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Record W4234184340 · doi:10.1255/ejms.400

Investigation of the Applicability of a Sequential Digestion Protocol Using Trypsin and Leucine Aminopeptidase M for Protein Identification by Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry

2001· article· en· W4234184340 on OpenAlex
Alan A. Doucette, Liang Li

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEuropean Journal of Mass Spectrometry · 2001
Typearticle
Languageen
FieldChemistry
TopicAdvanced Proteomics Techniques and Applications
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsTrypsinChemistryDigestion (alchemy)ChromatographyPeptideAminopeptidaseBottom-up proteomicsMass spectrometryLeucineMatrix-assisted laser desorption/ionizationPeptide sequenceSample preparationAmino acidSample preparation in mass spectrometryPeptide mass fingerprintingBiochemistryProtein mass spectrometryEnzymeDesorptionElectrospray ionizationProteomicsOrganic chemistry

Abstract

fetched live from OpenAlex

An investigation into the applicability of a sequential digestion procedure involving endo- and exoprotease digestion of proteins is reported. The procedure involves the digestion of a protein sample with trypsin, yielding peptide fragments characteristic of the protein. The resulting mixture of peptide fragments is then subjected to N-terminal sequencing with leucine aminopeptidase M (LAP), with matrix-assisted laser desorption/ionization time-of-flight mass spectrometric analysis of the various digestion products. Several proteins in solution, as well as gel-extracted proteins, were subjected to this sequential enzyme digestion procedure. The results of these experiments reveal that LAP will preferentially cleave specific peptides of the trypsin-digested sample with high efficiency, while leaving other peptides undigested. Also, the length of the amino acid sequence tags that can be generated with this method is limited; the longest sequence tag generated from a single tryptic peptide was four amino acids, even though the digestion was allowed to proceed for long times. In the experiments, N-terminal digestion products were detected as early as two minutes, or as late as 90 minutes, following the addition of LAP to the sample. The method was shown to be effective for sub-picomole starting quantities of protein, although with some loss in digestion efficiency at lower concentrations of starting material. This method is useful in providing additional sequence information to increase the level of confidence in protein identification, as illustrated in the identification of bacterial proteins fractionated by HPLC. In some instances, this method can provide additional sequence information where post-source decay and nanospray mass spectrometry failed to generate fragment-ion spectra. This is illustrated by an example where the procedure was applied to a membrane protein, CD9, that had been isolated by sodium dodecyl sulfate-polyacrylamide gel electrophoresis. Although the sequential digestion procedure requires more human intervention, it is a straightforward method and can be readily implemented.

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.

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 score0.249
Threshold uncertainty score0.670

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.285
Teacher spread0.260 · 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