Degraders (e.g. PROTACs, SNIPERs, degronimers etc.) are a new modality offering increasing potential both as tools for basic research and therapeutic development.

Identifying protein-ligand binding interactions is a key step during early-stage drug discovery. Existing screening techniques are often associated with drawbacks such as low throughput, high sample consumption, and dynamic range limitations. The increasing use of fragment-based drug discovery (FBDD) demands that these techniques also detect very weak interactions (mM K(D) values). This paper presents the development and validation of a fully automated screen by mass spectrometry, capable of detecting fragment binding into the millimolar K(D) range. Low sample consumption, high throughput, and wide dynamic range make this a highly attractive, orthogonal approach. The method was applied to screen 157 compounds in 6 h against the anti-apoptotic protein target Bcl-x(L). Mass spectrometry results were validated using STD-NMR, HSQC-NMR, and ITC experiments. Agreement between techniques suggests that mass spectrometry offers a powerful, complementary approach for screening.

The high sensitivity and spectral resolution achievable with the Orbitrap technology confer significant advantages over TOF mass spectrometers, and offer a solution to current limitations regarding throughput, data analysis and sample requirements. A further benefit of improved spectral resolution is the possibility of using heterogeneous protein samples such as glycoproteins for fragment screening. This would significantly expand the scope of applicability of non-covalent MS in the pharmaceutical and other industries.

The transfer of the phosphopantetheine chain from coenzyme A (CoA) to the acyl carrier protein (ACP), a key protein in both fatty acid and polyketide synthesis, is catalyzed by ACP synthase (AcpS). Streptomyces coelicolor AcpS is a doubly promiscuous enzyme capable of activation of ACPs from both fatty acid and polyketide synthesis and catalyzes the transfer of modified CoA substrates. Five crystal structures have been determined, including those of ligand-free AcpS, complexes with CoA and acetyl-CoA, and two of the active site mutants, His110Ala and Asp111Ala. All five structures are trimeric and provide further insight into the mechanism of catalysis, revealing the first detailed structure of a group I active site with the essential magnesium in place. Modeling of ACP binding supported by mutational analysis suggests an explanation for the promiscuity in terms of both ACP partner and modified CoA substrates.

CIC-DUX4 sarcoma (CDS) is a highly aggressive and metastatic small round type of predominantly pediatric sarcoma driven by a fusion oncoprotein comprising the transcriptional repressor Capicua (CIC) fused to the C-terminal transcriptional activation domain of DUX4. CDS rapidly develops resistance to chemotherapy, thus novel specific therapies are greatly needed. We demonstrate that CIC-DUX4 requires P300/CBP to induce histone H3 acetylation, activate its targets, and drive oncogenesis. We describe the synthetic route to a selective and highly potent P300/CBP inhibitor named iP300w and related stereoisomers, and find that iP300w efficiently suppresses CIC-DUX4 transcriptional activity and reverses CIC-DUX4 induced acetylation. iP300w is active at 100-fold lower concentrations than related stereoisomers or A-485. At low doses, iP300w shows specificity to CDS cancer cell lines, rapidly inducing cell cycle arrest and preventing growth of established CDS xenograft tumors when delivered in vivo. The effectiveness of iP300w to inactivate CIC-DUX4 highlights a promising therapeutic opportunity for CDS.

SARS-CoV-2 is the causative agent behind the COVID-19 pandemic. The main protease (Mpro, 3CLpro) of SARS-CoV-2 is a key enzyme that processes polyproteins translated from the viral RNA. Mpro is therefore an attractive target for the design of inhibitors that block viral replication. We report the diastereomeric resolution of the previously designed SARS-CoV-2 Mpro α-ketoamide inhibitor 13b. The pure (S,S,S)-diastereomer, 13b-K, displays an IC50 of 120 nM against the Mpro and EC50 values of 0.8–3.4 μM for antiviral activity in different cell types. Crystal structures have been elucidated for the Mpro complexes with each of the major diastereomers, the active (S,S,S)-13b (13b-K), and the nearly inactive (R,S,S)-13b (13b-H); results for the latter reveal a novel binding mode. Pharmacokinetic studies show good levels of 13b-K after inhalative as well as after peroral administration. The active inhibitor (13b-K) is a promising candidate for further development as an antiviral treatment for COVID-19.

Serum and plasma are commonly used in metabolomic-epidemiology studies. Their metabolome is susceptible to differences in pre-analytical conditions and the impact of this is unclear. Participant-matched EDTA-plasma and serum samples were collected from 37 non-fasting volunteers and profiled using a targeted nuclear magnetic resonance (NMR) metabolomics platform (n = 151 traits). Correlations and differences in mean of metabolite concentrations were compared between reference (pre-storage: 4 °C, 1.5 h; post-storage: no buffer addition delay or NMR analysis delay) and four pre-storage blood processing conditions, where samples were incubated at (i) 4 °C, 24 h; (ii) 4 °C, 48 h; (iii) 21 °C, 24 h; and (iv) 21 °C, 48 h, before centrifugation; and two post-storage sample processing conditions in which samples thawed overnight (i) then left for 24 h before addition of sodium buffer followed by immediate NMR analysis; and (ii) addition of sodium buffer, then left for 24 h before NMR profiling. We used multilevel linear regression models and Spearman’s rank correlation coefficients to analyse the data. Most metabolic traits had high rank correlation and minimal differences in mean concentrations between samples subjected to reference and the different conditions tested, that may commonly occur in studies. However, glycolysis metabolites, histidine, acetate and diacylglycerol concentrations may be compromised and this could bias results in association/causal analyses.

No abstract