Selection Of Lead Compounds Research Articles

Exploring the Impact of Pharmacological Target-Mediated Low Plasma Exposure in Lead Compound Selection in Drug Discovery – A Modeling Approach

Exploring the Impact of Pharmacological Target-Mediated Low Plasma Exposure in Lead Compound Selection in Drug Discovery – A Modeling Approach

Insights into Antibacterial Design: Computational Modeling of Eugenol Derivatives Targeting DNA Gyrase

The rise of antibiotic resistance underscores the urgent need for novel antibacterial agents. DNA gyrase, an essential enzyme involved in bacterial DNA replication, is a promising target for antibacterial therapy. Computational approaches offer a cost-effective means to design and screen potential inhibitors, such as eugenol derivatives. This study aims to computationally design eugenol derivatives as potential antibacterial agents targeting DNA gyrase, assess their binding affinities, evaluate physicochemical properties, and toxicity, and select lead compounds for further investigation. Molecular docking simulations were conducted to investigate the binding affinities of eugenol derivatives and controls to DNA gyrase. Physicochemical properties and toxicity assessments of eugenol were evaluated. Lead compounds were selected based on drug likeness, toxicity, and binding affinity. Molecular docking studies revealed varying binding affinities of eugenol derivatives to DNA gyrase, with lead compounds exhibiting superior affinity compared to eugenol. Physicochemical properties indicated moderate lipophilicity and low aqueous solubility for eugenol. Toxicity assessment revealed mutagenicity and tumorigenicity. De novo compound synthesis generated 244 novel compounds, with 44 selected based on drug-likeness, toxicity, and binding affinity as lead candidates. These findings provide valuable insights for the development of novel antibacterial agents targeting DNA gyrase, with implications for combating antibiotic resistance.

High-Throughput Drug Stability Assessment via Biomimetic Metalloporphyrin-Catalyzed Reactions Using Laser-Assisted Rapid Evaporative Ionization Mass Spectrometry (LA-REIMS)

Background: Building extensive drug candidate libraries as early in the development pipeline as possible, with high-throughput in vitro absorption, distribution, metabolism, and excretion (ADME) profiling, is crucial for the selection of lead compounds to guide subsequent research and production phases. Traditionally, the analysis of metabolic stability assays heavily relies on high-throughput LC-MS/MS (liquid chromatography tandem mass spectrometry) techniques to meet with the lead profiling demands. Laser-assisted rapid evaporative ionization mass spectrometry (LA-REIMS) is a quick and efficient technique for characterizing complex biological samples without laborious sample preparation. Objective: In this study, using an automated LA-REIMS well plate reader, achieving an 8 s per sample measurement time, the oxidative metabolic stability of active drug agents was assessed using biomimetic metalloporphyrin-based oxidative model reactions. Results: The results obtained using the novel LA-REIMS-based protocol were compared to and corroborated by those obtained using conventional HPLC-UV-MS (high performance liquid chromatography with ultra-violet detection coupled with mass spectrometry) measurements. Conclusions: LA-REIMS emerges as a promising technique, demonstrating potential suitability for semi-quantitative high-throughput metabolic stability in an optimized solvent environment.

Advances and Insights in Positron Emission Tomography Tracers for Metabotropic Glutamate Receptor 4 Imaging.

Positron emission tomography (PET) imaging employs positron-emitting radioisotopes to visualize biological processes in living subjects with high sensitivity and quantitative accuracy. As the most translational molecular imaging modality, PET can detect and image a wide range of radiotracers with minimal or no modification to parent drugs or targeting molecules. This Perspective provides a comprehensive analysis of developing PET radioligands using allosteric modulators for the metabotropic glutamate receptor subtype 4 (mGluR4) as a therapeutic target for neurological disorders. We focus on the selection of lead compounds from various chemotypes of mGluR4 positive allosteric modulators (PAMs) and discuss the challenges and systematic characterization required in developing brain-penetrant PET tracers specific for mGluR4. Through this analysis, we offer insights into the development and evaluation of PET ligands. Our review concludes that further research and development in this field hold great promise for discovering effective treatments for neurological disorders.

Generation and Characterization of Novel Pan-Cancer Anti-uPAR Fluorescent Nanobodies as Tools for Image-Guided Surgery.

Fluorescence molecular imaging plays a vital role in image-guided surgery. In this context, the urokinase plasminogen activator receptor (uPAR) is an interesting biomarker enabling the detection and delineation of various tumor types due to its elevated expression on both tumor cells and the tumor microenvironment. In this study, anti-uPAR Nanobodies (Nbs) are generated through llama immunization with human and murine uPAR protein. Extensive in vitro characterization and in vivo testing with radiolabeled variants are conducted to assess their pharmacokinetics and select lead compounds. Subsequently, the selected Nbs are converted into fluorescent agents, and their application for fluorescence-guided surgery is evaluated in various subcutaneous and orthotopic tumor models. The study yields a panel of high-affinity anti-uPAR Nbs, showing specific binding across multiple types of cancer cells in vitro and in vivo. Lead fluorescently-labeled compounds exhibit high tumor uptake with high contrast at 1h after intravenous injection across all assessed uPAR-expressing tumor models, outperforming a non-targeting control Nb. Additionally, rapid and accurate tumor localization and demarcation are demonstrated in an orthotopic human glioma model. Utilizing these Nbs can potentially enhance the precision of surgical tumor resection and, consequently, improve survival rates in the clinic.

Exploration and Validation of Lead Molecules against Yellow Fever through High Throughput Virtual Screening and Molecular Dynamics Simulation

Background: Yellow fever (YF) is a mosquito-borne flaviviral hemorrhagic fever (VHF) that causes severe hepatitis, renal failure, bleeding, and quick terminal events such as shock and multi-organ failure. There are currently no particular anti-viral medications for the management of the YF virus (YFV). Despite the availability of a commercial YFV vaccination, there are roughly 30,000 fatalities globally each year, with instances rising over the previous 20 years. After being translocated into the endoplasmic reticulum lumen, glycosylated NS1 resides as a membrane-associated dimer, where it is required for viral genome replication. The secreted hexamer NS1 has a role in immune evasion and pathogenesis and has been discovered as a possible diagnostic marker for the early identification of viral infections. Objective: The main aim of this study is to analyze the small molecule as a potent drug candidate against the target NS1 protein. Methods: In this study, Computational approaches, including high throughput virtual screening, molecular docking, and dynamics simulation, were carried out against the target NS1 protein using three different chemical libraries Enamine, Asinex, and NCI. The selected lead compounds were validated through HOMO-LUMO analysis, ADME prediction, and Toxicity parameters to analyze the biological and pharmacological properties of the lead small molecules. Results: From the result, it was concluded that the leads possessed the highest docking scores, interacting with the binding residues, and were stable in the simulation period. Conclusion: Overall findings revealed that the lead three small molecules could act as the potential drug candidate for the target NS1 protein to inhibit the diseasing efficacy of Yellow fever.

Chemoproteomics Identifies State-Dependent and Proteoform-Selective Caspase-2 Inhibitors.

Caspases are a highly conserved family of cysteine-aspartyl proteases known for their essential roles in regulating apoptosis, inflammation, cell differentiation, and proliferation. Complementary to genetic approaches, small-molecule probes have emerged as useful tools for modulating caspase activity. However, due to the high sequence and structure homology of all 12 human caspases, achieving selectivity remains a central challenge for caspase-directed small-molecule inhibitor development efforts. Here, using mass spectrometry-based chemoproteomics, we first identify a highly reactive noncatalytic cysteine that is unique to caspase-2. By combining both gel-based activity-based protein profiling (ABPP) and a tobacco etch virus (TEV) protease activation assay, we then identify covalent lead compounds that react preferentially with this cysteine and afford a complete blockade of caspase-2 activity. Inhibitory activity is restricted to the zymogen or precursor form of monomeric caspase-2. Focused analogue synthesis combined with chemoproteomic target engagement analysis in cellular lysates and in cells yielded both pan-caspase-reactive molecules and caspase-2 selective lead compounds together with a structurally matched inactive control. Application of this focused set of tool compounds to stratify the functions of the zymogen and partially processed (p32) forms of caspase-2 provide evidence to support that caspase-2-mediated response to DNA damage is largely driven by the partially processed p32 form of the enzyme. More broadly, our study highlights future opportunities for the development of proteoform-selective caspase inhibitors that target nonconserved and noncatalytic cysteine residues.

Discovery of novel macrocyclic derivatives as potent and selective cyclin-dependent kinase 2 inhibitors

Cyclin-dependent kinase 2 (CDK2) is a member of CDK family of kinases (CDKs) that regulate the cell cycle. Its inopportune or over-activation leads to uncontrolled cell cycle progression and drives numerous types of cancers, especially ovarian, uterine, gastric cancer, as well as those associated with amplified CCNE1 gene. However, developing selective lead compound as CDK2 inhibitors remains challenging owing to similarities in the ATP pockets among different CDKs. Herein, we described the optimization of compound 1, a novel macrocyclic inhibitor targeting CDK2/5/7/9, aiming to discover more selective and metabolically stable lead compound as CDK2 inhibitor. Molecular dynamic (MD) simulations were performed for compound 1 and 9 to gain insights into the improved selectivity against CDK5. Further optimization efforts led to compound 22, exhibiting excellent CDK2 inhibitory activity, good selectivity over other CDKs and potent cellular effects. Based on these characterizations, we propose that compound 22 holds great promise as a potential lead candidate for drug development.

Discovery of Novel Noncovalent KRAS G12D Inhibitors through Structure-Based Virtual Screening and Molecular Dynamics Simulations.

The development of effective inhibitors targeting the Kirsten rat sarcoma viral proto-oncogene (KRASG12D) mutation, a prevalent oncogenic driver in cancer, represents a significant unmet need in precision medicine. In this study, an integrated computational approach combining structure-based virtual screening and molecular dynamics simulation was employed to identify novel noncovalent inhibitors targeting the KRASG12D variant. Through virtual screening of over 1.7 million diverse compounds, potential lead compounds with high binding affinity and specificity were identified using molecular docking and scoring techniques. Subsequently, 200 ns molecular dynamics simulations provided critical insights into the dynamic behavior, stability, and conformational changes of the inhibitor-KRASG12D complexes, facilitating the selection of lead compounds with robust binding profiles. Additionally, in silico absorption, distribution, metabolism, excretion (ADME) profiling, and toxicity predictions were applied to prioritize the lead compounds for further experimental validation. The discovered noncovalent KRASG12D inhibitors exhibit promises as potential candidates for targeted therapy against KRASG12D-driven cancers. This comprehensive computational framework not only expedites the discovery of novel KRASG12D inhibitors but also provides valuable insights for the development of precision treatments tailored to this oncogenic mutation.

Discovery of Potential Inhibitors for SFRP3: Ligand-Based 3D Pharmacophore, Virtual Screening, Molecular Docking, and Dynamics Studies

Cancer is a complicated and diverse family of diseases characterized by the body’s aberrant cells growing and spreading out of control. It is one of the major causes of mortality in the world and may affect almost every organ or tissue in the body. One of the most prevalent forms of malignant tumors that affect both men and women is bone cancer. The study introduces the soluble frizzled-related protein SFRP3 as a significant participant. It functions as a tumor suppressor and regulator as well as an antagonist of the Wnt signaling pathway. It interacts directly with Wnts, regulating Wnt signaling and directing cell proliferation and differentiation in certain cell types. The study focuses on SFRP3 as a possible target for bone cancer therapy. The purpose is to find prospective medication candidates. Several databases are listed as possible drug compound sources, including NCI_Natural Products, Enamine, and specifications. Potent drugs from the selected databases are scrutinized and identified using ligand-based pharmacophore modeling. The binding affinity and interactions between the selected compounds and the SFRP3-modeled protein are evaluated using virtual screening and molecular docking approaches. The selection of lead compounds is based on their scores, binding affinity, and interactions, which indicate their potential as therapeutic candidates. To ensure that the contacts stay stable throughout time, molecular dynamics modeling is used to analyze the stability of the Protein-Ligand complex. The investigation leads to the identification of the top three compounds from each of the three databases that show potential against the target protein, SFRP3.

Short-course combination treatment for experimental chronic Chagas disease.

Chagas disease, caused by the protozoan parasite Trypanosoma cruzi, affects millions of people in the Americas and across the world, leading to considerable morbidity and mortality. Current treatment options, benznidazole (BNZ) and nifurtimox, offer limited efficacy and often lead to adverse side effects because of long treatment durations. Better treatment options are therefore urgently required. Here, we describe a pyrrolopyrimidine series, identified through phenotypic screening, that offers an opportunity to improve on current treatments. In vitro cell-based washout assays demonstrate that compounds in the series are incapable of killing all parasites; however, combining these pyrrolopyrimidines with a subefficacious dose of BNZ can clear all parasites in vitro after 5 days. These findings were replicated in a clinically predictive in vivo model of chronic Chagas disease, where 5 days of treatment with the combination was sufficient to prevent parasite relapse. Comprehensive mechanism of action studies, supported by ligand-structure modeling, show that compounds from this pyrrolopyrimidine series inhibit the Qi active site of T. cruzi cytochrome b, part of the cytochrome bc1 complex of the electron transport chain. Knowledge of the molecular target enabled a cascade of assays to be assembled to evaluate selectivity over the human cytochrome b homolog. As a result, a highly selective and efficacious lead compound was identified. The combination of our lead compound with BNZ rapidly clears T. cruzi parasites, both in vitro and in vivo, and shows great potential to overcome key issues associated with currently available treatments.

Schistosomiasis Drug Development: A Computational Approach

Schistosomiasis continues to be a significant global health concern, affecting millions of individuals worldwide. The limitations associated with the existing treatment, Praziquantel, highlight the urgent need for novel schistosomicides. The development of a structure-based drug with high efficacy offers a potential solution to the challenges posed by current treatments. Given the capital and time-intensive nature of traditional inhibitor identification methods, computational techniques have gained prominence as valuable tools in drug discovery. This study employed a comprehensive computational approach to identify potential drug candidates, laying the groundwork for future wet-lab experimentation. In this research, in silico molecular docking analysis assessed the binding affinity of various compounds to the Schistosoma japonicum tegument protein 4 (SGTP4). To facilitate this analysis, homology modeling generated a reliable 3D structure of SGTP4. This rigorous approach, encompassing homology modeling and subsequent validation, ensured the reliability and high quality of the SGTP4 protein model, providing a solid foundation for subsequent molecular docking and drug discovery investigations. The ligands examined included Praziquantel , Licochalcone, P96, Licarin, and Harmonine. Ligand preparations were conducted using LigPrep within the Schrodinger Maestro suite, and pharmacokinetic parameters were evaluated using the QikProp tool within the Schrodinger-2019-4 software suite. Subsequently, AutoDockTools version 4 facilitated the docking analysis of the prepared ligands. The docking results furnished valuable insights into the binding affinities and potential inhibitory activities of the assessed compounds against SGTP4. PZQ, Licochalcone, and P96 exhibited robust binding affinities and inhibitory potentials, characterized by their lower binding energies and Ki values. Licarin demonstrated moderate activity, whereas Harmonine exhibited comparatively weaker binding and inhibition. The amalgamated results of docking analysis and ADMET simulations establish a foundation for the selection of lead compounds for further experimental evaluation in the quest for effective anti-schistosomal drugs. Among the evaluated compounds, Licochalcone and Licarin emerge as promising candidates, characterized by favorable molecular properties, drug-like attributes, and bioavailability. While PZQ retains its importance as a reference, its limitations underscore the necessity of exploring alternative compounds. Furthermore, P96 exhibits potential, particularly with structural modifications, warranting further investigation. This study underscores the significance of computational methodologies in the initial stages of drug discovery. Nonetheless, it is essential to stress that wet-lab experimentation remains an indispensable step in drug development. The computational insights presented herein offer a compelling rationale for the wet-lab validation of the identified candidates. Such experiments can elucidate the mechanisms of action, evaluate safety profiles, and confirm efficacy against schistosomes. Therefore, we advocate for the integration of wet-lab experiments to complement computational approaches, presenting a synergistic strategy poised to address the deficiencies of PZQ and effectively combat schistosomiasis.

Exploring the Binding Pathway of Novel Nonpeptidomimetic Plasmepsin V Inhibitors.

Predicting the interaction modes and binding affinities of virtual compound libraries is of great interest in drug development. It reduces the cost and time of lead compound identification and selection. Here we apply path-based metadynamics simulations to characterize the binding of potential inhibitors to the Plasmodium falciparum aspartic protease plasmepsin V (plm V), a validated antimalarial drug target that has a highly mobile binding site. The potential plm V binders were identified in a high-throughput virtual screening (HTVS) campaign and were experimentally verified in a fluorescence resonance energy transfer (FRET) assay. Our simulations allowed us to estimate compound binding energies and revealed relevant states along binding/unbinding pathways in atomistic resolution. We believe that the method described allows the prioritization of compounds for synthesis and enables rational structure-based drug design for targets that undergo considerable conformational changes upon inhibitor binding.

Identifying natural products for gastric cancer treatment through pharmacophore creation, 3D QSAR, virtual screening, and molecular dynamics studies.

Gastric cancer (GC) is known as the fourth leading cause of cancer-related death and the fifth major cancer in the world, and this is a serious threat to general health all over the world. The lack of early detection markers results in a belated diagnosis, i.e. the final stages, which could be associated with the ineffectiveness of the treatment strategies, and naturally, it leads to poor prognosis. Even though a variety of treatments have been developed, there is a trend of studying traditional medicinal plants, due to the worrying side effect of drugs available in the market. In this study, pharmacophore generation and 3D-QSAR model were created using 50 compounds with anti-gastric cancer activity (with IC50 had been reported in the previous studies). Based on three of the best pharmacophoric hypotheses, virtual screening was performed to discover the top anti-gastric cancer compounds from a database of 183,885 compounds. The selected compounds were used for molecular docking with three protein receptors 7BKG, 4F5B, and 4ZT1 to investigate the intermolecular interactions between these ligands and receptors. Finally, 21 lead compounds with the highest amount of docking score ranging from - 13.366 to -6.404kcal/mol were selected, and then the ADME/Tox properties of these compounds were calculated. All these compounds have a fitness score above 1.8, a molecular weight of less than 500g/mol, hydrogen bond donors up to 3, hydrogen bond acceptors up to 8.50, and logP of 1.013 to 4.174. Finally, molecular dynamic simulations for top-scoring ligand-receptor complexes were investigated. These selected lead compounds have the most anti-gastric cancer effects among the 183,885 compounds in the database. Therefore, lead compounds might be considered for gastric cancer therapy in future studies.

Discovery of potent DNMT1 inhibitors against sickle cell disease using structural-based virtual screening, MM-GBSA and molecular dynamics simulation-based approaches

Sickle cell disease (SCD) is an autosomal recessive genetic disorder affecting millions of people worldwide. A reversible and selective DNMT1 inhibitor, GSK3482364, has been known to decrease the overall methylation activity of DNMT1, resulting in the increase of HbF levels and percentage of HbF-expressing erythrocytes in an in vitro and in vivo model. In this study, a structure-based virtual screening was done with GSK3685032, a co-crystalized ligand of DNMT1 (PDB ID: 6X9K) with an IC50 value of 0.036 μM and identified 3988 compounds from three databases (ChEMBL, PubChem and Drug Bank). Using this screening method, we identified around 15 compounds with XP docking scores greater than −8 kcal/mol. Further, prime MM-GBSA calculations have been performed and found compound SCHEMBL19716714 with the highest binding free energy of −83.31 kcal/mol. Finally, four compounds were identified based on glide energy and ΔG bind scores that have the most binding with DG7, DG19, DG20 bases and Lys1535, His1507, Trp1510, Ser1230, which were required for the target enzyme inhibition. Furthermore, molecular dynamics simulation studies of top ligands validate the stability of the docked complexes by examining root mean square deviations, root mean square fluctuations, solvent accessible surface area, and radius of gyration graphs from simulation trajectories. These findings suggest that the top four hit compounds may be capable of inhibiting DNMT1 and that additional in vitro and in vivo studies will be essential to prove the clinical effectiveness of the selected lead compounds. Communicated by Ramaswamy H. Sarma

In silico discovery of potent inhibitors against monkeypox’s major structural proteins

Monkeypox virus (MPXV) outbreak in non-endemic countries is a worldwide public health emergency. An enveloped double-stranded DNA virus belongs to the genus Orth poxvirus. A viral zoonotic infection known as monkeypox has been a serious risk to public health, especially in Africa. However, it has recently spread to other continents, so it might soon become a worldwide problem. There is an increased risk of transmission of the virus because there is a lack of effective treatment that cures the disease. To stop the multi-country outbreak from spreading, it is important to discover effective medications urgently. The objective of the current study is to swiftly find new treatments for the monkeypox virus using advanced computational approaches. By investigating five potential MPXV targets (DNA ligase, Palmytilated Extracellular Enveloped Virus (EEV) membrane protein, Scaffold protein D13, Thymidylate Kinase, and Viral core cysteine proteinase), this research was carried out using cutting-edge computational techniques against human monkeypox virus infection. Here we present the accurate 3D structures and their binding cavities of the selected targets with higher confidence using AlphaFold 2 and SiteMap analysis. Molecular docking and MD simulation analysis revealed the top five potential lead compounds with higher binding affinity and stability toward selected targets. Binding free energy calculations and other essential dynamics analysis supports the finding. The selected lead compounds utilizing virtual screening and drug repurposing approach reported in this study are beneficial for medical scientists and experimental biologists in drug development for the treatment of human MPXV.Communicated by Ramaswamy H. Sarma

Tupichinol-E Reverse Epithelial to Mesenchymal Transition against ER Positive and Triple Negative Breast Cancer

Aim: To investigate the effects of Tupichinol E, an alkaloid present in Tupistra chinensis BAKER (Liliaceae) on the metastasis of Triple negative mammary carcinoma in-vitro, and elucidate the underlying mechanisms and Tupichinol E binding to EGFR stabilises the protein structure and is a pharmacologically active substance that can be used against cancer due to its potent activity. Methods: Growth of MCF-7 and MDA-MB-231 cells was assessed using MTT assay. Apoptosis and cell cycle of MCF-7 cells were evaluated with flow cytometry, and the related proteins were examined using Western blotting. Structurally similar EGFR inhibitors, their modes of binding and mechanism of actions are a new way to select lead compounds for better alternatives. Therefore molecular docking is done to find a potential anti-EGFR flavonoid. Results: Tupichinol E (35–280 μmol/L) inhibited the growth of MCF-7 cells in time- and dose-dependent manners (the IC50 values were 105±1.08 and 78.52±1.06 μmol/L, respectively, at 48 and 72 h). Treatment of MCF-7 cells with Tupichinol E (70–280 μmol/L) dose-dependently induced apoptosis of MCF-7 cells, accompanying activation of caspase 3. The cells treated with Tupichinol E (140 and 280 μmol/L) significantly increased the percentage of cells in G2/M phase with a reduction in the expression of cyclin B1. Osmertinib shows binding energy -107.23 kcal/mol with EGFR, while Tupichinol E shows binding energy -98.89 kcal/mol. Tupichinol E shows 1.5 times more binding affinity than Osmertinib. Conclusion: These results demonstrated that Tupichinol E is an effective antitumor compound in vitro and in-silico, and has the potential to be developed as a new anticancer drug.

Obstructing Salmonella typhi's virulence in eukaryotic cells through design of its SipB protein antagonists

ObjectiveTyphoid fever, a disease caused by Salmonella typhi, is a leading cause of morbidity and mortality, particularly in developing nations. The evolution of resistance mechanisms to existing antibiotics has necessitated a search for newer drug candidates. This study used computer aided drug design techniques to design novel antibiotics that function by antagonizing SipB, an effector protein of the bacterium that is responsible for its pathogenicity and virulence in eukaryotic host cells. MethodsA data set of 32 bioactive molecules with established antibacterial activity against S. typhi was retrieved from the PubChem data base; optimized through a DFT approach in Spartan 14 software; and further subjected to QSAR modeling in BIOVIA-Accelrys Material Studio. The validated model (R2 = 0.80, R2Adj = 0.78, Q2LOO = 0.74, R2pred = 0.54, lack of fit = 0.07) revealed the dominant influence of MATS6c and E3p descriptors on the observed antibacterial activity of the compounds. Information from the model was used to optimize the structures of selected lead compounds in the data set, thus leading to the design of a highly potent set of novel analogues denoted D-1, D-2 and D-3. ResultsThe predicted MIC values of D-1, D-2 and D-3 were 1.03, 0.73 and 0.30 μg/mL, respectively. Furthermore, molecular docking studies on these novel ligands against the active sites of SipB revealed binding energy values of −8.0, −7.7 and −7.7 kcal/mol for D-1, D-2 and D-3, respectively. These values were better than the −7.0 kcal/mol recorded for ciprofloxacin, the reference antibiotic used herein for quality assurance. In addition, drug-likeness and ADMET evaluation of the designed compounds revealed that they are orally bioavailable and exhibit excellent pharmacokinetic and toxicological profiles. ConclusionThe current findings may provide a roadmap for the discovery of more potent antibiotics against S. typhi.

Inhibition of glycogen synthase kinase-3-beta (GSK3β) blocks nucleocapsid phosphorylation and SARS-CoV-2 replication

GSK3β has been proposed to have an essential role in Coronaviridae infections. Screening of a targeted library of GSK3β inhibitors against both SARS-CoV-2 and HCoV-229E to identify broad-spectrum anti-Coronaviridae inhibitors resulted in the identification of a high proportion of active compounds with low toxicity to host cells. A selected lead compound, T-1686568, showed low micromolar, dose-dependent activity against SARS-CoV-2 and HCoV-229E. T-1686568 showed efficacy in viral-infected cultured cells and primary 2D organoids. T-1686568 also inhibited SARS-CoV-2 variants of concern Delta and Omicron. Importantly, while inhibition by T-1686568 resulted in the overall reduction of viral load and protein translation, GSK3β inhibition resulted in cellular accumulation of the nucleocapsid protein relative to the spike protein. Following identification of potential phosphorylation sites of Coronaviridae nucleocapsid, protein kinase substrate profiling assays combined with Western blotting analysis of nine host kinases showed that the SARS-CoV-2 nucleocapsid could be phosphorylated by GSK3β and PKCa. GSK3β phosphorylated SARS-CoV-2 nucleocapsid on the S180/S184, S190/S194 and T198 phospho-sites, following previous priming in the adjacent S188, T198 and S206, respectively. Such inhibition presents a compelling target for broad-spectrum anti-Coronaviridae compound development, and underlies the mechanism of action of GSK3β host-directed therapy against this class of obligate intracellular pathogens.

A Large-Scale High-Throughput Screen for Modulators of SERCA Activity

The sarco/endoplasmic reticulum Ca-ATPase (SERCA) is a P-type ion pump that transports Ca2+ from the cytosol into the endoplasmic/sarcoplasmic reticulum (ER/SR) in most mammalian cells. It is critically important in muscle, facilitating relaxation and enabling subsequent contraction. Increasing SERCA expression or specific activity can alleviate muscle dysfunction, most notably in the heart, and we seek to develop small-molecule drug candidates that activate SERCA. Therefore, we adapted an NADH-coupled assay, measuring Ca-dependent ATPase activity of SERCA, to high-throughput screening (HTS) format, and screened a 46,000-compound library of diverse chemical scaffolds. This HTS platform yielded numerous hits that reproducibly alter SERCA Ca-ATPase activity, with few false positives. The top 19 activating hits were further tested for effects on both Ca-ATPase and Ca2+ transport, in both cardiac and skeletal SR. Nearly all hits increased Ca2+ uptake in both cardiac and skeletal SR, with some showing isoform specificity. Furthermore, dual analysis of both activities identified compounds with a range of effects on Ca2+-uptake and ATPase, which fit into distinct classifications. Further study will be needed to identify which classifications are best suited for therapeutic use. These results reinforce the need for robust secondary assays and criteria for selection of lead compounds, before undergoing HTS on a larger scale.