Identifying SARS-CoV-2 antiviral compounds by screening for small molecule inhibitors of Nsp5 main protease

The coronavirus 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), spread around the world with unprecedented health and socio-economic effects for the global population. While different vaccines are now being made available, very few antiviral drugs have been approved. The main viral protease (nsp5) of SARS-CoV-2 provides an excellent target for antivirals, due to its essential and conserved function in the viral replication cycle. We have expressed, purified and developed assays for nsp5 protease activity. We screened the nsp5 protease against a custom chemical library of over 5000 characterised pharmaceuticals. We identified calpain inhibitor I and three different peptidyl fluoromethylketones (FMK) as inhibitors of nsp5 activity in vitro, with IC(50) values in the low micromolar range. By altering the sequence of our peptidomimetic FMK inhibitors to better mimic the substrate sequence of nsp5, we generated an inhibitor with a subnanomolar IC(50). Calpain inhibitor I inhibited viral infection in monkey-derived Vero E6 cells, with an EC(50) in the low micromolar range. The most potent and commercially available peptidyl-FMK compound inhibited viral growth in Vero E6 cells to some extent, while our custom peptidyl FMK inhibitor offered a marked antiviral improvement

Mechanism-Based Screen for G1/S Checkpoint Activators Identifies a Selective Activator of EIF2AK3/PERK Signalling

Human cancers often contain genetic alterations that disable G1/S checkpoint control and loss of this checkpoint is thought to critically contribute to cancer generation by permitting inappropriate proliferation and distorting fate-driven cell cycle exit. The identification of cell permeable small molecules that activate the G1/S checkpoint may therefore represent a broadly applicable and clinically effective strategy for the treatment of cancer. Here we describe the identification of several novel small molecules that trigger G1/S checkpoint activation and characterise the mechanism of action for one, CCT020312, in detail. Transcriptional profiling by cDNA microarray combined with reverse genetics revealed phosphorylation of the eukaryotic initiation factor 2-alpha (EIF2A) through the eukaryotic translation initiation factor 2-alpha kinase 3 (EIF2AK3/PERK) as the mechanism of action of this compound. While EIF2AK3/PERK activation classically follows endoplasmic reticulum (ER) stress signalling that sets off a range of different cellular responses, CCT020312 does not trigger these other cellular responses but instead selectively elicits EIF2AK3/PERK signalling. Phosphorylation of EIF2A by EIF2A kinases is a known means to block protein translation and hence restriction point transit in G1, but further supports apoptosis in specific contexts. Significantly, EIF2AK3/PERK signalling has previously been linked to the resistance of cancer cells to multiple anticancer chemotherapeutic agents, including drugs that target the ubiquitin/proteasome pathway and taxanes. Consistent with such findings CCT020312 sensitizes cancer cells with defective taxane-induced EIF2A phosphorylation to paclitaxel treatment. Our work therefore identifies CCT020312 as a novel small molecule chemical tool for the selective activation of EIF2A-mediated translation control with utility for proof-of-concept applications in EIF2A-centered therapeutic approaches, and as a chemical starting point for pathway selective agent development. We demonstrate that consistent with its mode of action CCT020312 is capable of delivering potent, and EIF2AK3 selective, proliferation control and can act as a sensitizer to chemotherapy-associated stresses as elicited by taxanes

Mechanism-based screen for G1/S checkpoint activators identifies a selective activator of EIF2AK3/PERK signalling.

Human cancers often contain genetic alterations that disable G1/S checkpoint control and loss of this checkpoint is thought to critically contribute to cancer generation by permitting inappropriate proliferation and distorting fate-driven cell cycle exit. The identification of cell permeable small molecules that activate the G1/S checkpoint may therefore represent a broadly applicable and clinically effective strategy for the treatment of cancer. Here we describe the identification of several novel small molecules that trigger G1/S checkpoint activation and characterise the mechanism of action for one, CCT020312, in detail. Transcriptional profiling by cDNA microarray combined with reverse genetics revealed phosphorylation of the eukaryotic initiation factor 2-alpha (EIF2A) through the eukaryotic translation initiation factor 2-alpha kinase 3 (EIF2AK3/PERK) as the mechanism of action of this compound. While EIF2AK3/PERK activation classically follows endoplasmic reticulum (ER) stress signalling that sets off a range of different cellular responses, CCT020312 does not trigger these other cellular responses but instead selectively elicits EIF2AK3/PERK signalling. Phosphorylation of EIF2A by EIF2A kinases is a known means to block protein translation and hence restriction point transit in G1, but further supports apoptosis in specific contexts. Significantly, EIF2AK3/PERK signalling has previously been linked to the resistance of cancer cells to multiple anticancer chemotherapeutic agents, including drugs that target the ubiquitin/proteasome pathway and taxanes. Consistent with such findings CCT020312 sensitizes cancer cells with defective taxane-induced EIF2A phosphorylation to paclitaxel treatment. Our work therefore identifies CCT020312 as a novel small molecule chemical tool for the selective activation of EIF2A-mediated translation control with utility for proof-of-concept applications in EIF2A-centered therapeutic approaches, and as a chemical starting point for pathway selective agent development. We demonstrate that consistent with its mode of action CCT020312 is capable of delivering potent, and EIF2AK3 selective, proliferation control and can act as a sensitizer to chemotherapy-associated stresses as elicited by taxanes

Discovery of a Potent and Selective Covalent Inhibitor and Activity-Based Probe for the Deubiquitylating Enzyme UCHL1, with Anti-Fibrotic Activity

Ubiquitin carboxy-terminal hydrolase L1 (UCHL1) is a deubiquitylating enzyme which is proposed as a potential therapeutic target in neurodegeneration, cancer, and liver and lung fibrosis. Herein we report the discovery of the most potent and selective UCHL1 probe (IMP-1710) to date based on a covalent inhibitor scaffold and apply this probe to identify and quantify target proteins in intact human cells. IMP-1710 stereoselectively labels the catalytic cysteine of UCHL1 at low nanomolar concentration in cells, and we show that a previously claimed UCHL1 inhibitor (LDN-57444) fails to engage UCHL1 in cells. We further demonstrate that potent UCHL1 inhibitors block pro-fibrotic responses in a cellular model of idiopathic pulmonary fibrosis, supporting a potential therapeutic role for UCHL1 inhibition and providing a basis for future therapeutic development of selective UCHL1 inhibitors

ZDHHC_lipidomics_2023.zip

Lipidomics Methods Lipid extraction: HEK293T cells were seeded in 6-well plates, grown to 70% confluency and treated with bumped fatty acid probes (15 µM) for 4 h. Cells were dislodged into their growth media by pipetting and pelleted by centrifugation (500 x g, 5 min). The cell pellet was washed 2X with ice-cold PBS and pelleting by centrifugation. Subsequently, the cells were resuspended in 500 µL of ice-cold 150 mM ammonium bicarbonate. An aliquot (10%) was kept aside for protein concentration determination and the remaining sample snap-frozen in liquid nitrogen and stored at -80°C until further processing. For protein concentration determination, cells were lysed in M-PER™ Mammalian Protein Extraction Reagent (Thermo Fisher, 78501) and protein content determined using the Pierce™ BCA Protein Assay Kit (Thermo Fisher, 23227) as per the manufacturer’s instructions. An aliquot equivalent to 100 µg protein per sample were used for lipid extraction. Lipid were extracted by the methyl-tert-butyl ether (MTBE) method with minor modifications62. Extractions were performed in glass vials fitted with Teflon-lined caps using MS-grade solvents and water. Glass pipettes were used to handle any MTBE-containing solutions or lipid extracts. Methanol (1.5 mL) was added and the protein sample vortexed. MTBE (5 mL) was added and the mixture was incubated for 1 h at RT on a shaker. Phase separation was induced by the addition of water (1.25 mL) followed by incubation for 10 min at room temperature. The sample was centrifuged (1,000 x g, 10 min) and the upper organic phase collected. The lower aqueous phase was re-extracted by addition of 1.67 mL of solvent mixture comprising MTBE/methanol (10:3, v/v) and 0.32 mL water. The samples were vortexed, incubated for 10 min and centrifuged (1000 x g, 10 min). The upper phase was recovered, and the combined organic phases were evaporated at 37°C under a stream of nitrogen and stored at -20°C. Lipid extracts were reconstituted in 100 µL loading buffer (isopropanol/water/acetonitrile, 2:1:1, v/v/v). Blank control extraction was performed on a 200 µL aliquot of 150 mM ammonium bicarbonate solution. Quality control (QC) samples were prepared by pooling a small aliquot of all experimental samples after resuspension in loading buffer. Ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS): Analysis was performed on a 1290 Infinity II UHPLC system coupled to a 6550 iFunnel quadrupole time-of-flight (QTOF) mass spectrometer (Agilent Technologies). The reversed-phase chromatography protocol was optimized with minor modifications from Cajka and Fiehn63. Extracted lipids were separated on an Acquity UPLC CSH C18 column (130 Å, 1.7 μm, 2.1 x 100 mm) fitted with an Acquity UPLC CSH C18 VanGuard pre-column (130 Å, 1.7 µm, 2.1 mm x 5 mm) (both Waters). The column was maintained at 65°C at a flowrate of 0.6 mL/min. The mobile phases used were 60:40 (v:v) acetonitrile/H2O (solvent A) and 10:90 (v:v) acetonitrile/isopropanol (solvent B). Solvent A and B were supplemented with 10 mM ammonium formate and 0.1% formic acid for ESI positive mode and with 10 mM ammonium acetate for ESI negative mode analysis. UHPLC gradient elution was carried out as follows: 0−2 min 15-30% B; 2-2.5 min 30-48% B; 2.5−11 min 48-82% B; 11-11.5 min 82-99% B; 11.5-14.50 min 99% B. The gradient was returned to initial conditions over 0.5 min and the column equilibrated for 3 min before subsequent runs. Between injections a 100% isopropanol needle wash was performed. For negative mode 5 µL (MS mode) or 10 µL (MS/MS mode) of sample and for positive mode 4 µL (MS mode) or 8 µL (MS/MS mode) of sample were injected. Samples were injected in randomized order, with QC sample injections added to the start, middle and end of each sample sequence to ensure consistency and reproducibility of all acquisition parameters. Samples were loaded in a random order by blinded selection from pooled anonymously labelled samples. Electrospray parameters were set as follows: gas and sheath gas temperature, 200°C; drying gas flow, 14 L/min; sheath gas flow, 11 L/min; sheath gas temperature, 350°C; nebulizer pressure, 35 psig; capillary voltage, 3,000 V; nozzle voltage, 1,000 V. MS-TOF fragmentor and Oct 1 RF Vpp radio voltage were set to 350 and 750 V respectively. The QTOF was calibrated and operated in the extended dynamic range mode (∼2 GHz) in the mass range 50 to 1700 m/z. Spectra were acquired in centroid mode with an acquisition rate of 2 spectra/s for MS mode acquisition. Data was acquired in MS mode for quantitative analysis of the natural lipidome, and MS/MS mode to obtain data for lipid structure assignment. MS/MS data was acquired in auto-MS/MS mode (data-dependent). Spectra were acquired in centroid mode with an acquisition rate of 1 and 5 spectra/s for MS and MS/MS acquisition, respectively. Collision energy was adjusted to -35 eV and 30 eV for negative and positive modes, respectively. Mass range for precursor selection was 300-1650 m/z (negative) and 250-1680 m/z (positive). Fragmentation was triggered if the precursor reached 5000 (negative) or 2000 (positive) counts and maximum precursors per cycle was set to 5. MS/MS isolation width for precursors was selected as narrow (1.3 m/z). Active exclusion was enabled, set to exclude after 3 spectra and release after 0.1 min. To improve precursor selection, background ions were added to an exclusion list. For structure determination of probe-derived lipids, a list of preferred precursor ions was generated for each probe to improve MS/MS coverage of features originating from probe metabolism. MS/MS analysis of DMSO control samples were used to confirm assignment of natural lipids. Quantitative analysis of natural lipidome: Lipid annotations and quantifications were performed following the guidelines of the Lipidomics Standard Initiative (https://lipidomics-standards-initiative.org/). Feature extraction was carried out in Mass Hunter Profinder (v. 10.0, Agilent Technologies) using the “Batch Targeted Feature Extraction” option. Features were matched to an in-house library containing mass and retention time information of lipid species including glycerophospholipids, sphingolipids, fatty acids and glycolipids. All lipids in the database were previously assigned from MS/MS data using MS-DIAL64 followed by manual curation. H+, Na+ and NH4+ adducts were selected for positive mode and H−, C2H3O2− and CHO2− adducts were selected for negative mode data. Both mass and retention time were required for feature matching. Match tolerance was set to 5 ppm for mass and 0.15 min for retention time. The EIC extraction range was limited to +/- 0.3 min of the expected retention time. An overall score of >70 was required for feature matching, with the contribution to overall score set as follows: Mass score 100, Isotope abundance score 60, Isotope spacing score 50, Retention time score 100. Features over 20% of saturation limit were excluded from the dataset. Matched features were manually inspected and re-integrated where required and checked for correct adduct pattern for the relevant lipid class. Data were exported as .csv files containing the identity, peak area and the retention time of each lipid species. Further data analysis and data representation was performed in Excel and GraphPad Prism. The relative abundance of each lipid species within a class was calculated as a percentage of the summed peak areas of all species identified within the class. TG species were quantified from data acquired in positive mode while all other species were quantified from data acquired in negative mode. n=5 for each experimental condition. Assignment of probe-derived lipids: Feature extraction of data acquired in MS mode was carried out in Mass Hunter Profinder (v. 10.0, Agilent Technologies) using the “Batch Recursive Feature Extraction (small molecule/peptide)” option. Samples were grouped according to experimental condition. All parameters except those detailed below were used as pre-set by the program. Peak heights were set to a minimum of 3000 counts. H+, Na+ and NH4+ adducts were selected for positive mode and H−, C2H3O2− and CHO2− adducts were selected for negative mode. For compound binning and alignment, retention time tolerance was set to (+/- 0% + 0.15 min) and mass tolerance to (+/- 5 ppm + 2 mDa). A MFE score of at least 70 was required in at least 4 of 6 samples per group. For match tolerance, the mass was set to +/- 10 ppm and retention time to +/- 0.15 min. The EIC extraction range was limited to +/- 0.15 min of the expected retention time. An overall score of >75 was required for feature matching, with the contribution to overall score set as follows: Mass score 100, Isotope abundance score 60, Isotope spacing score 50, Retention time score 100. Features over 20% of saturation limit were excluded from the dataset. Post-processing filters were set to require a score (Tgt) of at least 50 in 4 out of 6 samples per experimental group. Manual filtering was performed to remove features present in the blank extraction samples. To create a list of features originating from probe metabolism, only features unique to each probe condition were selected. All features present in DMSO control samples were discarded. Features were manually inspected and re-integrated where required. The feature lists were used to create inclusion lists for MS/MS analysis and peak lists for lipid annotations as described below. </p

ZDHHC_metabolomics_chemgen_2023.zip

MetabolomicsAcyl- and probe-Coenzyme A analysis.HEK293T cells were seeded in 6-well plates, grown to 70% confluency in media containing 0.5% FBS and treated with 30 mM YnPal or 18-Bz for 2 h. Cells were dislodged into their growth media by pipetting and pelleted by centrifugation (500 x g, 5 min). The cell pellet was washed twice by resuspending in ice-cold PBS and pelleting by centrifugation.Sample extractionTo each sample, 400 µL chloroform was added and vortexed for ~1 min, followed by addition of 200 µL methanol and a repeated vortex. Samples were incubated in a water bath sonicator (4°C, 1 h), with 3 × 8 min sonication pulses, followed by centrifugation (4°C, 10 min, 17,000 x g). The supernatant was transferred to a new Eppendorf 1.5 mL tube (E1). The pellet was re-extracted with 450 µL methanol:water (2:1 v:v, containing internal standard, 13C3-Malonyl-CoA), sonicated (8 min, 4°C) and centrifuged, as above. The supernatant was added to the first extract (E1). Combined extracts were dried using a speedvac concentrator, re-suspended in 350 µL chloroform:methanol:water (1:3:3, v/v), and centrifuged, as above. The upper, aqueous phase containing the polar metabolites (including probe, probe-CoA, and acyl-CoA molecules) was dried using the speedvac concentrator and resuspended in 100 µL acetonitrile/ammonium carbonate 20 mM (7:3, v/v) for LC-MS injection.Liquid chromatography-mass spectrometry (LC-MS)Chromatography conditions:Chromatography prior to all mass spectrometry was performed using an adaptation of a method previously described61. Samples were injected into a Dionex UltiMate 3000 LC system (Thermo Fisher) with a Phenomenex Luna C18(2) 100 Å (100 x 2 mm, 3 μm) column coupled with a SecurityGuard C18 guard column (4 x 2 mm). Analytes were separated using 20 mM ammonium carbonate in water (Optima HPLC grade, Sigma Aldrich) as solvent A and acetonitrile (Optima HPLC grade, Sigma Aldrich) as solvent B at 0.3 mL/min flow rate. Elution began at 5% Solvent B, maintained for 3 min, increased to 100% B over 12 min, followed by a 3 min wash of 100% B and subsequent 3 min re-equilibration to 5% B. Other parameters were as follows: column temperature, 30°C; injection volume, 10 μL; needle wash, 50% methanol; autosampler temperature, 4°C.High resolution mass spectrometryPost-chromatography, high resolution (HR) MS was performed with positive and negative polarity switching using a Q-Exactive Orbitrap (Thermo Fisher) with a HESI-II (Heated electrospray ionization) probe. MS parameters were as follows: spray voltage, 3.5 kV and 3.2 kV (for positive and negative modes, respectively); probe temperature, 320°C; sheath and auxiliary gases, 30 and 5 arbitrary units (au), respectively; full scan range: 100 to 1300 m/z with settings of AGC target and resolution as Balanced and High (3 × 106 and 70,000), respectively. Data were recorded using Xcalibur 3.0.63 software (Thermo Fisher). Mass calibration was performed for both ESI polarities before analysis using the standard Thermo Fisher Calmix solution. Qualitative analysis was performed using Xcalibur FreeStyle 1.8 SP1 and Tracefinder 5.1 software (Thermo Fisher) according to the manufacturer’s workflows. Masses, retention times, and fragmentation of all relevant sample-derived molecules were compared to authentic chemical standards.MS/MS MS parameters were optimized by direct infusion of 16 μM acyl-CoAs dissolved in 10 mM MeOH/ammonium acetate at 5 μL/min into an TSQ Quantiva triple quadrupole MS (Thermo Fisher). The heated electrospray was set in positive mode with the following parameters: capillary voltage, 3472 V; sheath gas, 60 au; aux gas, 10 au; sweep gas, 1 au; ion transfer tube temp, 325°C; vaporizer temp, 275°C. A selected reaction monitoring (SRM) function was applied for the simultaneous detection of acyl-CoA and probe-CoA molecules with RF lens and collision energies as shown in the Supplementary Table 7. Data were recorded using the Xcalibur 4.0.27.10 software and analysed using QuanBrowser 4.5.445.18 (Thermo Fisher).</p