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Record W2605108588 · doi:10.3389/fimmu.2017.00351

A Novel Regulator of Activation-Induced Cytidine Deaminase/APOBECs in Immunity and Cancer: Schrödinger’s CATalytic Pocket

2017· review· en· W2605108588 on OpenAlexafffund
Justin J. King, Mani Larijani

Bibliographic record

VenueFrontiers in Immunology · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsMemorial University of Newfoundland
FundersCanadian Institutes of Health Research
KeywordsCytidine deaminaseRegulatorActivation-induced (cytidine) deaminaseMaster regulatorImmunityCatalysisCytidineCancer researchChemistryBiologyImmunologyImmune systemBiochemistryEnzymeGeneAntibodySomatic hypermutation

Abstract

fetched live from OpenAlex

Activation-induced cytidine deaminase (AID) and its relative APOBEC3 cytidine deaminases boost immune response by mutating immune or viral genes. Because of their genome-mutating activities, AID/APOBECs are also drivers of tumorigenesis. Due to highly charged surfaces, extensive non-specific protein-protein/nucleic acid interactions, formation of polydisperse oligomers, and general insolubility, structure elucidation of these proteins by X-ray crystallography and NMR has been challenging. Hence, almost all available AID/APOBEC structures are of mutated and/or truncated versions. In 2015, we reported a functional structure for AID using a combined computational-biochemical approach. In so doing, we described a new regulatory mechanism that is a first for human DNA/RNA-editing enzymes. This mechanism involves dynamic closure of the catalytic pocket. Subsequent X-ray and NMR studies confirmed our discovery by showing that other APOBEC3s also close their catalytic pockets. Here, we highlight catalytic pocket closure as an emerging and important regulatory mechanism of AID/APOBEC3s. We focus on three sub-topics: first, we propose that variable pocket closure rates across AID/APOBEC3s underlie differential activity in immunity and cancer and review supporting evidence. Second, we discuss dynamic pocket closure as an ever-present internal regulator, in contrast to other proposed regulatory mechanisms that involve extrinsic binding partners. Third, we compare the merits of classical approaches of X-ray and NMR, with that of emerging computational-biochemical approaches, for structural elucidation specifically for AID/APOBEC3s.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.050
GPT teacher head0.334
Teacher spread0.284 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations42
Published2017
Admission routes2
Has abstractyes

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