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Record W3168551641

FlICked ACE2 Mimics Inhibit SARS-CoV-2 Spike Protein-ACE2 Interaction

2021· article· en· W3168551641 on OpenAlexaff
Mihajlo Todorovic, Antonio A. W. L. Wong, Naysilla Dayanara, Taylor Navi, David M. Perrin

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsChemistryMoietyCoronavirus disease 2019 (COVID-19)PeptideBiochemistryCombinatorial chemistryStereochemistryMedicineInfectious disease (medical specialty)
DOInot available

Abstract

fetched live from OpenAlex

SARS-CoV-2 is the viral cause of the most significant global health crisis of our generation, causing over 144 million confirmed cases and 3 million deaths in the year following the declaration of a public health emergency of international concern by the WHO. While the first mRNA vaccines were deployed, the use of stapled peptides to investigate more synthetically accessible inhibitors has sparked rampant interest since as such peptides can have well-defined secondary structures and small molecule-like pharmacokinetic properties. Peptide stapling allows shorter amino acid sequences to mimic the interactions found at the surfaces of protein-protein interactions. In the environment of a rapidly growing field our lab has developed a unique stapling technology we coined Fluorescent Isoindole Crosslinking (FlICk) which employs ortho-phthalaldehyde (OPA) to staple an amine bearing side chain and a thiol bearing side chain in a dehydrative aromatization reaction to yield an isoindole, a chemical moiety which adds value beyond just rigidification through the emergent fluorescence of the staple itself, directly yielding lead molecules which do not have to be further derivatized with fluorophores for use as probes. The reaction conditions are highly benign, operating at room temperature and at ambient conditions close to physiological pH, thus lending themselves naturally to cyclization of unprotected peptides. In the process of developing this chemistry we were able to produce both monocycles and bicycles with biological activity (on melanocortin stimulating hormone and α-amanitin platforms, respectively.) With the emergence of the COVID-19 pandemic in 2020 we were compelled to apply our newly developed technology to what may be the most significant global health crisis of our time. The SARS-CoV-2 virus enters human cells via the interaction of the spike-RBD proteins on its surface with the Angiotensin Converting Enzyme 2 (ACE2) on the host cell surface. The viral protein interacts with the α-helical N-terminal domain of ACE2, a portion of the protein we sought to interrogate with stapled peptide surrogates as such molecules could act as decoys for virus, blocking attachment and thus entry to host cells. We developed an ELISA for testing new lead molecules and set off by examining linear sequences that were direct cut-outs from the ACE2 protein and found that none inhibited the ACE2-Spike interaction at the concentrations tested. We found that while we could smoothly apply our FlICk chemistry to produce stapled helical mimics, such monocyclic compounds were also inactive at the concentrations tested. Thus, we sought to expand the capabilities of FlICk and explore the possibility of introducing a double staple on an unprotected linear sequence and were pleased to find that the resulting double FlICked peptides were our first hits for successfully inhibiting the Spike-ACE2 interaction (at μM concentrations.) We are rapidly developing a pseudovirus neutralization assay (PNA) to validate these initial hits in-vivo while simultaneously pressing lead development in search of better inhibitors. Additionally, we are beginning work on examining the interactions of our ACE2 mimicking stapled peptides with COVID-19 variant spike proteins, which have an even greater affinity for ACE2 than the original viral protein. While this fact has grave implications for public health and has led to their increased transmissivity, it also offers the potential that peptide mimics of ACE2, such as ours, could be more effective treatments against these mutant strains.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.068
GPT teacher head0.378
Teacher spread0.309 · 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
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

Citations0
Published2021
Admission routes1
Has abstractyes

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