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Identifying Functional Hotspot Residues for Biased Ligand Design in G-Protein-Coupled Receptors S

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Identifying Functional Hotspot Residues for Biased Ligand Design in G-Protein-Coupled Receptors S Supplemental material to this article can be found at: http://molpharm.aspetjournals.org/content/suppl/2018/01/24/mol.117.110395.DC1 1521-0111/93/4/288–296$35.00 https://doi.org/10.1124/mol.117.110395 MOLECULAR PHARMACOLOGY Mol Pharmacol 93:288–296, April 2018 Copyright ª 2018 by The American Society for Pharmacology and Experimental Therapeutics Identifying Functional Hotspot Residues for Biased Ligand Design in G-Protein-Coupled Receptors s Anita K. Nivedha, Christofer S. Tautermann, Supriyo Bhattacharya, Sangbae Lee, Paola Casarosa, Ines Kollak, Tobias Kiechle, and Nagarajan Vaidehi Department of Molecular Immunology, Beckman Research Institute of the City of Hope, Duarte, California (A.K.N., S.B., S.L., N.V.); Departments of Medicinal Chemistry (C.S.T.) and Immunology and Respiratory Diseases Research (I.K., T.K.), Boehringer Ingelheim Pharma GmbH & Co. KG, Biberach, Germany; and Corporate Department of Business Development and Licensing, C.H. Boehringer Sohn, Ingelheim, Germany (P.C.) Received August 24, 2017; accepted January 16, 2018 Downloaded from ABSTRACT G-protein-coupled receptors (GPCRs) mediate multiple signal- coupling region in GPCRs, we have developed a computational ing pathways in the cell, depending on the agonist that activates method to calculate ligand bias ahead of experiments. We have the receptor and multiple cellular factors. Agonists that show validated the method for several b-arrestin–biased agonists in molpharm.aspetjournals.org higher potency to specific signaling pathways over others are b2-adrenergic receptor (b2AR), serotonin receptors 5-HT1B and known as “biased agonists” and have been shown to have better 5-HT2B and for G-protein–biased agonists in the k-opioid therapeutic index. Although biased agonists are desirable, their receptor. Using this computational method, we also performed design poses several challenges to date. The number of assays a blind prediction followed by experimental testing and showed to identify biased agonists seems expensive and tedious. that the agonist carmoterol is b-arrestin–biased in b2AR. Therefore, computational methods that can reliably calculate Additionally, we have identified amino acid residues in the the possible bias of various ligands ahead of experiments and biased agonist binding site in both b2AR and k-opioid receptors provide guidance, will be both cost and time effective. In this that are involved in potentiating the ligand bias. We call these work, using the mechanism of allosteric communication from residues functional hotspots, and they can be used to derive the extracellular region to the intracellular transducer protein pharmacophores to design biased agonists in GPCRs. at ASPET Journals on October 1, 2021 Introduction lowering the unfavorable side effects of a drug. This property of biased agonists can markedly improve their therapeutic G-protein-coupled receptors (GPCRs) are a superfamily of index when compared with unbiased or balanced agonists signaling proteins of critical importance to cellular function, (Mailman, 2007; Neve, 2009; Violin et al., 2014). Design of and comprise the largest group of drug targets. The binding of biased agonists remains a daunting challenge due to the endogenous agonists to their target GPCRs results in coupling complexity of the cellular and structural factors that contrib- to a variety of intracellular transducer proteins, including ute to the bias. Therefore, an understanding of the structural various heterotrimeric G-proteins and b-arrestins, that medi- underpinnings of biased signaling of both G-protein bias as ate different downstream signaling pathways. Certain GPCR well as b-arrestin bias of GPCRs is needed to design biased agonists elicit differential responses to different signaling agonists for GPCRs. pathways and are known as biased agonists, and the phenom- Linking GPCR Conformation to Cellular Function. enon is called functional selectivity or biased signaling (Urban Several factors contribute to biased signaling by an agonist– et al., 2007; Rajagopal et al., 2010; Rasmussen et al., 2011; GPCR pair in cells: 1) structural features of the agonist–GPCR– Wisler et al., 2014). G-protein or agonist–GPCR–b-arrestin complex (Shukla et al., The ability of biased agonists to cause differential signaling 2014) and 2) cell-specific and tissue-specific factors (Zhou and resulting in more focused cellular changes could translate to Bohn, 2014). Designing biased agonists is a challenge due to the lack of structural information on how an agonist–GPCR This work was funded by Boehringer-Ingelheim and by National Institutes of pair selectively couples to specific G-proteins or b-arrestins. Health National Institute of General Medical Sciences [Grant R01-GM097296]. Moreover, because GPCRs are dynamic, with various possi- https://doi.org/10.1124/mol.117.110395. s This article has supplemental material available at molpharm. ble active-state conformations, the structural ensemble of aspetjournals.org. the agonist–GPCR–transducer complex is one of the key ABBREVIATIONS: 3D, three-dimensional; b2AR, b 2-adrenergic receptor; BAI, b-arrestin interface; BI-167107, 5-hydroxy-8-[1-hydroxy-2-[[2- methyl-1-(2-methylphenyl)propan-2-yl]amino]ethyl]-4H-1,4-benzoxazin-3-one; EC, extracellular; ECL2, extracellular loop 2; GPCR, G-protein- coupled receptor; GPI, G-protein interface; 5-HT1B, 5-hydroxytryptamine (serotonin) receptor 1B; 5-HT2B, 5-hydroxytryptamine (serotonin) receptor 2B; MD, molecular dynamics; kOR, k-opioid receptor; PDB, Protein Data Bank; PR, allosteric pipeline ratio; SAR, structure–activity relationship; TM, transmembrane domain; U69593, N-methyl-2-phenyl-N-[(5R,7S,8S)-7-pyrrolidin-1-yl-1-oxaspiro[4.5]decan-8-yl]acetamide. 288 Identifying Functional Hotspots for Biased Ligand Design 289 determinants driving the biased signaling (Shukla et al., 2014). the m-opioid receptor because the active state structure of kOR The selectivity of GPCRs to trigger distinct intracellular is not available and we wanted to test our computational signaling profiles is very ligand dependent. Spectroscopic method using a homology model of the receptor that makes the studies have now established that ligands differentially stabi- testing more realistic. lize a range of GPCR conformations (Yao et al., 2006; Kahsai The serotonin receptors 5-hydroxytryptamine 1B (5-HT1B) et al., 2011; Liu et al., 2012; Nygaard et al., 2013). Therefore, and 5-HT2B have been crystallized with the same agonist knowledge about how the agonist affects the agonist–GPCR–G- ergotamine, yet ergotamine shows b-arrestin bias in 5-HT2B protein structural ensemble will significantly aid the design of and not in 5-HT1B (Wacker et al., 2013). We chose to study the biased agonists. system to find out which residues in 5-HT2B cause the bias in Challenges in Biased Ligand Identification and ergotamine. This example would provide a validation for the Design. Given the huge challenges in crystallography and same ligand showing different biases in two related receptors. NMR in determining structural ensembles of agonist-GPCR- Another similar example is the bias behavior of epinephrine in effector complexes, computational methods can greatly aid in the triple mutant T68F, Y132G, Y219A b2AR, denoted here as delineating the structural factors that determine agonist b2ARTYY. This mutant was designed using evolutionary trace bias and its outcome. Despite a wealth of biochemical and analysis to identify residues that could cause bias in b2ARTYY biophysical studies on inactive conformations, there is (Shenoy et al., 2006). Thus, choosing the variety of different paucity of structural information on active conformations of systems described here provides a test for the robustness of Downloaded from GPCRs. More importantly the dynamics of the agonist- our computational method. GPCR-effector complex is one of the major factors leading To summarize, we have studied b2AR and its biased mutant to a conformational ensemble, which governs the functional b2ARTYY with several agonists, 5HT1B and 5HT2B with the same selectivity of biased signaling. agonist, and kOR with three agonists including two G-protein– A better understanding of the structural basis of G protein/ biased agonists. These systems are also listed in Supplemental b-arrestin selection will provide for a more precise targeting of Table 1 of the Supplemental Information for convenience. molpharm.aspetjournals.org GPCRs with pharmaceuticals and also inform ongoing structure-based drug discovery efforts. Hence, our goal in this work is to identify structural elements in the GPCR that Materials and Methods confer functional selectivity either to the G-protein signaling A New Computational Method for Calculating Ligand Bias pathway or to the b-arrestin signaling pathway. Our unan- The experimentally measured ligand bias factor depends on the swered question has been, how do the various biased agonists 21 ligand affinity (KA ) and its efficacy (t) toward a specific signaling influence the role of these structural determinants in biasing pathway. The bias factor is calculated with respect to a reference b the signaling to effect -arrestin signaling or G-protein ligand using the Black and Leff operational model (Kenakin et al., signaling? Here we have developed a computational method 2012). Because macroscopic properties such as ligand potency and at ASPET Journals on October 1, 2021 to calculate the ligand bias ahead of experiments, which would coupling efficacy are still intractable computationally, we developed a aid
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