracellular stimuli into intracellular signaling responses but the molecular underpinnings remain poorly understood. We report a computational approach for designing protein allosteric signaling functions. By combining molecular dynamics simulations and design calculations, the method engineers amino-acid ‘microswitches’ at allosteric sites that modulate receptor stability or long-range coupling, to reprogram specific signaling properties. We designed 36 dopamine D2 receptor variants, whose constitutive and ligand-induced signaling agreed well with our predictions, repurposed the D2 receptor into a serotonin biosensor and predicted the signaling effects of more than 100 known G-protein-coupled receptor (GPCR) mutations. Our results reveal the existence of distinct classes of allosteric microswitches and pathways that define an unforeseen molecular mechanism of regulation and evolution of GPCR signaling. Our approach enables the rational design of allosteric receptors with enhanced stability and function to facilitate structural characterization, and reprogram cellular signaling in synthetic biology and cell engineering applications.

Reprogramming G Protein-Coupled Receptor Structure, Function And Signaling By Computational Design

Dániel Kéri

G protein-coupled receptors (GPCRs) are 7-transmembrane alpha-helical integral membrane proteins on which cells heavily rely to receive information regarding their external environment. These receptors are able to transfer information to intracellular downstream effectors upon stimulation from their cognate ligands, which can be considerably diverse. They can include light, small molecules, peptides, protons; Due to its evolutionary success, over millions of years of evolution, this protein family has expanded to include over 800 members. Despite the large size of the family and the diverse inputs they accept, the structure and the mechanism for relaying signals to their downstream partners, G proteins and B-arrestins, remains largely the same. As these receptors are involved in a great deal of biological processes such as sight (rhodopsin), cognition (dopamine, serotonin, opioid receptors), immunity (chemokine receptors), heart function (adrenergic, angiotensin receptors), etc.; a great deal of effort has gone into understanding their structure and function. Our efforts have gone into understanding their signaling properties and rationally modifying them. Most proteins are fairly flexible entities and their structures tend to oscillate and move around, sampling a number of conformations. Nature has taken advantage of these natural motions to regulate protein function from distant binding sites, in a phenomenon called allostery. GPCRs are unique in the sense that their primary function relies on allostery. By tweaking the allosteric signaling of GPCRs, we hope to have a better understand allostery, use the principles we learn to create designer GPCR biosensors with the desired sensitivity, and to eventually create de novo allosteric proteins. In this work, I present our progress in this effort, which has been significant. We have created a highly accurate in silico method to allosterically alter relative stabilities of the active and inactive states of the GPCR dopamine D2 receptor, but also to independently control its allosteric signaling strength. With our methodology we have been able to create receptors which have high basal activities by selectively stabilizing the active state of the receptor. This has already facilitated the structure determination of the active, G protein-bound dopamine D2 receptor; a first for this GPCR. Additionally, we have created a number of dopamine D2 variants with roughly 100 times higher sensitivity to dopamine than the WT receptor. These efforts continue to characterize the functional effects of these allosteric mutations. Furthermore, we are also working on a collaboration to rewire the signaling pathway of the adenosine A2A receptor. Adenosine is a common immunosuppresant in solid tumor micro-environments (TMEs). By rewiring the downstream signaling of the A2A receptor, we hope to reverse the response of T-cells in these TMEs to activate and attack the solid tumor.

EPFL2021

Computational rewiring of allosteric pathways reprograms GPCR selective responses to ligands

Patrick Daniel Barth, Mahdi Hijazi, Dániel Kéri, Aurélien Laurent Jean-Charles Oggier

G-protein-coupled receptors (GPCRs) are the largest class of cell surface receptors and drug targets, and respond to a wide variety of chemical stimuli to activate diverse cellular functions. Understanding and predicting how ligand binding triggers a specific signaling response is critical for drug discovery and design but remains a major challenge. Here, computational design of GPCR allosteric functions is used to uncover the mechanistic relationships between agonist ligand chemistry, receptor sequence, structure, dynamics and allosteric signaling in the dopamine D2 receptor. Designed gain of function D2 variants for dopamine displayed very divergent G-protein signaling responses to other ligand agonists that strongly correlated with ligand structural similarity. Consistent with these observations, computational analysis revealed distinct topologies of allosteric signal transduction pathways for each ligand-bound D2 pair that were perturbed differently by the designs. We leveraged these findings by rewiring ligand-specific pathways and designed receptors with highly selective ligand responses. Overall, our study suggests that distinct ligand agonists can activate a given signaling effector through specific “allosteric activator” moieties that engage partially independent signal transmission networks in GPCRs. The results provide a mechanistic framework for understanding and predicting the impact of sequence polymorphism on receptor pharmacology, informing selective drug design and rationally designing receptors with highly selective ligand responses for basic and therapeutic applications.

bioRxiv2022

Reprogramming the B1 Domain of Streptococcal Protein G (GB1)

Esra Bozkurt

Nature has the ability to cope with extreme pH, temperature and pressure, in addition to bestowing a wide array of functionalities to (bio)macromolecules. These specialized skills have attracted the interest of vast scientific communities especially in view of possible industrial or biomedical applications. In general, the design of functional and thermostable biological constructs is one of the overarching themes in biochemisty. Despite extensive research and some recent breakthroughs, the level of understanding of the factors that determine protein reactivity and stability is still modest. The use of computational methods for an atomic level understanding of the functionality and stability of biomacromolecules is therefore an attractive alternative. This dissertation presents a number of research projects that combine different computational methods in a close blend with experiments in order to identify the crucial determinants that can be used for a rational design of thermostable and catalytically active, (re-)engineered protein domains. The main findings are the following: Chapter 3 of the thesis presents the results of computational studies towards the design of biomimetic compounds capable of performing tetrazole formation based on Lewis acid catalysis. Our quantum chemical calculations suggest the incorporation of unnatural modifications of glutamate residues as a promising starting point for the development of an efficacious bioinspired catalytic system based on a zinc active site. Chapter 4 and 5 focuses on the computational design and re-engineering of the B1 domain of Streptococcal protein G (GB1) to introduce hydrolytic activity. In addition to exhibiting encouraging reaction rates, our computationally designed artificial enzymes are reasonably thermostable. Chapter 6 is about the design of a highly thermostable metallo variant of GB1. It describes the successful attempt to establish a stable tetrahedral zinc binding site in GB1 with the help of a computational protocol based on genetic algorithm optimization. A high resolution crystal structure of this metallo variant reveals a novel head-to-tail organization. Chapter 7 reports the design of two re-engineered thermostable GB1 sequences using a new computational method for thermostability prediction as well as on their expression and structural characterization. Interestingly, one of the mutants show an intertwined dimer organization in the crystal structure. The combined theoretical and experimental approaches reported herein provide valuable insights into the successful design of different GB1 variants with tailored properties and may help to open new avenues for the rational design of new thermostable and functional biomacromolecules.