A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Unraveling viral drug targets : a deep learning-based approach for the identification of potential binding sites (2024)
Popov, P., Kalinin, R., Buslaev, P., Kozlovskii, I., Zaretckii, M., Karlov, D., Gabibov, A., & Stepanov, A. (2024). Unraveling viral drug targets : a deep learning-based approach for the identification of potential binding sites. Briefings in Bioinformatics, 25(1), Article bbad459. https://doi.org/10.1093/bib/bbad459
JYU-tekijät tai -toimittajat
Julkaisun tiedot
Julkaisun kaikki tekijät tai toimittajat: Popov, Petr; Kalinin, Roman; Buslaev, Pavel; Kozlovskii, Igor; Zaretckii, Mark; Karlov, Dmitry; Gabibov, Alexander; Stepanov, Alexey
Lehti tai sarja: Briefings in Bioinformatics
ISSN: 1467-5463
eISSN: 1477-4054
Julkaisuvuosi: 2024
Ilmestymispäivä: 18.12.2023
Volyymi: 25
Lehden numero: 1
Artikkelinumero: bbad459
Kustantaja: Oxford University Press (OUP)
Julkaisumaa: Britannia
Julkaisun kieli: englanti
DOI: https://doi.org/10.1093/bib/bbad459
Julkaisun avoin saatavuus: Avoimesti saatavilla
Julkaisukanavan avoin saatavuus: Kokonaan avoin julkaisukanava
Julkaisu on rinnakkaistallennettu (JYX): https://jyx.jyu.fi/handle/123456789/93901
Tiivistelmä
The coronavirus disease 2019 (COVID-19) pandemic has spurred a wide range of approaches to control and combat the disease. However, selecting an effective antiviral drug target remains a time-consuming challenge. Computational methods offer a promising solution by efficiently reducing the number of candidates. In this study, we propose a structure- and deep learning-based approach that identifies vulnerable regions in viral proteins corresponding to drug binding sites. Our approach takes into account the protein dynamics, accessibility and mutability of the binding site and the putative mechanism of action of the drug. We applied this technique to validate drug targeting toward severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) spike glycoprotein S. Our findings reveal a conformation- and oligomer-specific glycan-free binding site proximal to the receptor binding domain. This site comprises topologically important amino acid residues. Molecular dynamics simulations of Spike in complex with candidate drug molecules bound to the potential binding sites indicate an equilibrium shifted toward the inactive conformation compared with drug-free simulations. Small molecules targeting this binding site have the potential to prevent the closed-to-open conformational transition of Spike, thereby allosterically inhibiting its interaction with human angiotensin-converting enzyme 2 receptor. Using a pseudotyped virus-based assay with a SARS-CoV-2 neutralizing antibody, we identified a set of hit compounds that exhibited inhibition at micromolar concentrations.
YSO-asiasanat: koronavirukset; SARS-CoV-2-virus; lääkkeet; lääkehoito; proteiinit
Vapaat asiasanat: cryptic binding sites learning; SARS-CoV-2; Spike glycoprotein S
Liittyvät organisaatiot
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OKM-raportointi: Kyllä
VIRTA-lähetysvuosi: 2024
Alustava JUFO-taso: 2