Exploiting high-energy hydration sites for the discovery of potent peptide aldehyde inhibitors of the SARS-CoV-2 main protease with cellular antiviral activity.

Small-molecule antivirals that prevent the replication of the SARS-CoV-2 virus by blocking the enzymatic activity of its main protease (Mpro) are and will be a tenet of pandemic preparedness. However, the peptidic nature of such compounds often precludes the design of compounds within favorable physical property ranges, limiting cellular activity. Here we describe the discovery of peptide aldehyde Mpro inhibitors with potent enzymatic and cellular antiviral activity. This structure-activity relationship (SAR) exploration was guided by the use of calculated hydration site thermodynamic maps (WaterMap) to drive potency via displacement of waters from high-energy sites. Thousands of diverse compounds were designed to target these high-energy hydration sites and then prioritized for synthesis by physics- and structure-based Free-Energy Perturbation (FEP+) simulations, which accurately predicted biochemical potencies. This approach ultimately led to the rapid discovery of lead compounds with unique SAR that exhibited potent enzymatic and cellular activity with excellent pan-coronavirus coverage.

Benchmarking Refined and Unrefined AlphaFold2 Structures for Hit Discovery.

The recently developed AlphaFold2 (AF2) algorithm predicts proteins' 3D structures from amino acid sequences. The open AlphaFold protein structure database covers the complete human proteome. Using an industry-leading molecular docking method (Glide), we investigated the virtual screening performance of 37 common drug targets, each with an AF2 structure and known holo and apo structures from the DUD-E data set. In a subset of 27 targets where the AF2 structures are suitable for refinement, the AF2 structures show comparable early enrichment of known active compounds (avg. EF 1%: 13.0) to apo structures (avg. EF 1%: 11.4) while falling behind early enrichment of the holo structures (avg. EF 1%: 24.2). With an induced-fit protocol (IFD-MD), we can refine the AF2 structures using an aligned known binding ligand as the template to improve the performance in structure-based virtual screening (avg. EF 1%: 18.9). Glide-generated docking poses of known binding ligands can also be used as templates for IFD-MD, achieving similar improvements (avg. EF 1% 18.0). Thus, with proper preparation and refinement, AF2 structures show considerable promise for in silico hit identification.

Potency- and Selectivity-Enhancing Mutations of Conotoxins for Nicotinic Acetylcholine Receptors Can Be Predicted Using Accurate Free-Energy Calculations.

Nicotinic acetylcholine receptor (nAChR) subtypes are key drug targets, but it is challenging to pharmacologically differentiate between them because of their highly similar sequence identities. Furthermore, α-conotoxins (α-CTXs) are naturally selective and competitive antagonists for nAChRs and hold great potential for treating nAChR disorders. Identifying selectivity-enhancing mutations is the chief aim of most α-CTX mutagenesis studies, although doing so with traditional docking methods is difficult due to the lack of α-CTX/nAChR crystal structures. Here, we use homology modeling to predict the structures of α-CTXs bound to two nearly identical nAChR subtypes, α3ß2 and α3ß4, and use free-energy perturbation (FEP) to re-predict the relative potency and selectivity of α-CTX mutants at these subtypes. First, we use three available crystal structures of the nAChR homologue, acetylcholine-binding protein (AChBP), and re-predict the relative affinities of twenty point mutations made to the α-CTXs LvIA, LsIA, and GIC, with an overall root mean square error (RMSE) of 1.08 ± 0.15 kcal/mol and an R2 of 0.62, equivalent to experimental uncertainty. We then use AChBP as a template for α3ß2 and α3ß4 nAChR homology models bound to the α-CTX LvIA and re-predict the potencies of eleven point mutations at both subtypes, with an overall RMSE of 0.85 ± 0.08 kcal/mol and an R2 of 0.49. This is significantly better than the widely used molecular mechanics-generalized born/surface area (MM-GB/SA) method, which gives an RMSE of 1.96 ± 0.24 kcal/mol and an R2 of 0.06 on the same test set. Next, we demonstrate that FEP accurately classifies α3ß2 nAChR selective LvIA mutants while MM-GB/SA does not. Finally, we use FEP to perform an exhaustive amino acid mutational scan of LvIA and predict fifty-two mutations of LvIA to have greater than 100X selectivity for the α3ß2 nAChR. Our results demonstrate the FEP is well-suited to accurately predict potency- and selectivity-enhancing mutations of α-CTXs for nAChRs and to identify alternative strategies for developing selective α-CTXs.

EPHA2 mutations with oncogenic characteristics in squamous cell lung cancer and malignant pleural mesothelioma.

Squamous cell carcinoma (SCC) and malignant pleural mesothelioma (MPM) are thoracic malignancies with very poor prognosis and limited treatment options. It is an established fact that most of the solid tumors have overexpression of EPHA2 receptor tyrosine kinase. EPHA2 is known to exhibit opposing roles towards cancer progression. It functions in inhibiting cancer survival and migration via a ligand and tyrosine kinase dependent signaling (Y772). Whereas it is known to promote tumor progression and cell migration through a ligand-independent signaling (S897). We analyzed the expression profile and mutational status of the ephrin receptor A2 (EPHA2) in SCC and MPM cell lines and primary patient specimens. The EPHA2 receptor was found to be either overexpressed, mutated or amplified in SCC and MPM. In particular, the EPHA2 mutants A859D and T647M were interesting to explore, A859D Y772 dead mutant exhibited lower levels of phosphorylation at Y772 compared to T647M mutant. Molecular Dynamics simulations studies suggested that differential changes in conformation might form the structural basis for differences in the level of EPHA2 activation. Consequently, A859D mutant cells exhibited increased proliferation as well as cell migration compared to controls and T647M mutant. Kinomics analysis demonstrated that the STAT3 and PDGF pathways were upregulated whereas signaling through CBL was suppressed. Considered together, the present work has uncovered the oncogenic characteristics of EPHA2 mutations in SSC and MPM reinstating the dynamics of different roles of EPHA2 in cancer. This study also suggests that a combination of doxazosin and other EPHA2 inhibitors directed to inhibit the pertinent signaling components may be a novel therapeutic strategy for MPM and Non-small cell lung cancer patients who have either EPHA2 or CBL alterations.

How Does the Proliferating Cell Nuclear Antigen Modulate Binding Specificity to Multiple Partner Proteins?

Proliferating cell nuclear antigen (PCNA) is a member of the family of sliding clamp proteins that serves as a clamp during DNA repair, DNA replication, cell cycle control, and multiple forms of chromatin modification. PCNA functions as a homotrimer and complexes with multiple proteins in order to carry out each of these varied functions. PCNA binds to different partner proteins in the same region of its structure, called the " interdomain connecting loop", but with different affinities. This interdomain connecting loop is an intrinsically disordered region that takes different conformations when binding to different partner proteins. In this work, we performed all-atom molecular dynamics simulations on PCNA trimer unbound to any partner protein, PCNA bound to peptides from different partner proteins, and PCNA bound to the full Fen 1 protein in two different conformations. Using this massive amount of simulation results, we analyzed whether PCNA in its free trimeric form samples conformations that are similar to those when it is bound to different partner proteins. We observed that PCNA samples many of these peptide-bound conformations even when not bound to the peptides and selects specific conformations when binding to partner proteins. We also identified PCNA-peptide interactions formed in the peptide bound simulation that play a crucial role in complex formation. The calculated binding energies correlate well with the measured binding affinities of various peptides to PCNA. Lastly, we studied the internal dynamics of PCNA and propose a mechanism through which PCNA recruits binding partners. This work highlights the functional role of intrinsically disordered regions in multifunctional proteins such as PCNA.

Cooperation of neurotrophin receptor TrkB and Her2 in breast cancer cells facilitates brain metastases.

BACKGROUND: Patients with primary breast cancer that is positive for human epidermal growth factor receptor 2 (Her2+) have a high risk of developing metastases in the brain. Despite gains with systemic control of Her2+ disease using molecular therapies, brain metastases remain recalcitrant to therapeutic discovery. The clinical predilection of Her2+ breast cancer cells to colonize the brain likely relies on paracrine mechanisms. The neural niche poses unique selection pressures, and neoplastic cells that utilize the brain microenvironment may have a survival advantage. METHODS: Tropomyosin-related kinase B (TrkB), Her2, and downstream targets were analyzed in primary breast cancer, breast-to-brain metastasis (BBM) tissues, and tumor-derived cell lines using quantitative real-time PCR, western blot, and immunohistochemical assessment. TrkB function on BBM was confirmed with intracranial, intracardiac, or mammary fat pad xenografts in non-obese diabetic/severe combined immunodeficiency mice. The function of brain-derived neurotrophic factor (BDNF) on cell proliferation and TrkB/Her2 signaling and interactions were confirmed using selective shRNA knockdown and selective inhibitors. The physical interaction of Her2-TrkB was analyzed using electron microscopy, co-immunoprecipitation, and in silico analysis. Dual targeting of Her2 and TrkB was analyzed using clinically utilized treatments. RESULTS: We observed that patient tissues and cell lines derived from Her2+ human BBM displayed increased activation of TrkB, a neurotrophin receptor. BDNF, an extracellular neurotrophin, with roles in neuronal maturation and homeostasis, specifically binds to TrkB. TrkB knockdown in breast cancer cells led to decreased frequency and growth of brain metastasis in animal models, suggesting that circulating breast cancer cells entering the brain may take advantage of paracrine BDNF-TrkB signaling for colonization. In addition, we investigated a possible interaction between TrkB and Her2 receptors on brain metastatic breast cancer cells, and found that BDNF phosphorylated both its cognate TrkB receptor and the Her2 receptor in brain metastatic breast cancer cells. CONCLUSION: Collectively, our findings suggest that heterodimerization of Her2 and TrkB receptors gives breast cancer cells a survival advantage in the brain and that dual inhibition of these receptors may hold therapeutic potential.

CXCR3 antagonist VUF10085 binds to an intrahelical site distinct from that of the broad spectrum antagonist TAK-779.

BACKGROUND AND PURPOSE: The chemokine receptor CXCR3 is implicated in a variety of clinically important diseases, notably rheumatoid arthritis and atherosclerosis. Consequently, antagonists of CXCR3 are of therapeutic interest. In this study, we set out to characterize binding sites of the specific low MW CXCR3 antagonist VUF10085 and the broad spectrum antagonist TAK-779 which blocks CXCR3 along with CCR2 and CCR5. EXPERIMENTAL APPROACH: Molecular modelling of CXCR3, followed by virtual ligand docking, highlighted several CXCR3 residues likely to contact either antagonist, notably a conserved aspartate in helix 2 (Asp-112(2:63) ), which was postulated to interact with the quaternary nitrogen of TAK-779. Validation of modelling was carried out by site-directed mutagenesis of CXCR3, followed by assays of cell surface expression, ligand binding and receptor activation. KEY RESULTS: Mutation of Asn-132(3.33) , Phe-207 and Tyr-271(6.51) within CXCR3 severely impaired both ligand binding and chemotactic responses, suggesting that these residues are critical for maintenance of a functional CXCR3 conformation. Contrary to our hypothesis, mutation of Asp-112(2:63) had no observable effects on TAK-779 activity, but clearly decreased the antagonist potency of VUF 10085. Likewise, mutations of Phe-131(3.32) , Ile-279(6.59) and Tyr-308(7.43) were well tolerated and were critical for the antagonist activity of VUF 10085 but not for that of TAK-779. CONCLUSIONS AND IMPLICATIONS: This more detailed definition of a binding pocket within CXCR3 for low MW antagonists should facilitate the rational design of newer CXCR3 antagonists, with obvious clinical potential.

Computational method to identify druggable binding sites that target protein-protein interactions.

Protein-protein interactions are implicated in the pathogenesis of many diseases and are therefore attractive but challenging targets for drug design. One of the challenges in development is the identification of potential druggable binding sites in protein interacting interfaces. Identification of interface surfaces can greatly aid rational drug design of small molecules inhibiting protein-protein interactions. In this work, starting from the structure of a free monomer, we have developed a ligand docking based method, called "FindBindSite" (FBS), to locate protein-protein interacting interface regions and potential druggable sites in this interface. FindBindSite utilizes the results from docking a small and diverse library of small molecules to the entire protein structure. By clustering regions with the highest docked ligand density from FBS, we have shown that these high ligand density regions strongly correlate with the known protein-protein interacting surfaces. We have further predicted potential druggable binding sites on the protein surface using FBS, with druggability being defined as the site with high density of ligands docked. FBS shows a hit rate of 71% with high confidence and 93% with lower confidence for the 41 proteins used for predicting druggable binding sites on the protein-protein interface. Mining the regions of lower ligand density that are contiguous with the high scoring high ligand density regions from FBS, we were able to map 70% of the protein-protein interacting surface in 24 out of 41 structures tested. We also observed that FBS has limited sensitivity to the size and nature of the small molecule library used for docking. The experimentally determined hotspot residues for each protein-protein complex cluster near the best scoring druggable binding sites identified by FBS. These results validate the ability of our technique to identify druggable sites within protein-protein interface regions that have the maximal possibility of interface disruption.

Human breast cancer metastases to the brain display GABAergic properties in the neural niche.

Dispersion of tumors throughout the body is a neoplastic process responsible for the vast majority of deaths from cancer. Despite disseminating to distant organs as malignant scouts, most tumor cells fail to remain viable after their arrival. The physiologic microenvironment of the brain must become a tumor-favorable microenvironment for successful metastatic colonization by circulating breast cancer cells. Bidirectional interplay of breast cancer cells and native brain cells in metastasis is poorly understood and rarely studied. We had the rare opportunity to investigate uncommonly available specimens of matched fresh breast-to-brain metastases tissue and derived cells from patients undergoing neurosurgical resection. We hypothesized that, to metastasize, breast cancers may escape their normative genetic constraints by accommodating and coinhabiting the neural niche. This acquisition or expression of brain-like properties by breast cancer cells could be a malignant adaptation required for brain colonization. Indeed, we found breast-to-brain metastatic tissue and cells displayed a GABAergic phenotype similar to that of neuronal cells. The GABAA receptor, GABA transporter, GABA transaminase, parvalbumin, and reelin were all highly expressed in breast cancer metastases to the brain. Proliferative advantage was conferred by the ability of breast-to-brain metastases to take up and catabolize GABA into succinate with the resultant formation of NADH as a biosynthetic source through the GABA shunt. The results suggest that breast cancers exhibit neural characteristics when occupying the brain microenvironment and co-opt GABA as an oncometabolite.

Critical analysis of the successes and failures of homology models of G protein-coupled receptors.

We present a critical assessment of the performance of our homology model refinement method for G protein-coupled receptors (GPCRs), called LITICon that led to top ranking structures in a recent structure prediction assessment GPCRDOCK2010. GPCRs form the largest class of drug targets for which only a few crystal structures are currently available. Therefore, accurate homology models are essential for drug design in these receptors. We submitted five models each for human chemokine CXCR4 (bound to small molecule IT1t and peptide CVX15) and dopamine D3DR (bound to small molecule eticlopride) before the crystal structures were published. Our models in both CXCR4/IT1t and D3/eticlopride assessments were ranked first and second, respectively, by ligand RMSD to the crystal structures. For both receptors, we developed two types of protein models: homology models based on known GPCR crystal structures, and ab initio models based on the prediction method MembStruk. The homology-based models compared better to the crystal structures than the ab initio models. However, a robust refinement procedure for obtaining high accuracy structures is needed. We demonstrate that optimization of the helical tilt, rotation, and translation is vital for GPCR homology model refinement. As a proof of concept, our in-house refinement program LITiCon captured the distinct orientation of TM2 in CXCR4, which differs from that of adrenoreceptors. These findings would be critical for refining GPCR homology models in future.

Identification of anti-malarial compounds as novel antagonists to chemokine receptor CXCR4 in pancreatic cancer cells.

Despite recent advances in targeted therapies, patients with pancreatic adenocarcinoma continue to have poor survival highlighting the urgency to identify novel therapeutic targets. Our previous investigations have implicated chemokine receptor CXCR4 and its selective ligand CXCL12 in the pathogenesis and progression of pancreatic intraepithelial neoplasia and invasive pancreatic cancer; hence, CXCR4 is a promising target for suppression of pancreatic cancer growth. Here, we combined in silico structural modeling of CXCR4 to screen for candidate anti-CXCR4 compounds with in vitro cell line assays and identified NSC56612 from the National Cancer Institute's (NCI) Open Chemical Repository Collection as an inhibitor of activated CXCR4. Next, we identified that NSC56612 is structurally similar to the established anti-malarial drugs chloroquine and hydroxychloroquine. We evaluated these compounds in pancreatic cancer cells in vitro and observed specific antagonism of CXCR4-mediated signaling and cell proliferation. Recent in vivo therapeutic applications of chloroquine in pancreatic cancer mouse models have demonstrated decreased tumor growth and improved survival. Our results thus provide a molecular target and basis for further evaluation of chloroquine and hydroxychloroquine in pancreatic cancer. Historically safe in humans, chloroquine and hydroxychloroquine appear to be promising agents to safely and effectively target CXCR4 in patients with pancreatic cancer.

Small molecule chemokine mimetics suggest a molecular basis for the observation that CXCL10 and CXCL11 are allosteric ligands of CXCR3.

BACKGROUND AND PURPOSE: The chemokine receptor CXCR3 directs migration of T-cells in response to the ligands CXCL9/Mig, CXCL10/IP-10 and CXCL11/I-TAC. Both ligands and receptors are implicated in the pathogenesis of inflammatory disorders, including atherosclerosis and rheumatoid arthritis. Here, we describe the molecular mechanism by which two synthetic small molecule agonists activate CXCR3. EXPERIMENTAL APPROACH: As both small molecules are basic, we hypothesized that they formed electrostatic interactions with acidic residues within CXCR3. Nine point mutants of CXCR3 were generated in which an acidic residue was mutated to its amide counterpart. Following transient expression, the ability of the constructs to bind and signal in response to natural and synthetic ligands was examined. KEY RESULTS: The CXCR3 mutants D112N, D195N and E196Q were efficiently expressed and responsive in chemotaxis assays to CXCL11 but not to CXCL10 or to either of the synthetic agonists, confirmed with radioligand binding assays. Molecular modelling of both CXCL10 and CXCR3 suggests that the small molecule agonists mimic a region of the '30s loop' (residues 30-40 of CXCL10) which interacts with the intrahelical CXCR3 residue D112, leading to receptor activation. D195 and E196 are located in the second extracellular loop and form putative intramolecular salt bridges required for a CXCR3 conformation that recognizes CXCL10. In contrast, CXCL11 recognition by CXCR3 is largely independent of these residues. CONCLUSION AND IMPLICATIONS: We provide here a molecular basis for the observation that CXCL10 and CXCL11 are allosteric ligands of CXCR3. Such findings may have implications for the design of CXCR3 antagonists.

Ligand-stabilized conformational states of human beta(2) adrenergic receptor: insight into G-protein-coupled receptor activation.

G-protein-coupled receptors (GPCRs) are known to exist in dynamic equilibrium between inactive- and several active-state conformations, even in the absence of a ligand. Recent experimental studies on the beta(2) adrenergic receptor (beta(2)AR) indicate that structurally different ligands with varying efficacies trigger distinct conformational changes and stabilize different receptor conformations. We have developed a computational method to study the ligand-induced rotational orientation changes in the transmembrane helices of GPCRs. This method involves a systematic spanning of the rotational orientation of the transmembrane helices (TMs) that are in the vicinity of the ligand for predicting the helical rotations that occur on ligand binding. The predicted ligand-stabilized receptor conformations are characterized by a simultaneous lowering of the ligand binding energy and a significant gain in interhelical and receptor-ligand hydrogen bonds. Using the beta(2)AR as a model, we show that the receptor conformational state depends on the structure and efficacy of the ligand for a given signaling pathway. We have studied the ligand-stabilized receptor conformations of five different ligands, a full agonist, norepinephrine; a partial agonist, salbutamol; a weak partial agonist, dopamine; a very weak agonist, catechol; and an inverse agonist, ICI-115881. The predicted ligand-stabilized receptor models correlate well with the experimentally observed conformational switches in beta(2)AR, namely, the breaking of the ionic lock between R131(3.50) at the intracellular end of TM3 (part of the DRY motif) and E268(6.30) on TM6, and the rotamer toggle switch on W286(6.48) on TM6. In agreement with trp-bimane quenching experiments, we found that norepinephrine and dopamine break the ionic lock and engage the rotamer toggle switch, whereas salbutamol, a noncatechol partial agonist only breaks the ionic lock, and the weak agonist catechol only engages the rotamer toggle switch. Norepinephrine and dopamine occupy the same binding region, between TM3, TM5, and TM6, whereas the binding site of salbutamol is shifted toward TM4. Catechol binds deeper into the protein cavity compared to the other ligands, making contact with TM5 and TM6. A part of the catechol binding site overlaps with those of dopamine and norepinephrine but not with that of salbutamol. Virtual ligand screening on 10,060 ligands on the norepinephrine-stabilized receptor conformation shows an enrichment of 38% compared to ligand unbound receptor conformation. These results show that ligand-induced conformational changes are important for developing functionally specific drugs that will stabilize a particular receptor conformation. These studies represent the first step toward a more universally applicable computational method for studying ligand efficacy and GPCR activation.