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Record W4281888381 · doi:10.1002/anie.202206866

Property‐Driven Development of Passively Permeable Macrocyclic Scaffolds Using Heterocycles**

2022· article· en· W4281888381 on OpenAlexafffund
George J. Saunders, Andrei K. Yudin

Bibliographic record

VenueAngewandte Chemie International Edition · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical Synthesis and Analysis
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLipophilicityChemistryAmino acidMolecular dynamicsCombinatorial chemistryMembrane permeabilityMembraneMoleculeStereochemistryOrganic chemistryComputational chemistryBiochemistry

Abstract

fetched live from OpenAlex

Passive membrane permeability is a fundamental challenge in the development of bioactive macrocycles. To achieve this objective, chemists have resorted to various strategies, the most common of which is deployment of N-methylated amino acids and/or D-amino acids. Here we investigate the effect of heterocyclic grafts on the passive membrane permeability of macrocycles and report the structural consequences of iterative amino acid replacement by azole rings. Through stepwise substitution of amino acid residues for heterocycles, we show that lipophilicity and PAMPA permeability of a macrocycle can be vastly improved. Overall, changes in permeability do not scale linearly as more heterocycles are incorporated, underscoring the subtleties of conformation-property relationships in this class of molecule. NMR analysis and molecular dynamics simulations provide insights into the structural consequences of the added heterocycles and these frameworks can now be applied as macrocyclic scaffolds for drug discovery.

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 score0.049
Threshold uncertainty score0.513

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 head0.019
GPT teacher head0.256
Teacher spread0.236 · 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

Citations25
Published2022
Admission routes2
Has abstractyes

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