Osteocalcin binds to a GPRC6A Venus fly trap allosteric site to positively modulate GPRC6A signaling.

GPRC6A, a member of the Family C G-protein coupled receptors, regulates energy metabolism and sex hormone production and is activated by diverse ligands, including cations, L-amino acids, the osteocalcin (Ocn) peptide and the steroid hormone testosterone. We sought a structural framework for the ability of multiple distinct classes of ligands to active GPRC6A. We created a structural model of GPRC6A using Alphafold2. Using this model we explored a putative orthosteric ligand binding site in the bilobed Venus fly trap (VFT) domain of GPRC6A and two positive allosteric modulator (PAM) sites, one in the VFT and the other in the 7 transmembrane (7TM) domain. We provide evidence that Ocn peptides act as a PAM for GPRC6A by binding to a site in the VFT that is distinct from the orthosteric site for calcium and L-amino acids. In agreement with this prediction, alternatively spliced GPRC6A isoforms 2 and 3, which lack regions of the VFT, and mutations in the computationally predicted Ocn binding site, K352E and H355P, prevent Ocn activation of GPRC6A. These observations explain how dissimilar ligands activate GPRC6A and set the stage to develop novel molecules to activate and inhibit this previously poorly understood receptor.

GPRC6A is a Potential Therapeutic Target for Metformin Regulation of Glucose Homeostasis in Mice.

Understanding the mechanism of metformin actions in treating type 2 diabetes is limited by an incomplete knowledge of the specific protein targets mediating its metabolic effects. Metformin has structural similarities to L-Arginine (2-amino-5-guanidinopentanoic acid), which is a ligand for GPRC6A, a Family C G-protein coupled receptor that regulates energy metabolism. Ligand activation of GPRC6A results in lowering of blood glucose and other metabolic changes resembling the therapeutic effect of metformin. In the current study, we tested if metformin activates GPRC6A. We used Alphafold2 to develop a structural model for L-Arginine (L-Arg) binding to the extracellu-lar bilobed venus flytrap domain (VFT) of GPRC6A. We found that metformin docked to the site in the VFT that overlaps the binding site for L-Arg. Metformin resulted in a dose-dependent stimulation of GPRC6A activity in HEK-293 cells transfected with full-length wild-type GPRC6A but not in untransfected control cells. In addition, metformin failed to activate an alternatively spliced GPRC6A isoform lacking the putative binding site in the VFT. More specifically, mutation of the predicted metformin key binding residues Glu170 and Asp303 in the GPRC6A VFT resulted in loss of metformin receptor activation in vitro. The in vivo role of GPRC6A in mediating the effects of metformin was tested in Gprc6a-/- mice. Administration of therapeutic doses of metformin lowered blood glucose levels following a glucose tolerance test in wild-type but not Gprc6a-/- mice. Finally, we EN300, created by adding a carboxymethyl group from L-Arg to the biguanide backbone of metformin. EN300 showed dose-dependent stimulation of GPRC6A activity in vitro with greater potency than L-Arginine, but less than metformin. Thus, we suggest that GPRC6A is a potential molecular target for metformin which may be used to understand the therapeutic actions of metformin and develop novel small molecules to treat T2D.

Structure-Based Identification of Novel Histone Deacetylase 4 (HDAC4) Inhibitors.

Histone deacetylases (HDACs) are important cancer drug targets. Existing FDA-approved drugs target the catalytic pocket of HDACs, which is conserved across subfamilies (classes) of HDAC. However, engineering specificity is an important goal. Herein, we use molecular modeling approaches to identify and target potential novel pockets specific to Class IIA HDAC-HDAC4 at the interface between HDAC4 and the transcriptional corepressor component protein NCoR. These pockets were screened using an ensemble docking approach combined with consensus scoring to identify compounds with a different binding mechanism than the currently known HDAC modulators. Binding was compared in experimental assays between HDAC4 and HDAC3, which belong to a different family of HDACs. HDAC4 was significantly inhibited by compound 88402 but not HDAC3. Two other compounds (67436 and 134199) had IC50 values in the low micromolar range for both HDACs, which is comparable to the known inhibitor of HDAC4, SAHA (Vorinostat). However, both of these compounds were significantly weaker inhibitors of HDAC3 than SAHA and thus more selective, albeit to a limited extent. Five compounds exhibited activity on human breast carcinoma and/or urothelial carcinoma cell lines. The present result suggests potential mechanistic and chemical approaches for developing selective HDAC4 modulators.

Comparative Assessment of Pose Prediction Accuracy in RNA-Ligand Docking.

Structure-based virtual high-throughput screening is used in early-stage drug discovery. Over the years, docking protocols and scoring functions for protein-ligand complexes have evolved to improve the accuracy in the computation of binding strengths and poses. In the past decade, RNA has also emerged as a target class for new small-molecule drugs. However, most ligand docking programs have been validated and tested for proteins and not RNA. Here, we test the docking power (pose prediction accuracy) of three state-of-the-art docking protocols on 173 RNA-small molecule crystal structures. The programs are AutoDock4 (AD4) and AutoDock Vina (Vina), which were designed for protein targets, and rDock, which was designed for both protein and nucleic acid targets. AD4 performed relatively poorly. For RNA targets for which a crystal structure of a bound ligand used to limit the docking search space is available and for which the goal is to identify new molecules for the same pocket, rDock performs slightly better than Vina, with success rates of 48% and 63%, respectively. However, in the more common type of early-stage drug discovery setting, in which no structure of a ligand-target complex is known and for which a larger search space is defined, rDock performed similarly to Vina, with a low success rate of ∼27%. Vina was found to have bias for ligands with certain physicochemical properties, whereas rDock performs similarly for all ligand properties. Thus, for projects where no ligand-protein structure already exists, Vina and rDock are both applicable. However, the relatively poor performance of all methods relative to protein-target docking illustrates a need for further methods refinement.

SARS-CoV2 billion-compound docking.

This dataset contains ligand conformations and docking scores for 1.4 billion molecules docked against 6 structural targets from SARS-CoV2, representing 5 unique proteins: MPro, NSP15, PLPro, RDRP, and the Spike protein. Docking was carried out using the AutoDock-GPU platform on the Summit supercomputer and Google Cloud. The docking procedure employed the Solis Wets search method to generate 20 independent ligand binding poses per compound. Each compound geometry was scored using the AutoDock free energy estimate, and rescored using RFScore v3 and DUD-E machine-learned rescoring models. Input protein structures are included, suitable for use by AutoDock-GPU and other docking programs. As the result of an exceptionally large docking campaign, this dataset represents a valuable resource for discovering trends across small molecule and protein binding sites, training AI models, and comparing to inhibitor compounds targeting SARS-CoV-2. The work also gives an example of how to organize and process data from ultra-large docking screens.

Speed vs Accuracy: Effect on Ligand Pose Accuracy of Varying Box Size and Exhaustiveness in AutoDock Vina.

Structure-based virtual high-throughput screening involves docking chemical libraries to targets of interest. A parameter pertinent to the accuracy of the resulting pose is the root mean square deviation (RMSD) from a known crystallographic structure, i. e., the 'docking power'. Here, using a popular algorithm, Autodock Vina, as a model program, we evaluate the effects of varying two common docking parameters: the box size (the size of docking search space) and the exhaustiveness of the global search (the number of independent runs starting from random ligand conformations) on the RMSD from the PDBbind v2017 refined dataset of experimental protein-ligand complexes. Although it is clear that exhaustiveness is an important parameter, there is wide variation in the values used, with variation between 1 and >100. We, therefore, evaluated a combination of cubic boxes of different sizes and five exhaustiveness values (1, 8, 25, 50, 75, 100) within the range of those commonly adopted. The results show that the default exhaustiveness value of 8 performs well overall for most box sizes. In contrast, for all box sizes, but particularly for large boxes, an exhaustiveness value of 1 led to significantly higher median RMSD (mRMSD) values. The docking power was slightly improved with an exhaustiveness of 25, but the mRMSD changes little with values higher than 25. Therefore, although low exhaustiveness is computationally faster, the results are more likely to be far from reality, and, conversely, values >25 led to little improvement at the expense of computational resources. Overall, we recommend users to use at least the default exhaustiveness value of 8 for virtual screening calculations.

Origins of glycan selectivity in streptococcal Siglec-like adhesins suggest mechanisms of receptor adaptation.

Bacterial binding to host receptors underlies both commensalism and pathogenesis. Many streptococci adhere to protein-attached carbohydrates expressed on cell surfaces using Siglec-like binding regions (SLBRs). The precise glycan repertoire recognized may dictate whether the organism is a strict commensal versus a pathogen. However, it is currently not clear what drives receptor selectivity. Here, we use five representative SLBRs and identify regions of the receptor binding site that are hypervariable in sequence and structure. We show that these regions control the identity of the preferred carbohydrate ligand using chimeragenesis and single amino acid substitutions. We further evaluate how the identity of the preferred ligand affects the interaction with glycoprotein receptors in human saliva and plasma samples. As point mutations can change the preferred human receptor, these studies suggest how streptococci may adapt to changes in the environmental glycan repertoire.

Revised Glycemic Index for Diagnosing and Monitoring of Diabetes Mellitus in South Indian Population.

AIM: To find the optimal threshold of fasting plasma glucose (FPG) and glycated hemoglobin (HbA1c) for diagnosis of diabetes mellitus (DM) and to evaluate the association with diabetic retinopathy (DR) in the South Indian population. SETTINGS AND DESIGN: A retrospective population-based study. METHODS AND MATERIALS: A total of 909 newly detected type 2 DM patients were selected from our two previously conducted studies, which include an urban and a rural population of South India. All underwent estimation of fasting, postprandial plasma glucose (PPG), and other biochemical tests. A comprehensive and detailed ophthalmic examination was carried out. The fundi of patients were photographed using 45°, four-field stereoscopic photography. Based on receiver operating characteristic (ROC) curves, sensitivity and specificity were derived. RESULTS:  The optimal cut-off values determined by maximizing the sensitivity and specificity of FPG and HbA1c using the Youden index were ≥ 6.17 mmol/L and ≥ 6.3%, respectively. By distributing the cut-off points into deciles and comparing them to the WHO criteria, we found that our HbA1c level of 6.60% was more than the WHO threshold (6.5%), with higher sensitivity (81.6%) and lower specificity (48.3%). The FPG level of 6.80 mmol/L was lower to the WHO criteria (7 mmol/L) with increased sensitivity (77.0%) and lower specificity (45.7%). Prevalence of DR by HbA1c levels between 6.5% and 6.9% was 15.3%. The prevalence of DR was more in the FPG category between 6.4 and 6.9 mmol/L and ≥ 7.5 mmol/L. CONCLUSION: Our population-based data indicate that for the South Indian population HbA1c value of ≥63 % and FPG value of ≥6.17 mmol/L may be optimal for diagnosing DM with a high level of accuracy and will be useful for the identification of mild and moderate DR.

Hit Expansion of a Noncovalent SARS-CoV-2 Main Protease Inhibitor.

Inhibition of the SARS-CoV-2 main protease (Mpro) is a major focus of drug discovery efforts against COVID-19. Here we report a hit expansion of non-covalent inhibitors of Mpro. Starting from a recently discovered scaffold (The COVID Moonshot Consortium. Open Science Discovery of Oral Non-Covalent SARS-CoV-2 Main Protease Inhibitor Therapeutics. bioRxiv 2020.10.29.339317) represented by an isoquinoline series, we searched a database of over a billion compounds using a cheminformatics molecular fingerprinting approach. We identified and tested 48 compounds in enzyme inhibition assays, of which 21 exhibited inhibitory activity above 50% at 20 µM. Among these, four compounds with IC50 values around 1 µM were found. Interestingly, despite the large search space, the isoquinolone motif was conserved in each of these four strongest binders. Room-temperature X-ray structures of co-crystallized protein-inhibitor complexes were determined up to 1.9 Å resolution for two of these compounds as well as one of the stronger inhibitors in the original isoquinoline series, revealing essential interactions with the binding site and water molecules. Molecular dynamics simulations and quantum chemical calculations further elucidate the binding interactions as well as electrostatic effects on ligand binding. The results help explain the strength of this new non-covalent scaffold for Mpro inhibition and inform lead optimization efforts for this series, while demonstrating the effectiveness of a high-throughput computational approach to expanding a pharmacophore library.

A Model for the Signal Initiation Complex Between Arrestin-3 and the Src Family Kinase Fgr.

Arrestins regulate a wide range of signaling events, most notably when bound to active G protein-coupled receptors (GPCRs). Among the known effectors recruited by GPCR-bound arrestins are Src family kinases, which regulate cellular growth and proliferation. Here, we focus on arrestin-3 interactions with Fgr kinase, a member of the Src family. Previous reports demonstrated that Fgr exhibits high constitutive activity, but can be further activated by both arrestin-dependent and arrestin-independent pathways. We report that arrestin-3 modulates Fgr activity with a hallmark bell-shaped concentration-dependence, consistent with a role as a signaling scaffold. We further demonstrate using NMR spectroscopy that a polyproline motif within arrestin-3 interacts directly with the SH3 domain of Fgr. To provide a framework for this interaction, we determined the crystal structure of the Fgr SH3 domain at 1.9 Å resolution and developed a model for the GPCR-arrestin-3-Fgr complex that is supported by mutagenesis. This model suggests that Fgr interacts with arrestin-3 at multiple sites and is consistent with the locations of disease-associated Fgr mutations. Collectively, these studies provide a structural framework for arrestin-dependent activation of Fgr.

COVID-19 induced ventricular tachycardia storm unmasking a clinically silent cardiomyopathy: a case report.

BACKGROUND: Coronavirus disease (COVID-19) is a systemic illness characterized by raging impact of cytokine storm on multiple organs. This may trigger malignant ventricular arrhythmias and unmask a clinically silent cardiomyopathy. CASE SUMMARY: A 57-year-old gentleman, known case of hyperthyroidism and diabetes, was referred to our emergency department with history of two ventricular tachycardia (VT) episodes requiring direct current cardioversion in last 3 h followed by another episode in our emergency department that was cardioverted. There was no past history of cardiac illness. His 12-lead electrocardiogram (during sinus rhythm) along with screening echocardiography suggested Arrhythmogenic right ventricular cardiomyopathy (ARVC). He was coincidentally found to be COVID-19 positive by reverse transcription-polymerase chain reaction (RT-PCR) as part of our routine screening. However, he had no fever or respiratory complaints. We noted raised systemic inflammatory markers and cardiac troponin T which progressively increased over the next 4 weeks paralleled by an increase in ventricular premature contraction burden and thereafter started decreasing and returned to baseline by 6th week when the patient became COVID-19 negative by RT-PCR. Subsequently, a single-chamber automated implantable cardioverter-defibrillator implantation was done following which there was a transient increase in these biomarkers that subsided spontaneously. The patient is asymptomatic during 6 weeks of follow-up. DISCUSSION: COVID-19-associated cytokine surge triggering VT storm and unmasking a clinically silent ARVC has not yet been reported. The case highlights a life-threatening presentation of COVID-19 and indicates a probable link between inflammation and arrhythmogenicity.

Cross-reactive immunogenicity of group A streptococcal vaccines designed using a recurrent neural network to identify conserved M protein linear epitopes.

The M protein of group A streptococci (Strep A) is a major virulence determinant and protective antigen. The N-terminal sequence of the protein defines the more than 200 M types of Strep A and also contains epitopes that elicit opsonic antibodies, some of which cross-react with heterologous M types. Current efforts to develop broadly protective M protein-based vaccines are directed at identifying potential cross-protective epitopes located in the N-terminal regions of cluster-related M proteins for use as vaccine antigens. In this study, we have used a comprehensive approach using the recurrent neural network ABCpred and IEDB epitope conservancy analysis tools to predict 16 residue linear B-cell epitopes from 117 clinically relevant M types of Strep A (~88% of global Strep A infections). To examine the immunogenicity of these epitope-based vaccines, nine peptides that together shared ≥60% sequence identity with 37 heterologous M proteins were incorporated into two recombinant hybrid protein vaccines, in which the epitopes were repeated 2 or 3 times, respectively. The combined immune responses of immunized rabbits showed that the vaccines elicited significant levels of antibodies against all nine vaccine epitopes present in homologous N-terminal 1-50 amino acid synthetic M peptides, as well as cross-reactive antibodies against 16 of 37 heterologous M peptides predicted to contain similar epitopes. The epitope-specificity of the cross-reactive antibodies was confirmed by ELISA inhibition assays and functional opsonic activity was assayed in HL-60-based bactericidal assays. The results provide important information for the future design of broadly protective M protein-based Strep A vaccines.

Molecular dynamics analysis of the binding of human interleukin-6 with interleukin-6 α-receptor.

Human interleukin-6 (hIL-6) is a multifunctional cytokine that regulates immune and inflammatory responses in addition to metabolic and regenerative processes and cancer. hIL-6 binding to the IL-6 receptor (IL-6Rα) induces homodimerization and recruitment of the glycoprotein (gp130) to form a hexameric signaling complex. Anti-IL-6 and IL-6R antibodies are clinically approved inhibitors of IL-6 signaling pathway for treating rheumatoid arthritis and Castleman's disease, respectively. There is a potential to develop novel small molecule IL-6 antagonists derived from understanding the structural basis for IL-6/IL-6Rα interactions. Here, we combine homology modeling with extensive molecular dynamics (MD) simulations to examine the association of hIL-6 with IL-6Rα. A comparison with MD of apo hIL-6 reveals that the binding of hIL-6 to IL-6Rα induces structural and dynamic rearrangements in the AB loop region of hIL-6, disrupting intraprotein contacts and increasing the flexibility of residues 48 to 58 of the AB loop. In contrast, due to the involvement of residues 59 to 78 in forming contacts with the receptor, these residues of the AB loop are observed to rigidify in the presence of the receptor. The binary complex is primarily stabilized by two pairs of salt bridges, Arg181 (hIL-6)- Glu182 (IL-6Rα) and Arg184 (hIL-6)- Glu183 (IL-6Rα) as well as hydrophobic and aromatic stacking interactions mediated essentially by Phe residues in both proteins. An interplay of electrostatic, hydrophobic, hydrogen bonding, and aromatic stacking interactions facilitates the formation of the hIL-6/IL-6Rα complex.

Structure based virtual screening identifies small molecule effectors for the sialoglycan binding protein Hsa.

Infective endocarditis (IE) is a cardiovascular disease often caused by bacteria of the viridans group of streptococci, which includes Streptococcus gordonii and Streptococcus sanguinis. Previous research has found that serine-rich repeat (SRR) proteins on the S. gordonii bacterial surface play a critical role in pathogenesis by facilitating bacterial attachment to sialylated glycans displayed on human platelets. Despite their important role in disease progression, there are currently no anti-adhesive drugs available on the market. Here, we performed structure-based virtual screening using an ensemble docking approach followed by consensus scoring to identify novel small molecule effectors against the sialoglycan binding domain of the SRR adhesin protein Hsa from the S. gordonii strain DL1. The screening successfully predicted nine compounds which were able to displace the native ligand (sialyl-T antigen) in an in vitro assay and bind competitively to Hsa. Furthermore, hierarchical clustering based on the MACCS fingerprints showed that eight of these small molecules do not share a common scaffold with the native ligand. This study indicates that SRR family of adhesin proteins can be inhibited by diverse small molecules and thus prevent the interaction of the protein with the sialoglycans. This opens new avenues for discovering potential drugs against IE.

[Evolving Consensus of International Uveitis Study Group, Intraocular Inflammation Society, and Foster Ocular Inflammation Society with Uveitis in the Time of COVID-19 Infection]. / Konsenserfahrung von International Uveitis Study Group, Intraocular Inflammation Society und Foster Ocular Inflammation Society zur Uveitis in der Zeit der COVID-19-Infektion.

This document summarizes the experience of the International Uveitis Study Group (IUSG), the Intraocular Inflammation Society (IOIS) and the Foster Ocular Inflammation Society (FOIS) and can aid as a guide for the treatment of uveitis patients in the era of COVID-19 pandemic.

GPU-Accelerated Drug Discovery with Docking on the Summit Supercomputer: Porting, Optimization, and Application to COVID-19 Research.

Protein-ligand docking is an in silico tool used to screen potential drug compounds for their ability to bind to a given protein receptor within a drug-discovery campaign. Experimental drug screening is expensive and time consuming, and it is desirable to carry out large scale docking calculations in a high-throughput manner to narrow the experimental search space. Few of the existing computational docking tools were designed with high performance computing in mind. Therefore, optimizations to maximize use of high-performance computational resources available at leadership-class computing facilities enables these facilities to be leveraged for drug discovery. Here we present the porting, optimization, and validation of the AutoDock-GPU program for the Summit supercomputer, and its application to initial compound screening efforts to target proteins of the SARS-CoV-2 virus responsible for the current COVID-19 pandemic.

Mesophilic Pyrophosphatase Function at High Temperature: A Molecular Dynamics Simulation Study.

The mesophilic inorganic pyrophosphatase from Escherichia coli (EcPPase) retains function at 353 K, the physiological temperature of hyperthermophilic Thermococcus thioreducens, whereas the homolog protein (TtPPase) from this hyperthermophilic organism cannot function at room temperature. To explain this asymmetric behavior, we examined structural and dynamical properties of the two proteins using molecular dynamics simulations. The global flexibility of TtPPase is significantly higher than its mesophilic homolog at all tested temperature/pressure conditions. However, at 353 K, EcPPase reduces its solvent-exposed surface area and increases subunit compaction while maintaining flexibility in its catalytic pocket. In contrast, TtPPase lacks this adaptability and has increased rigidity and reduced protein/water interactions in its catalytic pocket at room temperature, providing a plausible explanation for its inactivity near room temperature.

Evolving consensus on managing vitreo-retina and uvea practice in post-COVID-19 pandemic era.

The COVID-19 pandemic has brought new challenges to the health care community. Many of the super-speciality practices are planning to re-open after the lockdown is lifted. However there is lot of apprehension in everyone's mind about conforming practices that would safeguard the patients, ophthalmologists, healthcare workers as well as taking adequate care of the equipment to minimize the damage. The aim of this article is to develop preferred practice patterns, by developing a consensus amongst the lead experts, that would help the institutes as well as individual vitreo-retina and uveitis experts to restart their practices with confidence. As the situation remains volatile, we would like to mention that these suggestions are evolving and likely to change as our understanding and experience gets better. Further, the suggestions are for routine patients as COVID-19 positive patients may be managed in designated hospitals as per local protocols. Also these suggestions have to be implemented keeping in compliance with local rules and regulations.

Capturing Deuteration Effects in a Molecular Mechanics Force Field: Deuterated THF and the THF-Water Miscibility Gap.

Deuteration is a common chemical modification used in conjunction with experiments such as neutron scattering, NMR, and Fourier-transform infrared for the study of molecular systems. Under the Born-Oppenheimer (BO) approximation, while the underlying potential energy surface remains unchanged by isotopic substitutions, isotopic substitution still alters intramolecular vibrations, which in turn may alter intermolecular interactions. Molecular mechanics (MM) force fields used in classical molecular dynamics simulations are assumed to represent local approximations of the BO potential energy surfaces, and hence, MD simulations using simple isotopic mass substitutions should capture BO-compatible isotope effects. However, standard MM force-field parameterizations do not directly fit to the local harmonic quantum mechanical (QM) Hessian that describes the BO surface, but rather to QM normal-modes and/or mass-dependent internal-coordinate derived distortion energies. Here, using tetrahydrofuran (THF)-water mixtures as our model system, we show that not only does a simple mass-substitution approach fail to capture an experimentally characterized deuteration effect (the loss of the closed-loop miscibility gap associated with the complete deuteration of THF) but also it is necessary to generate new MM force-field parameters that correctly describe isotopic dependent vibrations to capture the experimental deuteration effect. We show that the origin of this failure is a result of using mass-dependent features to fit the THF MM force field, which unintentionally biases the bonded terms of the force field to represent only the isotopologue used during the original force-field parameterization. In addition, we make use of our isotopologue-corrected force field for D8THF to examine the molecular origins of the isotope-dependent loss of the THF-water miscibility gap.