An automatic pipeline for the design of irreversible derivatives identifies a potent SARS-CoV-2 Mpro inhibitor.
Cell Chem Biol
; 28(12): 1795-1806.e5, 2021 12 16.
Article
em En
| MEDLINE
| ID: mdl-34174194
ABSTRACT
Designing covalent inhibitors is increasingly important, although it remains challenging. Here, we present covalentizer, a computational pipeline for identifying irreversible inhibitors based on structures of targets with non-covalent binders. Through covalent docking of tailored focused libraries, we identify candidates that can bind covalently to a nearby cysteine while preserving the interactions of the original molecule. We found â¼11,000 cysteines proximal to a ligand across 8,386 complexes in the PDB. Of these, the protocol identified 1,553 structures with covalent predictions. In a prospective evaluation, five out of nine predicted covalent kinase inhibitors showed half-maximal inhibitory concentration (IC50) values between 155 nM and 4.5 µM. Application against an existing SARS-CoV Mpro reversible inhibitor led to an acrylamide inhibitor series with low micromolar IC50 values against SARS-CoV-2 Mpro. The docking was validated by 12 co-crystal structures. Together these examples hint at the vast number of covalent inhibitors accessible through our protocol.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Desenho de Fármacos
/
Proteínas da Matriz Viral
/
Inibidores de Proteínas Quinases
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SARS-CoV-2
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Revista:
Cell Chem Biol
Ano de publicação:
2021
Tipo de documento:
Article