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Record W2623628426 · doi:10.1021/acs.accounts.7b00114

Azapeptide Synthesis Methods for Expanding Side-Chain Diversity for Biomedical Applications

2017· article· en· W2623628426 on OpenAlexafffund
Ramesh Chingle, Caroline Proulx, William D. Lubell

Bibliographic record

VenueAccounts of Chemical Research · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChemical Synthesis and Analysis
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsChemistryPeptidomimeticPeptide synthesisCombinatorial chemistrySemicarbazideAmino acidPeptideAlkylationStereochemistryOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

Conspectus Mimicry of bioactive conformations is critical for peptide-based medicinal chemistry because such peptidomimetics may augment stability, enhance affinity, and increase specificity. Azapeptides are peptidomimetics in which the α-carbon(s) of one or more amino acid residues are substituted by nitrogen. The resulting semicarbazide analogues have been shown to reinforce β-turn conformation through the combination of lone pair–lone pair repulsion of the adjacent hydrazine nitrogen and urea planarity. Substitution of a semicarbazide for an amino amide residue in a peptide may retain biological activity and add benefits such as improved metabolic stability. The applications of azapeptides include receptor ligands, enzyme inhibitors, prodrugs, probes, and imaging agents. Moreover, azapeptides have proven therapeutic utility. For example, the aza-glycinamide analogue of the luteinizing hormone-releasing hormone analogue Zoladex is a potent long-acting agonist currently used in the clinic for the treatment of prostate and breast cancer. However, the use of azapeptides was hampered by tedious solution-phase synthetic routes for selective hydrazine functionalization. A remarkable stride to overcome this bottleneck was made in 2009 through the introduction of the submonomer procedure for azapeptide synthesis, which enabled addition of diverse side chains onto a common semicarbazone intermediate, providing a means to construct azapeptide libraries by solution- and solid-phase chemistry. In brief, aza residues are introduced into the peptide chain using the submonomer strategy by semicarbazone incorporation, deprotonation, N-alkylation, and orthogonal deprotection. Amino acylation of the resulting semicarbazide and elongation gives the desired azapeptide. Since the initial report, a number of chemical transformations have taken advantage of the orthogonal chemistry of semicarbazone residues (e.g., Michael additions and N-arylations). In addition, libraries have been synthesized from libraries by diversification of aza-propargylglycine (e.g., A 3 coupling reactions, [1,3]-dipolar cycloadditions, and 5-exo-dig cyclizations) and aza-chloroalkylglycine residues. In addition, oxidation of aza-glycine residues has afforded azopeptides that react in pericyclic reactions (e.g., Diels–Alder and Alder–ene chemistry). The bulk of these transformations of aza-glycine residues have been developed by the Lubell laboratory, which has applied such chemistry in the synthesis of ligands with promising biological activity for treating diseases such as cancer and age-related macular degeneration. Azapeptide analogues of growth hormone-releasing peptide-6 (His- d -Trp-Ala-Trp- d -Phe-Lys-NH 2, GHRP-6) have for example been pursued as ligands of the cluster of differentiation 36 receptor (CD36) and show promising activity for the development of treatments for angiogenesis-related diseases, such as age-related macular degeneration, as well as for atherosclerosis. Azapeptides have also been employed to make a series of conformationally constrained second mitochondria-derived activator of caspase (Smac) mimetics that exhibit promising apoptosis-inducing activity in cancer cells. The synthesis of cyclic azapeptide derivatives was used to make an aza scan to study the conformation–activity relationships of the anticancer agent cilengitide, cyclo(RGDf-N(Me)V), and its parent counterpart cyclo(RGDfV), which exhibit potency against human tumor metastasis and tumor-induced angiogenesis. Innovations in the synthesis and application of azapeptides will be presented in this Account, focusing on the creation and use of side-chain diversity in medicinal chemistry.

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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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.091
GPT teacher head0.482
Teacher spread0.391 · 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 designBench or experimental
Domainnot available
GenreMethods

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

Citations110
Published2017
Admission routes2
Has abstractyes

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