Methods to Validate Binding and Kinetics of “Proximity‐Inducing” Covalent Immune‐Recruiting Molecules
Bibliographic record
Abstract
The emergence of covalent inhibitors and chemoproteomic probes in translational chemical biology research requires the development of robust biophysical and analytical methods to characterize their complex interactions with target biomolecules. Importantly, these methods must efficiently assess target selectivity and accurately discern noncovalent binding from the formation of resultant covalent adducts. One recently reported covalent chemical tool used in tumor immune oncology, covalent immune recruiters (CIRs), increases the proximity of immune cells and cancer cells, promoting immune recognition and response. Herein we describe biolayer interferometry (BLI) biosensor, flow cytometry, and solution fluorescence-based assay approaches to characterize CIR:antibody binding and CIR-antibody covalent-labeling kinetics. BLI technology, akin to surface plasmon resonance, provides the unique opportunity to investigate molecular binding and labeling kinetics both on a solid surface (Basic Protocol 1) and in solution (Alternate Protocol 1). Here, recruitment of mass-containing proteins to the BLI probe via CIR is measured with high sensitivity and is used as a readout of CIR labeling activity. Further, CIR technology is used to label antibodies with a fluorescent handle. In this system, labeling is monitored via SDS-PAGE with a fluorescence gel imager, where increased fluorescence intensity of a sample reflects increased labeling (Basic Protocol 2). Analysis of CIR:antibody target-specific immune activation is demonstrated with a flow cytometry-based antibody-dependent cellular phagocytosis (ADCP) assay (Basic Protocol 3). This ADCP protocol may be further used to discern CIR:antibody binding from covalent adduct formation (Alternate Protocol 3). For the protocols described, each method may be used to analyze characteristics of any covalent-tagging or antibody-recruiting small molecule or protein-based technology. © 2020 Wiley Periodicals LLC. Basic Protocol 1: Determining "on-probe" reaction kinetics of CIR1/CIR4 via biolayer interferometry with Octet RED96 Alternate Protocol 1: Determining "in-solution" reaction kinetics of prostate-specific membrane antigen targeting CIR (CIR3) via biolayer interferometry with Octet RED96 Basic Protocol 2: Reaction kinetics of covalently labeled antibodies via fluorescence SDS-PAGE Basic Protocol 3: Small molecule-directed antibody-dependent cellular phagocytosis on live human cells measured via flow cytometry Alternate Protocol 2: Kinetic analysis of CIR3:antibody labeling via antibody-dependent cellular phagocytosis on flow cytometry Support Protocol 1: Activation of U937 monocytes with interferon γ Support Protocol 2: Labeling streptavidin beads with biotinylated prostate-specific membrane antigen receptor.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 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".