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Record W2964927637 · doi:10.1038/s41598-019-47600-y

A Novel Cell-Penetrating Antibody Fragment Inhibits the DNA Repair Protein RAD51

2019· article· en· W2964927637 on OpenAlexafffund
Landon Pastushok, Yongpeng Fu, Leo S. Lin, Yu Luo, John F. DeCoteau, Ken Lee, C. Ronald Geyer

Bibliographic record

VenueScientific Reports · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Interference and Gene Delivery
Canadian institutionsiProgen Biotech (Canada)Saskatchewan Cancer AgencyUniversity of Saskatchewan
FundersWestern Economic Diversification CanadaGovernment of Canada
KeywordsRAD51DNAHomologous recombinationDNA damageMolecular biologyDNA repairAntibodyCancer cellCellIntracellularBiologyCell biologyChemistryBiochemistryCancerGenetics

Abstract

fetched live from OpenAlex

Abstract DNA damaging chemotherapies are successful in cancer therapy, however, the damage can be reversed by DNA repair mechanisms that may be up-regulated in cancer cells. We hypothesized that inhibiting RAD51, a protein involved in homologous recombination DNA repair, would block DNA repair and restore the effectiveness of DNA damaging chemotherapy. We used phage-display to generate a novel synthetic antibody fragment that bound human RAD51 with high affinity (K D = 8.1 nM) and inhibited RAD51 ssDNA binding in vitro . As RAD51 is an intracellular target, we created a corresponding intrabody fragment that caused a strong growth inhibitory phenotype on human cells in culture. We then used a novel cell-penetrating peptide “iPTD” fusion to generate a therapeutically relevant antibody fragment that effectively entered living cells and enhanced the cell-killing effect of a DNA alkylating agent. The iPTD may be similarly useful as a cell-penetrating peptide for other antibody fragments and open the door to numerous intracellular targets previously off-limits in living cells.

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 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)0.001
metaresearch head score (Gemma)0.000
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 score0.034
Threshold uncertainty score0.462

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.000
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 head0.009
GPT teacher head0.239
Teacher spread0.231 · 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 teacher head, 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

Citations21
Published2019
Admission routes2
Has abstractyes

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