Candidate Inhibitors Research Articles

Identification and prioritization of novel therapeutic candidates against glutamate racemase from Klebsiella pneumoniae

Background Klebsiella pneumoniae, a gram-negative bacterium in the Enterobacteriaceae family, is non-motile, encapsulated, and a major cause of nosocomial infections, particularly in intensive care units. The bacterium possesses a thick polysaccharide capsule and fimbriae, which contribute to its virulence, resistance to phagocytosis, and attachment to host cells. The bacterium has developed serious resistance to most antibiotics currently in use. Objective This study aims to investigate the structural properties of MurI (glutamate racemase) from Klebsiella pneumoniae and to identify potential candidate inhibitors against the protein, which will help in the development of new strategies to combat the infections related to MDR strains of Klebsiella pneumoniae. Methods The 3D structure of the protein was modelled using SWISS-MODEL, which utilizes the homology modelling technique. After refinement, the structure was subjected to virtual high throughput screening on the TACC server using Enamine AC collection. The obtained molecules were then put through various screening parameters to obtain promising lead candidates, and the selected molecules were then subjected to MD simulations. The data obtained from MD simulations was then assessed with the help of different global dynamics analyses. The protein-ligand complexes were also subjected to MM/PBSA-based binding free energy calculation using the g_mmpbsa program. Results The screening parameters employed on the molecules obtained via virtual screening from the TACC server revealed that Z1542321346 and Z2356864560 out of four molecules have better potential to act as potential inhibitors for MurI protein. The binding free energy values, which came out to be -27.26±3.06 kcal/mol and -29.53±4.29 kcal/mol for Z1542321346 and Z2356864560 molecules, respectively, favoured these molecules in terms of inhibition potential towards targeted protein. Conclusion The investigation of MurI via computational approach and the subsequent analysis of potential inhibitors can pave the way for developing new therapeutic strategies to combat the infections and antibiotic resistance of Klebsiella pneumoniae. This study could significantly help the medical fraternity in the treatment of infections caused by this multidrug-resistant pathogen.

Virtual Screening, Toxicity Evaluation and Pharmacokinetics of Erythrina Alkaloids as Acetylcholinesterase Inhibitor Candidates from Natural Products

Virtual Screening, Toxicity Evaluation and Pharmacokinetics of Erythrina Alkaloids as Acetylcholinesterase Inhibitor Candidates from Natural Products

Kinomic profiling to predict sunitinib response of patients with metastasized clear cell Renal Cell Carcinoma.

Treatment with Sunitinib, a potent multitargeted receptor tyrosine kinase inhibitor (TKI) has increased the progression-free survival (PFS) and overall-survival (OS) of patients with metastasized renal cell carcinoma (mRCC). With modest OS improvement and variable response and toxicity predictive and/or prognostic biomarkers are needed to personalize patient management: Prediction of individual TKI therapy response and resistance will increase successful treatment outcome while reducing unnecessary drug use and expense. The aim of this study was to investigate whether kinase activity analysis can predict sunitinib response and/or toxicity using tissue samples obtained from primary clear cell RCC (ccRCC) from a cohort of clinically annotated patients with mRCC receiving sunitinib as first-line treatment. EuroTARGET partners collected ccRCC and matched normal kidney tissue samples immediately after surgery, snap-frozen and stored at -80°C until use. Phosphotyrosine-activity profiling was performed using PamChip® peptide microarrays (144 peptides derived from known phosphorylation sites in Protein Tyrosine Kinase substrates) of lysed tissue samples (5 µg protein input) of 163 mRCC patients. Evolve software Was used to analyze kinome profiles and Bionavigator was used for unsupervised and supervised clustering. The kinexus kinase predictor (www.phosphonet.ca) was used to analyze the peptide lists within the clusters. Kinome data was available from 94 patients who received sunitinib as 1st-line treatment and had complete follow-up of their clinical data (PFS, OS and toxicity) for at least 6 months. Matched normal tissue was available from 14 mRCC patients. Supervised clustering of basal kinome activity could correctly classify mRCC patients with PFS >9 months versus PFS<9 months with an accuracy of 61 %. Unsupervised hierarchical clustering revealed 3 major clusters related to immune signaling, VEGF pathway, and immune signaling/cell adhesion. Basal kinase activity levels of patients with short PFS were substantially higher compared to patients who experienced extended PFS. Based on kinase levels ccRCC tumors can be subdivided into 3 clusters which may reflect the aggressiveness of these tumors. The accuracy of response prediction of 61 % based on basal kinase levels is too low to justify implementation. STK assays may help to predict sunitinib toxicity and guide clinical management. Additionally, it is possible that mRCC patients with an immune kinase signature are better checkpoint inhibitor candidates, but this needs to be studied.

P-26 DIABETIC KETOACIDOSIS: A POTENTIAL RISK OF SGLT2 INHIBITOR USE

Abstract Introduction Sodium-Glucose Cotransporter 2 (SGLT2) inhibitors have been increasingly linked to the development of ketoacidosis in individuals with presumed Type 2 Diabetes, despite the positive cardiorenal effects that have made SGLT2 inhibitors popular in managing Type 2 Diabetes. The clinical presentation of SGLT2 inhibitor-induced diabetic ketoacidosis (DKA) can be subtle, and patients may not necessarily exhibit hyperglycemia. Diagnosis can be complicated by other comorbidities, precipitating factors, and concurrent medications. Additionally, primary care clinicians may lack the means for early detection of rising blood ketone levels, and patients might inadvertently neglect the "sick day" rule. Moreover, a study in Australia found that 21% of Type 2 Diabetes patients on SGLT2 inhibitors who developed DKA were later diagnosed with Type 1 Diabetes or LADA. This highlights the need for clinicians to maintain a high index of suspicion for SGLT2 inhibitor-related DKA, ensuring prompt referral for evaluation and careful consideration of discontinuing the medication based on clinical outcomes. Clinical Case We reported a case of a 72-year-old woman with a 13-year history of Type 2 Diabetes Mellitus (DM) presented to the Emergency Department with reduced oral intake, generalized weakness, shortness of breath, and worsening pedal swelling. Her medical history included diabetic neuropathy, hypertension, a prior transient ischemic attack, and osteoarthrosis. She was on multiple medications, including empagliflozin, valsartan, and metformin. On examination, the patient was tachypneic with oral thrush, sacral edema, and dry mucosa. Initial investigations showed hyperglycemia (20.4 mmol/L), acidosis (pH 7.25), high blood ketones (7.2 mmol/L), and severe hypokalemia (2.2 mmol/L), leading to a diagnosis of diabetic ketoacidosis. She was transferred to the ICU, and an elevated D-dimer (1.4 µg/mL) prompted investigation for a possible pulmonary embolism. Further tests revealed an HbA1c of 91 mmol/mol, negative results for islet cell antibodies, GAD 65 antibodies, and C-peptide. The anti-factor Xa level was 1.19 IU/mL and antinuclear antibody specificity was normal. CT pulmonary angiography confirmed a small subsegmental pulmonary embolism. Empagliflozin was discontinued and the patient was started on Metformin, Gliclazide and Tresiba. Edoxaban was prescribed for pulmonary embolism. Upon discharge, her general practitioner was informed that she was no longer a candidate for SGLT2 inhibitors. Conclusion The report advises clinicians to remain alert for ketoacidosis associated with SGLT2 inhibitors in Type 2 DM patients, even when euglycemic. Emphasizing adherence to the "sick day rule" and discontinuing the medication at least four days prior to any surgery is essential. Patients who experience DKA related to SGLT2 inhibitors should be considered as inappropriate candidates for continued use of these agents. Funding: none No conflicts of interestFigure 1:Mechanism of action of SGLT2 inhibitorsSGLT2 inhibitors, like canagliflozin and empagliflozin, work by blocking the SGLT2 protein in the kidneys, leading to increased glucose excretion in the urine and lower blood glucose levels. They help preserve pancreatic beta-cell function, reduce stress on these cells, and slow beta-cell dysfunction. Additionally, they protect the kidneys by lowering intraglomerular pressure and albuminuria, slowing diabetic nephropathy. These inhibitors also offer cardiovascular benefits, including reduced risk of heart failure, likely due to effects on blood pressure, fluid volume, and glucose control. Furthermore, they aid in weight loss by increasing glucose excretion, which reduces body fat mass and improves metabolic health. Taken from reference {3} Table 1:FDA approved SGLT2 inhibitors and their outcomes Abbreviations: FDA, Food and Drug Administration: SGLT2, Sodium-Glucose Cotransporter-2; HbAlc, Hemoglobin Alc; BP, blood pressure; MI, myocardial infarction, LDL-C, low density lipoprotein cholesterol; HDL-C, high density lipoprotein cholesterol. Taken from reference [2}

Improved Inhibitors Targeting the Thymidylate Kinase of Multidrug-Resistant Mycobacterium tuberculosis with Favorable Pharmacokinetics

This study aims to design improved inhibitors targeting the thymidylate kinase (TMK) of Mycobacterium tuberculosis (Mtb), the causative agent of infectious disease tuberculosis that is associated with high morbidity and mortality in developing countries. TMK is an essential enzyme for the synthesis of bacterial DNA. We have performed computer-aided molecular design of MtbTMK inhibitors by modification of the reference crystal structures of the lead micromolar inhibitor TKI1 1-(1-((4-(3-Chlorophenoxy)quinolin-2-yl)methyl)piperidin-4-yl)-5-methylpyrimidine-2,4(1H,3H)-dione bound to TMK of Mtb strain H37Rv (PDB entries: 5NRN and 5NR7) using the computational approach MM-PBSA. A QSAR model was prepared for a training set of 31 MtbTMK inhibitors with published inhibitory potencies () and showed a significant correlation between the calculated relative Gibbs free energies of the MtbTMK–TKIx complex formation and the observed potencies. This model was able to explain approximately 95% of the variation in the in vitro inhibition data and validated our molecular model of MtbTMK inhibition for the subsequent design of new TKI analogs. Furthermore, we have confirmed the predictive capacity of this complexation QSAR model by generating a 3D QSAR PH4 pharmacophore-based model. A satisfactory correlation was also obtained for the validation PH4 model of MtbTMK inhibition (R2 = 0.84). We have extended the hydrophobic m-chloro-phenoxyquinolin-2-yl group of TKI1 that can occupy the entry into the thymidine binding cleft of MtbTMK by alternative larger hydrophobic groups. Analysis of residue interactions at the enzyme binding site made it possible to select suitable building blocks to be used in the preparation of a virtual combinatorial library of 28,900 analogs of TKI1. Structural information derived from the complexation model and the PH4 pharmacophore guided the in silico screening of the library of analogs and led to the identification of new potential MtbTMK inhibitors that were predicted to be effective in the low nanomolar concentration range. The QSAR complexation model predicted an inhibitory concentration of 9.5 nM for the best new virtual inhibitor candidate TKI 13_1, which represents a significant improvement in estimated inhibitory potency compared to TKI1. Finally, the stability of the MtbTMK–inhibitor complexes and the flexibility of the active conformation of the inhibitors were assessed by molecular dynamics for five top-ranking analogs. This computational study resulted in the discovery of new MtbTMK inhibitors with predicted enhanced inhibitory potencies, which also showed favorable predicted pharmacokinetic profiles.

Discovery of sugar-based natural framework as phytopathogenic virus capsid protein inhibitors using a state-of-the-art multiple screening strategy.

The prompt and efficient identification of targeted inhibitors against unscrupulous pathogenic viruses holds promise for preventing epidemic disease outbreaks. Herein, a comprehensive multichannel screening method (multiple docking cross-validation, molecular dynamics simulation, and density functional theory calculation) integrated with bioactivity identification is rationally established using sugar-based natural ligand libraries to target tobacco mosaic virus (TMV) capsid proteins. Encouragingly, compounds A0 (Kd=0.14μM) and A4 (Kd=1.43μM) were evaluated to have excellent binding capacities to TMV capsid protein, evidently exceeding that of viricide Ningnanmycin (Kd=3.47μM) by 24.8 and 2.4-folds. Moreover, A0 and A4 significantly down-regulated the expression of capsid proteins at the transcriptional level, effectively blocking the biosynthesis and assembly of TMV in tobacco. Additionally, bioactivity evaluation illustrated that the anti-TMV curative effects of A0 (EC50=310.9μg/mL) and A4 (EC50=371.2μg/mL) were comparable to Ningnanmycin (EC50=343.8μg/mL). Considering the availability, cost and synthesis difficulty of precursors, the more affordable A4 is reckoned to be a promising candidate for capsid protein inhibitors and warrants further exploration in follow-up studies. Current findings highlight that this state-of-the-art virtual strategy, integrated with bioactivity validation, facilitates the discovery of targeted candidates to combat pathogenic viruses.

Resveratrol-Based Carbamates as Selective Butyrylcholinesterase Inhibitors: Design, Synthesis, Computational Study and Biometal Complexation Capability.

Considering our previous experience in the design of new cholinesterase inhibitors, especially resveratrol analogs, in this research, the basic stilbene skeleton was used as a structural unit for new carbamates designed as potentially highly selective butyrylcholinesterase (BChE) inhibitors with excellent absorption, distribution, metabolism, excretion and toxicity ADMET properties. The inhibitory activity of newly prepared carbamates 1-13 was tested toward the enzymes acetylcholinesterase (AChE) and BChE. In the tested group of compounds, the leading inhibitors were 1 and 7, which achieved excellent selective inhibitory activity for BChE with IC50 values of 0.12 ± 0.09 μM and 0.38 ± 0.01 μM, respectively. Both were much more active than the standard inhibitor galantamine against BChE. Molecular docking of the most promising inhibitor candidates, compounds 1 and 7, revealed that stabilizing interactions between the active site residues of BChE and the ligands involve π-stacking, alkyl-π interactions, and, when the carbamate orientation allows, H-bond formation. MD analysis confirmed the stability of the obtained complexes. Some bioactive resveratrol-based carbamates displayed complex-forming capabilities with Fe3+ ions as metal centers. Spectrophotometric investigation indicated that they coordinate one or two metal ions, which is in accordance with their chemical structure, offering two binding sites: an amine and a carboxylic group in the carbamate moiety. Based on the obtained in silico, experimental and computational results on biological activity in the present work, new carbamates 1 and 7 represent potential selective BChE inhibitors as new therapeutics for neurological disorders.

Exploring novel inhibitors for Babesia bigemina lactate dehydrogenase: a computational structural biology perspective.

Babesia bigemina is an apicomplexan parasite responsible for causing "Texas fever" in bovines. Current treatments for bovine babesiosis are hindered by several limitations, including toxicity, insufficient efficacy in eliminating the parasite, and the potential for resistance development. A promising approach to overcome these challenges is the identification of compounds that specifically target essential metabolic pathways unique to the parasite. One such target is lactate dehydrogenase (LDH), a critical enzyme involved in the regulation of anaerobic glycolysis. Notably, Babesia bigemina LDH (BbigLDH) exhibits a five-amino acid insertion in the active site, a feature that differentiates it from the host's LDH. This structural divergence makes apicomplexan LDH an attractive and potentially selective drug target for therapeutic intervention. In this study, a structure-based drug discovery approach was implemented to find novel inhibitor candidates. Potential candidates were identified using a virtual screening workflow. The compounds with favorable docking scores were filtered using the QM-polarized ligand docking and induced fit docking methods. As a result, 20 novel compounds were identified that bind to the active site of BbigLDH but show low affinity to the host LDHs. Molecular dynamics simulations of the complexes (8.8µs in total) were performed, and binding free energies were calculated. As a result, protein structures containing compounds C9, C16 and C18 maintained their stability throughout 1µs simulations with low binding free energies and conserved interactions with known catalytic residues. Therefore, these three compounds deserve further investigation to better understand their mode of action and therapeutic potential for babesiosis. The results of this study elucidate the structural features of the BbigLDH enzyme and provide novel LDH binders that may pave the way for further research into the development of parasite-specific LDH inhibitors.

Molecular docking and molecular dynamics simulation studies of inhibitor candidates against Anopheles gambiae 3-hydroxykynurenine transaminase and implications on vector control.

Isoxazole and oxadiazole derivatives inhibiting 3-hydroxykynurenine transaminase (3HKT) are potential larvicidal candidates. This study aims to identify more suited potential inhibitors of Anopheles gambiae 3HKT (Ag3HKT) through molecular docking and molecular dynamics simulation. A total of 958 compounds were docked against Anopheles gambiae 3HKT (PDB ID: 2CH2) using Autodock vina and Autodock4. The top three identified hits were subjected to 300 ns molecular dynamics simulation using AMBER 18 and ADMET analysis using SWISSADME predictor and ADMETSAR. Replacement of alkyl attachment on C5 of isoxazole or oxadiazole derivative with a cycloalkyl group yielded compounds with lower binding energy than their straight chain counterparts. The top three compounds were brominated compounds, 2-[3-(4-bromophenyl)-1,2-oxazol-5-yl]cyclopentane-1-carboxylic acid, 2-[3-(4-bromophenyl)-1,2,4-oxadiazol-5-yl]cyclopentane-1-carboxylic acid, 3-[3-(4-bromo-2-methylphenyl)-1,2,4-oxadiazol-5-yl]cyclopentane-1-carboxylic acid, and they had binding energies of -8.58, -8.25, and -8.18kcal/mol in virtual screening against 2CH2 protein target, respectively. These compounds were predicted to be less toxic than temephos, a standard larvicide and more biodegradable than previously reported inhibitors. The three compounds exhibited a greater stabilizing effect on 2CH2 protein target than 4-[3-(4-bromophenyl)-1,2,4-oxadiazol-5-yl]butanoic acid, a previously reported inhibitor candidate with good larvicidal activity on Aedes aegypti. Further thermodynamic calculations revealed that the top three compounds possessed total binding energies (ΔGbind) of -26.64kcal/mol, -24.26kcal/mol and -14.11kcal/mol, respectively, as compared to -12.02kcal/mol for 4-[3-(4-bromophenyl)-1,2,4-oxadiazol-5-yl]butanoic acid. These compounds could be better larvicides than previously reported isoxazole or oxadiazole derivatives and safer than temephos.

Proposing a new anti-Covid-19 agent by using molecular docking and dynamics simulations

Abstract The Covid-19 pandemic, caused by SARS-CoV-2, was responsible for millions of deaths worldwide. The main protease (Mpro) of SARS-CoV-2 is considered one of the important drug targets for the treatment of Covid-19. Recent studies have shown that anisotine should be a potent Mpro inhibitor. In the present work, four oxoquinoline derivatives are proposed as candidates for Mpro inhibitors. The main functional group of these derivatives shows similarity to anisotine, and they are active against the HSV-1, as well as the latter. Molecular docking studies evaluated whether these compounds could be active against Mpro of SARS-CoV-2. Structural modifications were proposed on the oxoquinoline derivative which formed a more stable complex with Mpro and this proposal formed an even more stable complex besides exhibiting improvements in the toxicological profile. Molecular dynamics simulations indicated that derivatives proposed promote greater stabilization by complexing with Mpro than anisotine.

Identification of novel vesicular monoamine transporter 2 (VMAT2) inhibitors: A structure-based approach

The Vesicular Monoamine Transporter 2 (VMAT2) is responsible for transporting monoamine neurotransmitters such as serotonin, dopamine, and norepinephrine from the cytoplasm into synaptic vesicles. This VMAT2 mediated transport governs essential brain pathways, controlling functions like movement, sleep, and mood regulation. Dysfunction in these pathways is implicated in various psychiatric or neurodegenerative disorders, making VMAT2 a promising drug target. This study utilized a structure-based approach to identify novel VMAT2 inhibitor candidates. Initially, molecular docking identified several promising compounds when compared to standard inhibitors. Three novel compounds (S31, S42, and S48) that bind to VMAT2′s active site were further evaluated using molecular dynamics (MD) simulations, and their binding-free energies were calculated. Among these, S42 formed the most stable complex with VMAT2, exhibiting the lowest binding free energy and interacting with key residues such as Val-232 and Leu-37, which may confer selectivity. Additionally, S42 demonstrated superior binding strength in pulling simulations relative to other candidates and standard molecules. Umbrella sampling simulations further supported S42 as a strong candidate for VMAT2 inhibition. In conclusion, S42 warrants further investigation to fully explore its therapeutic potential.

Construction and validation of a regulatory T cells-based classification of renal cell carcinoma: an integrated bioinformatic analysis and clinical cohort study.

Renal cell carcinoma (RCC), exhibiting remarkable heterogeneity, can be highly infiltrated by regulatory T cells (Tregs). However, the relationship between Treg and the heterogeneity of RCC remains to be explored. We acquired single-cell RNA-seq profiles and 537 bulk RNA-seq profiles of TCGA-KIRC cohort. Through clustering, monocle2 pseudotime and prognostic analyses, we identified Treg states-related prognostic genes (TSRPGs), then constructing the RCC Treg states-related prognostic classification (RCC-TSC). We also explored its prognostic significance and multi-omics landmarks. Additionally, we utilized correlation analysis to establish regulatory networks, and predicted candidate inhibitors. More importantly, in Xinhua cohort of 370 patients with kidney neoplasm, we used immunohistochemical (IHC) staining for classification, then employing statistical analyses including Chi-square tests and multivariate Cox proportional hazards regression analysis to explore its clinical relevance. We defined 44 TSRPGs in four different monocle states, and identified high immune infiltration RCC (HIRC, LAG3+, Mki67+) as the highly exhausted subtype with the worst prognosis in RCC-TSC (p < 0.001). BATF-LAG3-immune cells axis might be its underlying metastasis-related mechanism. Immunotherapy and inhibitors including sunitinib potentially conferred best therapeutic effects for HIRC. Furthermore, we successfully validated HIRC subtype as an independent prognostic factor within the Xinhua cohort (OS, HR = 16.68, 95% CI = 1.88-148.1, p = 0.011; PFS, HR = 4.43, 95% CI = 1.55-12.6, p = 0.005). Through integrated bioinformatics analysis and a large-sample retrospective clinical study, we successfully established RCC-TSC and a diagnostic kit, which could stratify RCC patients with different prognosis and to guide personalized treatment.

Is it feasible to use AI-based drug design methods in the process of generating effective COVID-19 inhibitors? A validation study using molecular docking, molecular simulation, and pharmacophore methods

Although the COVID-19 pandemic has been brought under control to some extent globally, there is still debate in the industry about the feasibility of using artificial intelligence (AI) to generate COVID small-molecule inhibitors. In this study, we explored the feasibility of using AI to design effective inhibitors of COVID-19. By combining a generative model with reinforcement learning and molecular docking, we designed small-molecule inhibitors targeting the COVID-19 3CLpro enzyme. After screening based on molecular docking scores and physicochemical properties, we obtained five candidate inhibitors. Furthermore, theoretical calculations confirmed that these candidate inhibitors have significant binding stability with COVID-19 3CLpro, comparable to or better than existing COVID-19 inhibitors. Additionally, through ligand-based pharmacophore model screening, we validated the effectiveness of the generative model, demonstrating the potential value of AI in drug design.

In Silico Structural Insights and Potential Inhibitor Identification Based on the Benzothiazole Core for Targeting Leishmania major Pteridine Reductase 1.

Leishmaniasis is reported as the second most common protozoonosis, with the highest prevalence and mortality rate. Among the Leishmania drug targets, Pteridine Reductase 1 of Leishmania major (LmPTR1) proved to be promising because Leishmania is auxotrophic for folates. Thus, this study employed a combination of ligand- and structure-based approaches to screen new benzothiazole compounds as LmPTR1 inhibitor candidates. Initially, a highly predictive quantitative structure-activity relationship (QSAR) model was able to identify the relevant hybrid descriptors, with an accuracy of over 93%. Insights into the mechanism of action indicated Phe113, His241, Leu188, Met183, and Leu226 as key residues. New commercially available compounds were screened using QSAR, docking, and pharmacokinetic properties as filters. Molecular dynamics, non-covalent interactions analysis, and quantum chemical calculation of binding enthalpy demonstrated that the lead compound (ZINC 72229720) forms a stable complex with LmPTR1, indicating it as a new promising LmPTR1 inhibitor.

Corrosion Inhibition of Carbon Steel Immersed in Standardized Reconstituted Geothermal Water and Individually Treated with Four New Biosourced Oxazoline Molecules

The current demand for heat production via geothermal energy is increasingly rising amid concerns surrounding non-renewable forms of energy. The Dogger aquifer in the Paris Basin (DAPB) in France produces saline geothermal waters (GWs), which are as hot as 70–85 °C, anaerobic, slightly acidic (pH 6.1–6.4), and characterized mainly by the presence of Cl−, SO42−, CO2/HCO3−, and H2S/HS−. These GWs are corrosive, and the casings of all geothermal wells are carbon steel. Since 1989, these GWs have been progressively treated using petrosourced organic corrosion inhibitors (PS–OCI) at the bottom of the production wells. Currently, there is a great need to test not only new PS–OCIs but also, and above all, biosourced organic corrosion inhibitors (BS–OCIs) to improve the efficiency and environmental friendliness of this carbon-free geothermal energy source. The main objective of this study is to evaluate the potential performance of biosourced corrosion inhibitor candidates (BS–CICs) in terms of their inhibition efficiency (IE) for carbon steel corrosion. This was achieved using a previously established geochemical and electrochemical method to study the mechanisms and kinetics of the corrosion/scaling of carbon steel and optimize short-term corrosion inhibition in standardized reconstituted geothermal water (SRGW) representative of the DAPB’s waters. Four new molecules from the 2-oxazoline family were evaluated individually and compared based on their behavior and inhibition efficiency. These molecules exhibited a mixed nature (i.e., anodic and cathodic inhibitors), with a slight anodic predominance, and showed a significant IE at a concentration of at 10 mg/L during the first hours of immersion of CS-XC38 in SRGW. The average IEs, obtained via the three electrochemical techniques used for the determination of corrosion current densities, i.e., Jcorr(Rp), Jcorr(Tafel), and Jcorr(Rw), are 51%, 79%, 96%, and 93% for Decenox (C10:1), Decanox (C10:0), Undecanox (C11:0), and Tridecanox (C13:0), respectively.

Expedited SARS‐CoV‐2 Main Protease Inhibitor Discovery through Modular ‘Direct‐to‐Biology’ Screening

AbstractReactive fragment (RF) screening has emerged as an efficient method for ligand discovery across the proteome, irrespective of a target's perceived tractability. To date, however, the efficiency of subsequent optimisation campaigns has largely been low‐throughput, constrained by the need for synthesis and purification of target compounds. We report an efficient platform for ‘direct‐to‐biology’ (D2B) screening of cysteine‐targeting chloroacetamide RFs, wherein synthesis is performed in 384‐well plates allowing direct assessment in downstream biological assays without purification. Here, the developed platform was used to optimise inhibitors of SARS‐CoV‐2 main protease (MPro), an established drug target for the treatment of COVID‐19. An initial RF hit was developed into a series of potent inhibitors, and further exploration using D2B screening enabled a ‘switch’ to a reversible inhibitor series. This example of ligand discovery for MPro illustrates the acceleration that D2B chemistry can offer for optimising RFs towards covalent inhibitor candidates, as well as providing future impetus to explore the evolution of RFs into non‐covalent ligands.

Expedited SARS-CoV-2 Main Protease Inhibitor Discovery through Modular 'Direct-to-Biology' Screening.

Reactive fragment (RF) screening has emerged as an efficient method for ligand discovery across the proteome, irrespective of a target's perceived tractability. To date, however, the efficiency of subsequent optimisation campaigns has largely been low-throughput, constrained by the need for synthesis and purification of target compounds. We report an efficient platform for 'direct-to-biology' (D2B) screening of cysteine-targeting chloroacetamide RFs, wherein synthesis is performed in 384-well plates allowing direct assessment in downstream biological assays without purification. Here, the developed platform was used to optimise inhibitors of SARS-CoV-2 main protease (MPro), an established drug target for the treatment of COVID-19. An initial RF hit was developed into a series of potent inhibitors, and further exploration using D2B screening enabled a 'switch' to a reversible inhibitor series. This example of ligand discovery for MPro illustrates the acceleration that D2B chemistry can offer for optimising RFs towards covalent inhibitor candidates, as well as providing future impetus to explore the evolution of RFs into non-covalent ligands.

Synthesis and Fungicidal Activities of Coumarin Derivatives as Succinate Dehydrogenase Inhibitors.

Succinate dehydrogenase inhibitors (SDHIs) have been developed to the fastest growing family of fungicides. To develop novel succinate dehydrogenase (SDH) inhibitors, 27 novel non-amides coumarin derivatives were designed, synthesized, and characterized. The bioassay revealed that most of the target compounds exhibited significant antifungal activity against Botrytis cinerea in vitro. Notably, compounds 1a and 2c with EC50 values of 0.92 and 0.52µg/mL, respectively, which were better than that of positive control chlorothalonil (EC50=3.14µg/mL). Moreover, in vivo antifungal assay results showed that compound 2c could observably inhibit the growth of B. cinerea on Kuerla pears with remarkable protective at a dosage of 200µg/mL. The scanning electron microscopy (SEM) and transmission electron microscopy (TEM) investigation indicated that compound 2c significantly damaged the cell structures of B. cinerea mycelium. Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were analyzed for structure-activity relationships of all target compounds. Furthermore, molecular docking revealed that compound 2c was able to bind closely to the receptor protein of SDH. Enzyme activity analysis also further verified its inhibitory effect. These results demonstrated that compound 2c may be potential candidate for novel SDH inhibitors, and these results afforded further valuable reference for SDHIs discovery.

Kinase-Bench: Comprehensive Benchmarking Tools and Guidance for Achieving Selectivity in Kinase Drug Discovery.

Developing selective kinase inhibitors remains a formidable challenge in drug discovery because of the highly conserved structural information on adenosine triphosphate (ATP) binding sites across the kinase family. Tailoring docking protocols to identify promising kinase inhibitor candidates for optimization has long been a substantial obstacle to drug discovery. Therefore, we introduced "Kinase-Bench," a pioneering benchmark suite designed for an advanced virtual screen, to improve the selectivity and efficacy of kinase inhibitors. Our comprehensive data set includes 6875 selective ligands and 422,799 decoys for 75 kinases, using extensive bioactivity and structural data from the ChEMBL database and decoys generated by the Directory of Useful Decoys-Enhanced version. Our benchmarking sets and retrospective case studies were designed to provide useful guidance in discovering selective kinase inhibitors. We employed a Glide High-Throughput Virtual Screen and Standard Precision complemented by three scoring functions and customized protein-ligand interaction filters that target specific kinase residue interactions. These innovations were successfully implemented in our virtual screen efforts targeting JAK1 inhibitors, achieving selectivity against its family member, TYK2. Consequently, we identified novel potential hits: Compound 2 (JAK1 IC50: 980.5 nM, TYK2 IC50: 4.5 μM) and the approved pan-AKT inhibitor Capivasertib (JAK1 IC50: 275.9 nM, TYK2 IC50: 10.9 μM). Using the Kinase-Bench protocol, both compounds demonstrated substantial JAK1 selectivity, making them strong candidates for further investigation. Our pharmaceutical results underscore the utility of tailored virtual screen protocols in identifying selective kinase inhibitors with substantial implications for rational drug design. Kinase-Bench offers a robust toolset for selective kinase drug discovery with the potential to effectively guide future therapeutic strategies effectively.

KAHA ligation as a platform for the rapid discovery of Protein Tyrosine phosphatase 1B (PTP1B) inhibitors.

We have successfully designed and assembled a 66-member library of protein tyrosine phosphatases (PTP) inhibitor candidates using α-ketoacid-hydroxylamine (KAHA) ligation. Subsequent in situ enzymatic screening revealed a potent hit (IC50=1.67μM) against PTP1B, which displayed 6.8- to 50-fold selectivity over other phosphatases.