Screening of Inhibitors Using Enzymes Entrapped in Sol−Gel-Derived Materials
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Bibliographic record
Abstract
In recent years, a number of new methods have been reported that make use of immobilized enzymes either on microarrays or in bioaffinity columns for high-throughput screening of compound libraries. A key question that arises in such methods is whether immobilization may alter the intrinsic catalytic and inhibition constants of the enzyme. Herein, we examine how immobilization within sol-gel-derived materials affects the catalytic constant (kcat), Michaelis constant (KM), and inhibition constant (KI) of the clinically relevant enzymes Factor Xa, dihydrofolate reductase, cyclooxygenase-2, and gamma-glutamyl transpeptidase. These enzymes were encapsulated into sol-gel-derived glasses produced from either tetraethyl orthosilicate (TEOS) or the newly developed silica precursor diglyceryl silane (DGS). It was found that the catalytic efficiency and long-term stability of all enzymes were improved upon entrapment into DGS-derived materials relative to entrapment in TEOS-based glasses, likely owing to the liberation of the biocompatible reagent glycerol from DGS. The KM values of enzymes entrapped in DGS-derived materials were typically higher than those in solution, whereas upon entrapment, kcat values were generally lowered by a factor of 1.5-7 relative to the value in solution, indicating that substrate turnover was limited by partitioning effects or diffusion through the silica matrix. Nonetheless, the apparent KI value for the entrapped enzyme was in most cases within error of the value in solution, and even in the worst case, the values differed by no more than a factor of 3. The implications of these findings for high-throughput screening are discussed.
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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) | 0.000 | 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 | 0.000 |
| 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 it