The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Computational Design of ACE2-Based Peptide Inhibitors of SARS-CoV-2
Open accessAbstract
Peptide inhibitors against the SARS-CoV-2 coronavirus, currently causing a worldwide pandemic, are designed and simulated. The inhibitors are mostly formed by two sequential self-supporting α-helices (bundle) extracted from the protease domain (PD) of angiotensin-converting enzyme 2 (ACE2), which bind to the SARS-CoV-2 receptor binding domains. Molecular dynamics simulations revealed that the α-helical peptides maintain their secondary structure and provide a highly specific and stable binding (blocking) to SARS-CoV-2. To provide a multivalent binding to the SARS-CoV-2 receptors, many such peptides could be attached to the surfaces of nanoparticle carriers. The proposed peptide inhibitors could provide simple and efficient therapeutics against the COVID-19 disease.
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Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30211-7 · Cited by 21,415
Self-citationScalable molecular dynamics with NAMD
Phillips, J. C., Braun, R., Wang, W., Gumbart, J., Tajkhorshid, E., Villa, E., Chipot, C., Skeel, R. D., Kalé, L., & Schulten, K. (2005) · Journal of Computational Chemistry · doi:10.1002/jcc.20289 · Cited by 16,914
Cryo-EM structure of the 2019-nCoV spike in the prefusion conformation
Wrapp, D., Wang, N., Corbett, K. S., Goldsmith, J. A., Hsieh, C.-L., Abiona, O., Graham, B. S., & McLellan, J. S. (2020) · Science · doi:10.1126/science.abb2507 · Cited by 8,897
Wan, Y., Shang, J., Graham, R., Baric, R. S., & Li, F. (2020) · Journal of Virology · doi:10.1128/jvi.00127-20 · Cited by 4,341 · cited 2×
“8 The angiotensin-converting enzyme 2 (ACE2) is the host cellular receptor with a higher affinity to SARS-CoV-2 than to SARS-CoV. 5 In the recognition of RBD, the protease domain (PD) of ACE2 mainly engages the α 1 -helix with a minor contribution from the α 2 -helix and the linker of the β 3and β 4 -sheets.”
BackgroundStructure, Function, and Evolution of Coronavirus Spike Proteins
Li, F. (2016) · Annual Review of Virology · doi:10.1146/annurev-virology-110615-042301 · Cited by 2,740
Protein Therapeutics: A Summary and Pharmacological Classification
Leader, B., Baca, Q. J., & Golan, D. E. (2008) · Nature Reviews Drug Discovery · doi:10.1038/nrd2399 · Cited by 2,161
Bosch, B. J., van der Zee, R., de Haan, C. A. M., & Rottier, P. J. M. (2003) · Journal of Virology · doi:10.1128/jvi.77.16.8801-8811.2003 · Cited by 1,489
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Toward Nanotechnology-Enabled Approaches against the COVID-19 Pandemic
Weiss, C., Carriere, M., Fusco, L., Capua, I., Regla-Nava, J. A., Pasquali, M., Scott, J. A., Vitale, F., Unal, M. A., Mattevi, C., et al. (2020) · ACS Nano · doi:10.1021/acsnano.0c03697 · Cited by 601
Chen, S., Lin, T., Basu, R., Ritchey, J., Wang, S., Luo, Y., Li, X., Pei, D., Kara, L. B., & Cheng, X. (2024) · Nature Communications · doi:10.1038/s41467-024-45766-2 · Cited by 324
Emerging Technologies for Use in the Study, Diagnosis, and Treatment of Patients with COVID-19
Tsikala Vafea, M., Atalla, E., Georgakas, J., Shehadeh, F., Mylona, E. K., Kalligeros, M., & Mylonakis, E. (2020) · Cellular and Molecular Bioengineering · doi:10.1007/s12195-020-00629-w · Cited by 153
Ching, W.-Y., Adhikari, P., Jawad, B., & Podgornik, R. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms231710091 · Cited by 17
Metadata
- Authors
- Han, Y., & Král, P.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2020-04-14
- Volume
- 14
- Issue
- 4
- Pages
- 5143-5147
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W3015313862
- Cited by
- 381
- References
- 7
- FWCI
- 9.96
- Type
- journal article
- Language
- en
- Open access
- bronze
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