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Record W2406728760 · doi:10.1007/978-1-61779-520-6_15

A Medicinal Chemistry Perspective on Structure-Based Drug Design and Development

2011· review· en· W2406728760 on OpenAlex
Shawn P. Maddaford

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.

Bibliographic record

VenueMethods in molecular biology · 2011
Typereview
Languageen
FieldChemistry
TopicClick Chemistry and Applications
Canadian institutionsNeurAxon (Canada)
Fundersnot available
KeywordsPerspective (graphical)DrugChemistryNanotechnologyPharmacologyComputer scienceMedicineMaterials scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The application of X-ray crystallography and molecular modeling can provide valuable insight into the optimization of the molecular interactions of a drug-protein complex to achieve potency and selectivity of a drug candidate. For the successful application of SBDD in a drug development program, the impact of these structural modifications required to improve potency and selectivity must be considered in the context of balancing of a multitude of drug properties and other considerations that include solubility, bioavailability, metabolism, distribution, toxicology, chemical stability, and intellectual property space. The utility of structure-based design from the medicinal chemist's perspective is described in this chapter.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.930
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.074
GPT teacher head0.443
Teacher spread0.369 · 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