Bibliographic record
Abstract
Since I started doing scientific research, I've been fascinated by the interplay of protein structure and dynamics and how they together mediate protein function. A particular area of interest has been in understanding the mechanistic basis of how lipid-signaling enzymes function on membrane surfaces. In this award lecture article, I will describe my laboratory's studies on the structure and dynamics of lipid-signaling enzymes on membrane surfaces. This is important, as many lipid-signaling enzymes are regulated through dynamic regulatory mechanisms that control their enzymatic activity. This article will discuss my continued enthusiasm in using a synergistic application of hydrogen-deuterium exchange MS (HDX-MS) with other structural biology techniques to probe the mechanistic basis for how membrane-localized signaling enzymes are regulated and how these approaches can be used to understand how they are misregulated in disease. I will discuss specific examples of how we have used HDX-MS to study phosphoinositide kinases and the protein kinase Akt. An important focus will be on a description of how HDX-MS can be used as a powerful tool to optimize the design of constructs for X-ray crystallography and EM. The use of a diverse toolbox of biophysical methods has revealed novel insight into the complex and varied regulatory networks that control the function of lipid-signaling enzymes and enabled unique insight into the mechanics of membrane recruitment.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".