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Record W2073041565 · doi:10.3892/ijmm.13.4.557

Lipidic inhibitors of human N-myristoyltransferase

2004· article· en· W2073041565 on OpenAlexaff
Mohammed Khysar Pasha, Ponniah Selvakumar, Ashakumary Lakshmikuttyamma, Mabood Qureshi, Frank S. Guziec, Jonathan R. Dimmock, Ronald L. Felsted, Constance J. Glover, Rajendra K. Sharma

Bibliographic record

VenueInternational Journal of Molecular Medicine · 2004
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMyristoylationMyristic acidEnzymeBiochemistryAcyltransferasesKinasePeptideProtein kinase AStereochemistryChemistryAntiparasiticSubstrate (aquarium)BiologyFatty acidPalmitic acidPhosphorylationBiosynthesis

Abstract

fetched live from OpenAlex

This study was undertaken in order to identify compounds which inhibit the activity of human myristoyl-CoA:protein N-myristoyltransferase (hNMT). In particular, the structural features of such molecules which contribute to enzyme inhibition were investigated. Two groups of compounds, namely myristic acid and analogs 1-13 and derivatives of myristoyl-CoA 14-19 were evaluated. All compounds were examined using cAMP-dependent protein kinase derived peptide substrate. The IC(50) values were <1 micro M, between 1 and 100 micro M or >100 micro M in eight, four and seven compounds, respectively. Of the six myristoyl-CoA analogs, five had IC(50) values in the 0.06-0.59 micro M range. These molecules were examined using three additional substrates viz pp60src, MARCKS and M2 gene segment of reovirus type 3 which led to results similar to those obtained with the cAMP-dependent protein kinase substrate. On the other hand, evaluation of myristic acid and four related compounds revealed some differences in hNMT-inhibiting properties among the substrates. From the results obtained, the possible manner whereby potent inhibitors interact with the enzyme was formulated thus enabling the design of further analogs as candidate inhibitors of hNMT.

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)0.000
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 score0.089
Threshold uncertainty score0.327

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.011
GPT teacher head0.306
Teacher spread0.294 · 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

Citations9
Published2004
Admission routes1
Has abstractyes

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