Solid-phase assays for small molecule screening using sol-gel entrapped proteinsThis paper is one of a selection of papers published in this Special Issue, entitled CSBMCB — Systems and Chemical Biology, and has undergone the Journal's usual peer review process.
Bibliographic record
Abstract
With compound libraries exceeding one million compounds, the ability to quickly and effectively screen these compounds against relevant pharmaceutical targets has become crucial. Solid-phase assays present several advantages over solution-based methods. For example, a higher degree of miniaturization can be achieved, functional- and affinity-based studies are possible, and a variety of detection methods can be used. Unfortunately, most protein immobilization methods are either too harsh or require recombinant proteins and thus are not amenable to delicate proteins such as kinases and membrane-bound receptors. Sol-gel encapsulation of proteins in an inorganic silica matrix has emerged as a novel solid-phase assay platform. In this minireview, we discuss the development of sol-gel derived protein microarrays and sol-gel based monolithic bioaffinity columns for the high-throughput screening of small molecule libraries and mixtures.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.007 |
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".