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Record W2061068674 · doi:10.2174/1568026043387953

Sulfonamide-Based Acyclic and Conformationally Constrained MMP Inhibitors: From Computer-Assisted Design to Nanomolar Compounds

2004· review· en· W2061068674 on OpenAlexafffund
Stephen Hanessian, Nicolas Moitessier

Bibliographic record

VenueCurrent Topics in Medicinal Chemistry · 2004
Typereview
Languageen
FieldChemistry
TopicSynthesis and Catalytic Reactions
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaServier
KeywordsEnantiopure drugPyrrolidineAziridineSulfonamideChemistryHydroxamic acidCombinatorial chemistryTetrahydrofuranPeptidomimeticDocking (animal)StereochemistryEnantioselective synthesisOrganic chemistryBiochemistryMedicineRing (chemistry)

Abstract

fetched live from OpenAlex

The present account relates to our studies in the computer assisted design and synthesis of acyclic and cyclic MMP inhibitors. Our early efforts focused on the preparation of cyclopropane and tetrahydrofuran-based mimics of batimastat which were not active. The discovery of subnanomolar sulfonamide-based acyclic inhibitors instigated the design of novel target compounds. Thus, with the help of a fully automated and reliable docking program, we embarked on the design and synthesis of enantiopure inhibitors incorporating cyclic scaffolds. This ultimately led to compounds exhibiting inhibitory activities in the nanomolar range. Interestingly, the qualitative ranking prediction was found to be in good agreement with the observed activities.

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: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.002

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 head0.060
GPT teacher head0.322
Teacher spread0.262 · 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

Citations15
Published2004
Admission routes2
Has abstractyes

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