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Record W4404028049 · doi:10.1101/2024.11.04.621849

Using phage display for rational engineering of a higher affinity humanized 3’phosphohistidine-specific antibody

2024· preprint· en· W4404028049 on OpenAlexaff
Gregory D. Martyn, Rajasree Kalagiri, Gianluca Veggiani, Robyn L. Stanfield, Indrani Choudhuri, Margaux Sala, Jill Meisenhelder, Chao Chen, Avik Biswas, Ronald M. Levy, Dmitry Lyumkis, Ian A. Wilson, Tony Hunter, Sachdev S. Sidhu

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldMedicine
TopicMonoclonal and Polyclonal Antibodies Research
Canadian institutionsUniversity of Waterloo
FundersSLAC National Accelerator LaboratoryBiological and Environmental ResearchArgonne National LaboratoryBasic Energy SciencesNational Institute of General Medical SciencesNational Institutes of HealthNational Cancer InstituteOffice of ScienceU.S. Department of Energy
KeywordsPhage displayRational designAntibodyComputational biologyChemistryBiologyImmunologyGenetics

Abstract

fetched live from OpenAlex

Abstract Histidine phosphorylation (pHis) is a non-canonical post-translational modification (PTM) that is historically understudied due to a lack of robust reagents that are required for its investigation, such as high affinity pHis-specific antibodies. Engineering pHis-specific antibodies is very challenging due to the labile nature of the phosphoramidate (P-N) bond and the stringent requirements for selective recognition of the two isoforms, 1-phosphohistidine (1-pHis) and 3-phosphohistidine (3-pHis). Here, we present a strategy for in vitro engineering of antibodies for detection of native 3-pHis targets. Specifically, we humanized the rabbit SC44-8 anti-3-pTza (a stable 3-pHis mimetic) mAb into a scaffold (herein referred to as hSC44) that was suitable for phage display. We then constructed six unique Fab phage-displayed libraries using the hSC44 scaffold and selected high affinity 3-pHis binders. Our selection strategy was carefully designed to enrich antibodies that bound 3-pHis with high affinity and had specificity for 3-pHis versus 3-pTza. hSC44.20N32F L , the best engineered antibody, has an ∼10-fold higher affinity for 3-pHis than the parental hSC44. Eleven new Fab structures, including the first reported antibody-pHis peptide structures were solved by X-ray crystallography. Structural and quantum mechanical calculations provided molecular insights into 3-pHis and 3-pTza discrimination by different hSC44 variants and their affinity increase obtained through in vitro engineering. Furthermore, we demonstrate the utility of these newly developed high-affinity 3-pHis-specific antibodies for recognition of pHis proteins in mammalian cells by immunoblotting and immunofluorescence staining. Overall, our work describes a general method for engineering PTM-specific antibodies and provides a set of novel antibodies for further investigations of the role of 3-pHis in cell biology. Significance Statement Histidine phosphorylation is an elusive PTM whose role in mammalian cell biology is largely unknown due to the lack of robust tools and methods for its analysis. Here we report the development of antibodies with unprecedented affinity and specificity towards 3-pHis and present the first crystal structures of a pHis peptide in complex with an antibody. Finally, we show how these antibodies can be used in standard molecular biology workflows to investigate pHis-dependent biology.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.045
GPT teacher head0.315
Teacher spread0.270 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2024
Admission routes1
Has abstractyes

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