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Record W2964987874 · doi:10.3389/fpls.2019.01058

Molecular Origins of Functional Diversity in Benzylisoquinoline Alkaloid Methyltransferases

2019· review· en· W2964987874 on OpenAlexafffund
Jeremy S. Morris, Peter J. Facchini

Bibliographic record

VenueFrontiers in Plant Science · 2019
Typereview
Languageen
FieldMedicine
TopicBerberine and alkaloids research
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBenzylisoquinolineBiologyEvolutionary biologyFunction (biology)Computational biologyGeneticsBiosynthesisGene

Abstract

fetched live from OpenAlex

O- and N-methylations are ubiquitous and recurring features in the biosynthesis of many specialized metabolites. Accordingly, the methyltransferase (MT) enzymes catalyzing these modifications are directly responsible for a substantial fraction of the vast chemodiversity observed in plants. Enabled by DNA sequencing and synthesizing technologies, recent studies have revealed and experimentally validated the trajectories of molecular evolution through which MTs, such as those biosynthesizing caffeine, emerge and shape plant chemistry. Despite these advances, the evolutionary origins of many other alkaloid MTs are still unclear. Focusing on benzylisoquinoline alkaloid (BIA) producing plants such as opium poppy, we review the functional breadth of BIA N- and O-MT enzymes and their relationship with the chemical diversity of their host species. Drawing on recent structural studies, we discuss newfound insight regarding the molecular determinants of BIA MT function and highlight key hypotheses to be tested. We explore what is known and suspected concerning the evolutionary histories of BIA MTs and show that substantial advances in this domain are within reach. This new knowledge is expected to greatly enhance our conceptual understanding of the evolutionary origins of specialized metabolism.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.975
Threshold uncertainty score0.891

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.087
GPT teacher head0.346
Teacher spread0.259 · 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 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

Citations58
Published2019
Admission routes2
Has abstractyes

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