Crystallographic and electrophilic fragment screening of the SARS-CoV-2 main protease
Why is this work in the frame?
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
No Canadian affiliation. An affiliation-only frame — the usual design — would never have seen this work. It is one of the works that make the case for inverting the frame.
Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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.
- Teacher spread
- 0.279 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
Abstract
COVID-19, caused by SARS-CoV-2, lacks effective therapeutics. Additionally, no antiviral drugs or vaccines were developed against the closely related coronavirus, SARS-CoV-1 or MERS-CoV, despite previous zoonotic outbreaks. To identify starting points for such therapeutics, we performed a large-scale screen of electrophile and non-covalent fragments through a combined mass spectrometry and X-ray approach against the SARS-CoV-2 main protease, one of two cysteine viral proteases essential for viral replication. Our crystallographic screen identified 71 hits that span the entire active site, as well as 3 hits at the dimer interface. These structures reveal routes to rapidly develop more potent inhibitors through merging of covalent and non-covalent fragment hits; one series of low-reactivity, tractable covalent fragments were progressed to discover improved binders. These combined hits offer unprecedented structural and reactivity information for on-going structure-based drug design against SARS-CoV-2 main protease.
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.
The record
- Venue
- Nature Communications
- Topic
- Computational Drug Discovery Methods
- Field
- Computer Science
- Canadian institutions
- —
- Funders
- Helen and Martin Kimmel Center for Molecular Design, Weizmann Institute of ScienceNovartis PharmaMedical Research CouncilMinistero dello Sviluppo EconomicoAstex PharmaceuticalsHungarian Science FoundationDiamond Light SourceWellcome TrustEuropean Federation of Pharmaceutical Industries and AssociationsMerck KGaAFundação de Amparo à Pesquisa do Estado de São PauloGenome CanadaPfizerAstraZenecaEli Lilly and CompanyOntario Ministry of Economic Development and InnovationIsrael Science FoundationCancer Research UKIsrael Cancer Research Fund
- Keywords
- ProteaseProteasesSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Covalent bondCoronavirus disease 2019 (COVID-19)ElectrophileChemistryVirologyComputational biologyCoronavirus2019-20 coronavirus outbreakDimerCombinatorial chemistryBiologyEnzymeBiochemistryMedicineOutbreak
- Has abstract in OpenAlex
- yes