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Record W4246037517 · doi:10.32920/ryerson.14647701.v1

Towards the synthesis of photobactin: methodology and metal binding aspects

2021· preprint· en· W4246037517 on OpenAlexaff
Michelle Shuoprasad

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Production and Characterization
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsAmideLigand (biochemistry)Combinatorial chemistryHeteronuclear single quantum coherence spectroscopyChemistryChelationReagentMetalProton NMRStereochemistryNuclear magnetic resonance spectroscopyOrganic chemistryReceptor

Abstract

fetched live from OpenAlex

Siderophores are metal-typically iron-chelating compounds that have received countless attention in research, as they can play a role in medicine intended for drug delivery and iron overload treatment. The synthesis of Photobactin has been of interest as it has been previously isolated (<10 mg) from Photorhabdus luminescence and has not once been synthesized. This thesis examined the preparation of Photobactin using a multi-step approach: synthesizing two building blocks individually and coupling them together with an amide coupling reagent. Both building blocks were synthesized successfully. However, the deprotection of the ester group on one of the building blocks has been uncooperative, and therefore the total synthesis of Photobactin was not achieved. Moreover, DFT computation calculations were performed to study Photobactin binding properties with Fe3+. According to the results, iron (Fe3+) is likely to form a hexadentate (6-coordinate ligand) or a tetradentate (4-coordinate ligand) complex with Photobactin. Each of the compounds leading to Photobactin was characterized using 1H and 13C-NMR. Some compounds were characterized using elemental analysis and performing 2D-NMR (COSY, HMBC, and HSQC) to make final assignments.

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)0.000
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 score0.005
Threshold uncertainty score0.422

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.001
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 head0.058
GPT teacher head0.297
Teacher spread0.239 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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