MétaCan
Menu
Back to cohort
Record W4388288471 · doi:10.1021/acscentsci.3c01052

Offsetting Low-Affinity Carbohydrate Binding with Covalency to Engage Sugar-Specific Proteins for Tumor-Immune Proximity Induction

2023· article· en· W4388288471 on OpenAlex
Benjamin Lake, Anthony F. Rullo

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueACS Central Science · 2023
Typearticle
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaCancer Research Society
KeywordsChemistryBiochemistryImmune systemAntibodyAvidityReceptorCell biologyBiologyImmunology

Abstract

fetched live from OpenAlex

High Resolution Image Download MS PowerPoint Slide Carbohydrate-binding receptors are often used by the innate immune system to potentiate inflammation, target endocytosis/destruction, and adaptive immunity (e.g., CD206, DC-SIGN, MBL, and anticarbohydrate antibodies). To access this class of receptors for cancer immunotherapy, a growing repertoire of bifunctional proximity-inducing therapeutics use high-avidity multivalent carbohydrate binding domains to offset the intrinsically low affinity associated with monomeric carbohydrate–protein binding interactions ( K d ≈ 10 –3 –10 –6 M). For applications aimed at recruiting anticarbohydrate antibodies to tumor cells, large synthetic scaffolds are used that contain both a tumor-binding domain (TBD) and a multivalent antibody-binding domain (ABD) comprising multiple l -rhamnose monosaccharides. This allows for stable bridging between tumor cells and antibodies, which activates tumoricidal immune function. Problematically, such multivalent macromolecules can face limitations including synthetic and/or structural complexity and the potential for off-target immune engagement. We envisioned that small bifunctional “proximity-inducing” molecules containing a low-affinity monovalent ABD could efficiently engage carbohydrate-binding receptors for tumor-immune proximity by coupling weak binding with covalent engagement. Typical covalent drugs and electrophilic chimeras use high-affinity ligands to promote the fast covalent engagement of target proteins (i.e., large k inact / K I ), driven by a favorably small K I for binding. We hypothesized the much less favorable K I associated with carbohydrate–protein binding interactions can be offset by a favorably large k inact for the covalent labeling step. In the current study, we test this hypothesis in the context of a model system that uses rhamnose-specific antibodies to induce tumor-immune proximity and tumoricidal function. We discovered that synthetic chimeric molecules capable of preorganizing an optimal electrophile (i.e., SuFEx vs activated ester) for protein engagement can rapidly covalently engage natural sources of antirhamnose antibody using only a single low-affinity rhamnose monosaccharide ABD. Strikingly, we observe chimeric molecules lacking an electrophile, which can only noncovalently bind the antibody, completely lack tumoricidal function. This is in stark contrast to previous work targeting small molecule hapten and peptide-specific antibodies. Our findings underscore the utility of covalency as a strategy to engage low-affinity carbohydrate-specific proteins for tumor-immune proximity induction.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.395
Threshold uncertainty score0.823

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.044
GPT teacher head0.308
Teacher spread0.264 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it