Use of Substrate Analogs and Mutagenesis to Study Substrate Binding and Catalysis in the Sir2 Family of NAD-dependent Protein Deacetylases
Bibliographic record
Abstract
The Sir2 family of enzymes is highly conserved throughout evolution and functions in silencing, control of life span, apoptosis, and many other cellular processes. Since the discovery of the NAD-dependent deacetylase activity of Sir2 proteins, there has been a flurry of activity aiming to uncover the mode of substrate binding and catalysis. Structural and biochemical studies have led to several proposed reaction mechanisms, yet the exact catalytic steps remain unclear. Here we present in vitro studies of yeast homolog Hst2 that shed light on the mechanism of Sir2 proteins. Using acetyl-lysine substrate analogs, we demonstrate that the Hst2 reaction proceeds via an initial SN2-type mechanism with the direct formation of an ADP-ribose-acetyl-lysine intermediate. Kinetic studies further suggest that ADP-ribose inhibits the Hst2 reaction in a biologically relevant manner. Through biochemical and kinetic analyses of point mutants, we also clarify the role of several conserved core domain residues in substrate binding, stabilization of the ADP-ribose-acetyl-lysine intermediate, and catalysis. These findings bring us a few steps closer to understanding Sir2 activity and may provide a useful platform for the design of Sir2-specific inhibitors for analysis of Sir2 function and possibly therapeutic applications.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".