Antagonistic trends between binding affinity and drug-Likeness in SARS-CoV-2 Mpro inhibitors revealed by machine learning (2025)
- Authors:
- USP affiliated authors: SOUZA, ROBSON FRANCISCO DE - ICB ; CARVALHO, CRISTIANE RODRIGUES GUZZO - ICB ; SOUZA, ANACLETO SILVA DE - ICB ; AMORIM, VITOR MARTINS DE FREITAS - ICB ; SOARES, EDUARDO PEREIRA - ICB
- Unidade: ICB
- DOI: 10.3390/v17070935
- Subjects: MICROBIOLOGIA; ANTIVIRAIS; COVID-19; CORONAVIRUS; INIBIDORES DE ENZIMAS; MEDICAMENTO
- Agências de fomento:
- Language: Inglês
- Imprenta:
- Source:
- Este periódico é de acesso aberto
- Este artigo NÃO é de acesso aberto
-
ABNT
SOUZA, Anacleto Silva de et al. Antagonistic trends between binding affinity and drug-Likeness in SARS-CoV-2 Mpro inhibitors revealed by machine learning. Viruses, v. 17, n. 7. art. 935, p. 25 , 2025Tradução . . Disponível em: https://doi.org/10.3390/v17070935. Acesso em: 13 fev. 2026. -
APA
Souza, A. S. de, Amorim, V. M. de F., Soares, E. P., Guzzo, C. R., & Souza, R. F. de. (2025). Antagonistic trends between binding affinity and drug-Likeness in SARS-CoV-2 Mpro inhibitors revealed by machine learning. Viruses, 17( 7. art. 935), 25 . doi:10.3390/v17070935 -
NLM
Souza AS de, Amorim VM de F, Soares EP, Guzzo CR, Souza RF de. Antagonistic trends between binding affinity and drug-Likeness in SARS-CoV-2 Mpro inhibitors revealed by machine learning [Internet]. Viruses. 2025 ; 17( 7. art. 935): 25 .[citado 2026 fev. 13 ] Available from: https://doi.org/10.3390/v17070935 -
Vancouver
Souza AS de, Amorim VM de F, Soares EP, Guzzo CR, Souza RF de. Antagonistic trends between binding affinity and drug-Likeness in SARS-CoV-2 Mpro inhibitors revealed by machine learning [Internet]. Viruses. 2025 ; 17( 7. art. 935): 25 .[citado 2026 fev. 13 ] Available from: https://doi.org/10.3390/v17070935 - Molecular dynamics simulations of the spike trimeric ectodomain of the SARS-CoV-2 Omicron variant: structural relationships with infectivity, evasion to immune system and transmissibility
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Informações sobre o DOI: 10.3390/v17070935 (Fonte: oaDOI API)
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