Discovery of Protease-Activated Receptor 4 (PAR4)-Tethered Ligand Antagonists Using Ultralarge Virtual Screening

Here, we demonstrate a structure-based small molecule virtual screening and lead optimization pipeline using a homology model of a difficult-to-drug G-protein-coupled receptor (GPCR) target. Protease-activated receptor 4 (PAR4) is activated by thrombin cleavage, revealing a tethered ligand that activates the receptor, making PAR4 a challenging target. A virtual screen of a make-on-demand chemical library yielded a one-hit compound. From the single-hit compound, we developed a novel series of PAR4 antagonists. Subsequent lead optimization via simultaneous virtual library searches and structure-based rational design efforts led to potent antagonists of thrombin-induced activation. Interestingly, this series of antagonists was active against PAR4 activation by the native protease thrombin cleavage but not the synthetic PAR4 agonist peptide AYPGKF.

Rosetta's Predictive Ability for Low-Affinity Ligand Binding in Fragment-Based Drug Discovery

Fragment-based drug discovery begins with the identification of small molecules with a molecular weight of usually less than 250 Da which weakly bind to the protein of interest. This technique is challenging for computational docking methods as binding is determined by only a few specific interactions. Inaccuracies in the energy function or slight deviations in the docking pose can lead to the prediction of incorrect binding or difficulties in ranking fragments in in silico screening. Here, we test RosettaLigand by docking a series of fragments to a cysteine-depleted variant of the TIM-barrel protein, HisF (UniProtKB Q9X0C6). We compare the computational results with experimental NMR spectroscopy screens. NMR spectroscopy gives details on binding affinities of individual ligands, which allows assessment of the ligand-ranking ability using RosettaLigand and also provides feedback on the location of the binding pocket, which serves as a reliable test of RosettaLigand's ability to identify plausible binding poses. From a library screen of 3456 fragments, we identified a set of 31 ligands with intrinsic affinities to HisF with dissociation constants as low as 400 μM. The same library of fragments was blindly screened in silico. RosettaLigand was able to rank binders before non-binders with an area under the curve of the receiver operating characteristics of 0.74. The docking poses observed for binders agreed with the binding pocket identified by NMR chemical shift perturbations for all fragments. Taken together, these results provide a baseline performance of RosettaLigand in a fragment-based drug discovery setting.

Structure, function and pharmacology of human itch GPCRs

The MRGPRX family of receptors (MRGPRX1-4) is a family of mas-related G-protein-coupled receptors that have evolved relatively recently1. Of these, MRGPRX2 and MRGPRX4 are key physiological and pathological mediators of itch and related mast cell-mediated hypersensitivity reactions2-5. MRGPRX2 couples to both Gi and Gq in mast cells6. Here we describe agonist-stabilized structures of MRGPRX2 coupled to Gi1 and Gq in ternary complexes with the endogenous peptide cortistatin-14 and with a synthetic agonist probe, respectively, and the development of potent antagonist probes for MRGPRX2. We also describe a specific MRGPRX4 agonist and the structure of this agonist in a complex with MRGPRX4 and Gq. Together, these findings should accelerate the structure-guided discovery of therapeutic agents for pain, itch and mast cell-mediated hypersensitivity.

Molecular basis for the evolved instability of a human G-protein coupled receptor

Membrane proteins are prone to misfolding and degradation. This is particularly true for mammalian forms of the gonadotropin-releasing hormone receptor (GnRHR). Although they function at the plasma membrane, mammalian GnRHRs accumulate within the secretory pathway. Their apparent instability is believed to have evolved through selection for attenuated GnRHR activity. Nevertheless, the molecular basis of this adaptation remains unclear. We show that adaptation coincides with a C-terminal truncation that compromises the translocon-mediated membrane integration of its seventh transmembrane domain (TM7). We also identify a series of polar residues in mammalian GnRHRs that compromise the membrane integration of TM2 and TM6. Reverting a lipid-exposed polar residue in TM6 to an ancestral hydrophobic residue restores expression with no impact on function. Evolutionary trends suggest variations in the polarity of this residue track with reproductive phenotypes. Our findings suggest that the marginal energetics of cotranslational folding can be exploited to tune membrane protein fitness.

Integral membrane proteins are prone to misfolding, especially mammalian gonadotropin-releasing hormone receptors (GnRHRs). Chamness et al. show that the evolved instability of mammalian GnRHRs stems from adaptive modifications that disrupt translocon-mediated membrane integration, suggesting that membrane protein misfolding can be exploited to tune fitness.

Computational redesign of a fluorogen activating protein with Rosetta

The use of unnatural fluorogenic molecules widely expands the pallet of available genetically encoded fluorescent imaging tools through the design of fluorogen activating proteins (FAPs). While there is already a handful of such probes available, each of them went through laborious cycles of in vitro screening and selection. Computational modeling approaches are evolving incredibly fast right now and are demonstrating great results in many applications, including de novo protein design. It suggests that the easier task of fine-tuning the fluorogen-binding properties of an already functional protein in silico should be readily achievable. To test this hypothesis, we used Rosetta for computational ligand docking followed by protein binding pocket redesign to further improve the previously described FAP DiB1 that is capable of binding to a BODIPY-like dye M739. Despite an inaccurate initial docking of the chromophore, the incorporated mutations nevertheless improved multiple photophysical parameters as well as the overall performance of the tag. The designed protein, DiB-RM, shows higher brightness, localization precision, and apparent photostability in protein-PAINT super-resolution imaging compared to its parental variant DiB1. Moreover, DiB-RM can be cleaved to obtain an efficient split system with enhanced performance compared to a parental DiB-split system. The possible reasons for the inaccurate ligand binding pose prediction and its consequence on the outcome of the design experiment are further discussed.

Computational approaches have recently made significant progress in the protein engineering field evolving from a tool for helping experimentalists to prioritize or short-list mutations for testing to being capable of making fully reliable predictions. However, not all the fields of protein modeling are evolving at a similar pace. That is why evaluating the capabilities of computational tools on different tasks is important to provide other scientists with up-to-date information on the state of the field. Here we tested the performance of Rosetta (one of the leading macromolecule modeling tools) in improving small molecule-binding proteins. We successfully redesigned a fluorogen binding protein DiB1 –a protein that binds a non-fluorescent molecule and enforces its fluorescence in the obtained complex–for improved brightness and better performance in super-resolution imaging. Our results suggest that such tasks can be already achieved without laborious library screenings. However, the flexibility of the proteins might still be underestimated during standard modeling protocols and should be closely evaluated.

Viewpoints on the First Transatlantic GPCR Symposium for Early-Career Investigators

In July 2021, we organized a virtual symposium aimed at early-career investigators (ECIs) in G protein-coupled receptor (GPCR) research: the first Transatlantic ECI GPCR Symposium. Here, we discuss the proceedings of this symposium and the unique networking events with GPCR leaders including the Nobel Laureates Dr. Robert Lefkowitz and Dr. Brian Kobilka.

Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design

Structure-based antibody and antigen design has advanced greatly in recent years, due not only to the increasing availability of experimentally determined structures but also to improved computational methods for both prediction and design. Constant improvements in performance within the Rosetta software suite for biomolecular modeling have given rise to a greater breadth of structure prediction, including docking and design application cases for antibody and antigen modeling. Here, we present an overview of current protocols for antibody and antigen modeling using Rosetta and exemplify those by detailed tutorials originally developed for a Rosetta workshop at Vanderbilt University. These tutorials cover antibody structure prediction, docking, and design and antigen design strategies, including the addition of glycans in Rosetta. We expect that these materials will allow novice users to apply Rosetta in their own projects for modeling antibodies and antigens.

Macromolecular modeling and design in Rosetta: recent methods and frameworks

The Rosetta software for macromolecular modeling, docking and design is extensively used in laboratories worldwide. During two decades of development by a community of laboratories at more than 60 institutions, Rosetta has been continuously refactored and extended. Its advantages are its performance and interoperability between broad modeling capabilities. Here we review tools developed in the last 5 years, including over 80 methods. We discuss improvements to the score function, user interfaces and usability. Rosetta is available at http://www.rosettacommons.org.

Comparative modeling and docking of chemokine-receptor interactions with Rosetta

Chemokine receptors are a subset of G protein-coupled receptors defined by the distinct property of binding small protein ligands in the chemokine family. Chemokine receptors recognize their ligands by a mechanism that is distinct from other class A GPCRs that bind peptides or small molecules. For this reason, structural information on other ligand-GPCR interactions are only indirectly relevant to understanding the chemokine receptor interface. Additionally, the experimentally determined structures of chemokine-GPCR complexes represent less than 3% of the known interactions of this complex, multi-ligand/multi-receptor network. To enable predictive modeling of the remaining 97% of interactions, a general in silico protocol was designed to utilize existing chemokine receptor crystal structures, co-crystal structures, and NMR ensembles of chemokines bound to receptor fragments. This protocol was benchmarked on the ability to predict each of the three published co-crystal structures, while being blinded to the target structure. Averaging ensembles selected from the top-ranking models reproduced up to 84% of the intermolecular contacts found in the crystal structure, with the lowest Cα-RMSD of the complex at 3.3 Å. The chemokine receptor N-terminus, unresolved in crystal structures, was included in the modeling and recapitulates contacts with known sulfotyrosine binding pockets seen in structures derived from experimental NMR data. This benchmarking experiment suggests that realistic homology models of chemokine-GPCR complexes can be generated by leveraging current structural data.

Modeling the complete chemokine-receptor interaction

Chemokines are soluble, secreted proteins that induce chemotaxis of leukocytes and other cells. Migratory cells can sense the chemokine concentration gradient following chemokine binding and activation of chemokine receptors, a subset of the G protein-coupled receptor (GPCR) superfamily. Chemokine receptor signaling plays a central role in cell migration during inflammatory responses as well as in cancer and other diseases. Given their important role in mediating essential pathologic and physiologic processes, chemokines and their receptors are attractive targets for therapeutic development. A better understanding of the molecular basis of chemokine-GPCR interactions will aid in the understanding of the mechanistic basis for chemokine function in disease-related processes, as well as aid in the design of new therapeutics. High resolution protein structures are critical for determining these mechanisms and investigating the interactions between approximately 50 chemokines and 20 chemokine receptors. Currently, three unique structures of chemokine-GPCR complexes have been determined and have greatly broadened our knowledge of this large protein-protein interaction. While these structures represent only a small fraction of clinically relevant chemokines and receptors, they can be exploited as scaffolds for homology modeling to understand the chemokine-GPCR interactions. This chapter presents a specialized methodology to construct and validate models of chemokine-GPCR complexes using the Rosetta software suite.

Improved in Vitro Folding of the Y2 G Protein-Coupled Receptor into Bicelles

Prerequisite for structural studies on G protein-coupled receptors is the preparation of highly concentrated, stable, and biologically active receptor samples in milligram amounts of protein. Here, we present an improved protocol for Escherichia coli expression, functional refolding, and reconstitution into bicelles of the human neuropeptide Y receptor type 2 (Y₂R) for solution and solid-state NMR experiments. The isotopically labeled receptor is expressed in inclusion bodies and purified using SDS. We studied the details of an improved preparation protocol including the in vitro folding of the receptor, e.g., the native disulfide bridge formation, the exchange of the denaturating detergent SDS, and the functional reconstitution into bicelle environments of varying size. Full pharmacological functionality of the Y₂R preparation was shown by a ligand affinity of 4 nM and G-protein activation. Further, simple NMR experiments are used to test sample quality in high micromolar concentration.

Protocols for Molecular Modeling with Rosetta3 and RosettaScripts

Previously, we published an article providing an overview of the Rosetta suite of biomacromolecular modeling software and a series of step-by-step tutorials [Kaufmann, K. W., et al. (2010) Biochemistry 49, 2987–2998]. The overwhelming positive response to this publication we received motivates us to here share the next iteration of these tutorials that feature de novo folding, comparative modeling, loop construction, protein docking, small molecule docking, and protein design. This updated and expanded set of tutorials is needed, as since 2010 Rosetta has been fully redesigned into an object-oriented protein modeling program Rosetta3. Notable improvements include a substantially improved energy function, an XML-like language termed “RosettaScripts” for flexibly specifying modeling task, new analysis tools, the addition of the TopologyBroker to control conformational sampling, and support for multiple templates in comparative modeling. Rosetta’s ability to model systems with symmetric proteins, membrane proteins, noncanonical amino acids, and RNA has also been greatly expanded and improved.

A mutation deleting sequences encoding the amino terminus of human cytomegalovirus UL84 impairs interaction with UL44 and capsid localization

Protein-protein interactions are required for many biological functions. Previous work has demonstrated an interaction between the human cytomegalovirus DNA polymerase subunit UL44 and the viral replication factor UL84. In this study, glutathione S-transferase pulldown assays indicated that residues 1 to 68 of UL84 are both necessary and sufficient for efficient interaction of UL84 with UL44 in vitro. We created a mutant virus in which sequences encoding these residues were deleted. This mutant displayed decreased virus replication compared to wild-type virus. Immunoprecipitation assays showed that the mutation decreased but did not abrogate association of UL84 with UL44 in infected cell lysate, suggesting that the association in the infected cell can involve other protein-protein interactions. Further immunoprecipitation assays indicated that IRS1, TRS1, and nucleolin are candidates for such interactions in infected cells. Quantitative real-time PCR analysis of viral DNA indicated that the absence of the UL84 amino terminus does not notably affect viral DNA synthesis. Western blotting experiments and pulse labeling of infected cells with [(35)S]methionine demonstrated a rather modest downregulation of levels of multiple proteins and particularly decreased levels of the minor capsid protein UL85. Electron microscopy demonstrated that viral capsids assemble but are mislocalized in nuclei of cells infected with the mutant virus, with fewer cytoplasmic capsids detected. In sum, deletion of the sequences encoding the amino terminus of UL84 affects interaction with UL44 and virus replication unexpectedly, not viral DNA synthesis. Mislocalization of viral capsids in infected cell nuclei likely contributes to the observed decrease in virus replication.

Erythropoietic protoporphyria with hepatic cirrhosis

Cholestatic jaundice and rapidly deteriorating hepatic function developed in a 19-year-old man with a lifelong history of photosensitivity. Laboratory studies revealed the characteristic increased erythrocyte and fecal protoporphyrin levels of erythropoietic protoporphyria. Progressive hepatic failure was treated by orthotopic liver transplantation six months after the first clinical indication of hepatic dysfunction. Characteristic light microscopic, fluorescence microscopic, and electron microscopic findings of erythropoietic protoporphyria were present in skin and liver. Four weeks after liver transplantation, the patient died of disseminated candidiasis. At autopsy, the donor liver had no microscopic evidence of protoporphyrin accumulation, although tissue protoporphyrin levels were mildly elevated.