Identification and evaluation of small-molecule inhibitors against the dNTPase SAMHD1 <i>via</i> a comprehensive screening funnel
Bibliographic record
Abstract
Abstract Sterile alpha motif and histidine-aspartic acid domain containing protein-1 (SAMHD1) is a deoxynucleoside triphosphate (dNTP) triphosphohydrolase central to cellular nucleotide pool homeostasis. Recent literature has also demonstrated how SAMHD1 can detoxify chemotherapy metabolites thereby controlling their clinical responses. To further understand SAMHD1 biology and to investigate the potential of targeting this enzyme as a neoadjuvant to existing chemotherapies we set out to discover selective small molecule-based inhibitors of SAMHD1. Here we report a discovery pipeline encompassing a biochemical screening campaign and a set of complementary biochemical, biophysical, and cell-based readouts for further characterisation of the screen output. The identified hit compound TH6342 and its analogues, accompanied by their inactive negative control analogue TH7126, demonstrated specific, low μM potency in inhibiting the hydrolysis of both natural substrates and nucleotide analogue therapeutics, shown using complementary enzyme-coupled and direct enzymatic activity assays. Their mode of inhibition was subsequently detailed by coupling kinetic studies with thermal shift assays, where TH6342 and analogues were shown to engage with pre-tetrameric SAMHD1 and deter the oligomerisation and allosteric activation of SAMHD1 without occupying nucleotide binding pockets. We further outline the development and application of multiple cellular assays for assessing cellular target engagement and associated functional effects, including CETSA and an in-cell dNTP hydrolase activity assay, which highlighted future optimisation strategies of this chemotype. In summary, with a novel mode of inhibition, TH6342 and analogues broaden the set of tool compounds available in deciphering SAMHD1 enzymology and functions, and furthermore, the discovery pipeline reported herein represents a thorough framework for future SAMHD1 inhibitor development. Abstract Figure
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".