Structural studies of IPK1: how molecular turtles are made
Bibliographic record
Abstract
Inositol phosphates (IPs) are signaling molecules implicated in a variety of cellular processes, notably, cell survival signaling and vesicular trafficking, which underlie diseases such as cancer and diabetes. The specific roles of many IPs in disease states have yet to be determined. Inositol phosphate kinases (IPKs) phosphorylate inositol 1,4,5-trisphosphate (IP3) on different positions of its inositol ring to yield an array of unique IPs. Control of IP production at different stages of the IP metabolic pathway could be used as an approach to determine the functional roles of each IP. In this thesis, we focus on inositol 1,3,4,5,6-pentakisphosphate 2-kinase (IPK1), which phosphorylates IP5 to IP6. These two IPs regulate apoptosis in vitro and in vivo, revealing a role for IPK1 in cell death, but their precise mechanisms of action remain unresolved. Our overall goal was to structurally and biochemically characterize IPK1 to identify how it selects its substrates, how it is regulated, and how it may be targeted with small molecules to be used as tools to study IPK1 function. We determined the IP-free crystal structure of IPK1, which revealed that the N-lobe of IPK1 is unstable in the absence of substrate. Based on this observation, we hypothesized that IPK1 uses a mechanism of IP-induced stabilization to select IP5 as its substrate: IP5 is initially recognized by IPK1 through the 4-, 5-, and 6-phosphates, and then, the 1- and 3-phosphates induce N-lobe stabilization, thereby allowing IPK1 activation only when the appropriate IP is bound. The key interaction between R130 and the 1-phosphate of the IP stabilizes the N-lobe for subsequent kinase activation. To validate our hypothesis, we evaluated the role of each IP phosphate for IP binding and kinase activation. We determined that the 5- and 6-phosphates were more important for IP binding, while the 1- and 3-phosphates were more important for IPK1 activation. Moreover, we demonstrated that IPs lacking the 1- or 3-phosphates were unable to stabilize IPK1 to the same extent as IP5, and that artificial stabilization of the N-lobe by engineered disulfide bonds altered IPK1 substrate specificity, by reducing the need for N-lobe interactions with substrate. We also characterized PKRnc and Catechin Gallate as leads for the development of small molecule inhibitors of IPK1. Taken together, our studies provide a basis for the development of selective inhibitors for IPK1 to investigate the roles of IPs that modulate apoptotic signaling pathways. Moreover, IP-induced stabilization distinguishes IPK1 from other IPKs and provides important considerations for the selective inhibition of each IPK. Uncovering the role of IPs in different cellular processes may ultimately lead to novel treatments for diseases whose underlying mechanisms are mediated by IP signaling.
Stored with the screening record, where it is evidence for the labels above.
How this classification was reachedexpand
The three-model screen
all 5,600 screened works →All three models called this out of scope.
Doctoral dissertation on the structural biology of inositol phosphate kinase IPK1; the object is protein structure.
The dissertation studies the structure and biochemical function of a protein kinase.
Structural biology dissertation on IPK1 enzyme mechanism.
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) | 0.000 | 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 | 0.001 |
| 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".