Determination of Active Concentrations and Association and Dissociation Rate Constants of Interacting Biomolecules: An Analytical Solution to the Theory for Kinetic and Mass Transport Limitations in Biosensor Technology and Its Experimental Verification
Bibliographic record
Abstract
Accurate determination of kinetic rate constants for interacting biomolecules requires knowledge of the active concentrations of the participating molecules. Also, in other biomedical and clinical applications, sensitive, precise and accurate methods are needed to determine the concentration of biologically active molecules, which frequently constitute only a fraction of the total molecular pool. Here we report a novel development of the approach to determining active concentrations based on surface plasmon resonance (SPR) technology. The method relies on changes in binding rates with varying flow rates under conditions of partial mass transport, and does not require standards of known concentrations, given that the molecular mass of the molecule of interest is known. We introduce an analytical solution to the differential equations describing the formation of a 1:1 bimolecular complex, taking into account both the association and dissociation reactions, under partial mass transport limitations. This solution can be used in global fitting to binding curves obtained at different flow rates. The accuracy, precision, and sensitivity of this approach were determined in experiments involving binding of tyrosine-phosphorylated recombinant proteins to anti-phosphotyrosine antibodies, where the active concentration could be determined independently by in vitro phosphorylation with (33)P. There was an excellent agreement between the active concentrations determined by the analytical SPR-based method and by determination of the level of radioactivity of the phosphorylated protein. The SPR-based method allows determination of protein concentrations at picomolar levels. A procedure for accurate determinations of association and dissociation rate constants, based on the analytical solution of the mass transport and binding theory, is outlined.
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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 | 0.008 | 0.019 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.007 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".