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. 2021 Oct 7:12:749256.
doi: 10.3389/fgene.2021.749256. eCollection 2021.

Screening Potential Drugs for COVID-19 Based on Bound Nuclear Norm Regularization

Juanjuan Wang  1 , Chang Wang  1 , Ling Shen  1 , Liqian Zhou  1 , Lihong Peng  1   2
Affiliations

Screening Potential Drugs for COVID-19 Based on Bound Nuclear Norm Regularization

Juanjuan Wang et al. Front Genet. .

Abstract

The novel coronavirus pneumonia COVID-19 infected by SARS-CoV-2 has attracted worldwide attention. It is urgent to find effective therapeutic strategies for stopping COVID-19. In this study, a Bounded Nuclear Norm Regularization (BNNR) method is developed to predict anti-SARS-CoV-2 drug candidates. First, three virus-drug association datasets are compiled. Second, a heterogeneous virus-drug network is constructed. Third, complete genomic sequences and Gaussian association profiles are integrated to compute virus similarities; chemical structures and Gaussian association profiles are integrated to calculate drug similarities. Fourth, a BNNR model based on kernel similarity (VDA-GBNNR) is proposed to predict possible anti-SARS-CoV-2 drugs. VDA-GBNNR is compared with four existing advanced methods under fivefold cross-validation. The results show that VDA-GBNNR computes better AUCs of 0.8965, 0.8562, and 0.8803 on the three datasets, respectively. There are 6 anti-SARS-CoV-2 drugs overlapping in any two datasets, that is, remdesivir, favipiravir, ribavirin, mycophenolic acid, niclosamide, and mizoribine. Molecular dockings are conducted for the 6 small molecules and the junction of SARS-CoV-2 spike protein and human angiotensin-converting enzyme 2. In particular, niclosamide and mizoribine show higher binding energy of -8.06 and -7.06 kcal/mol with the junction, respectively. G496 and K353 may be potential key residues between anti-SARS-CoV-2 drugs and the interface junction. We hope that the predicted results can contribute to the treatment of COVID-19.

Keywords: FDA-approved drugs; SARS-CoV-2; bounded nuclear norm regularization; molecular docking; virus-drug association.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. The handling editor declared a past co-authorship with one of the author LZ.

Figures

FIGURE 1
FIGURE 1
Overall flow chart of VDA-GBNNR.
FIGURE 2
FIGURE 2
The AUC values of five VDA prediction models on three datasets. (A) The AUC values of five VDA prediction models on dataset 1. (B) The AUC values of five VDA prediction models on dataset 2. (C) The AUC values of five VDA prediction models on dataset 3.
FIGURE 3
FIGURE 3
Performance comparison between VDA-BNNR and VDA-GBNNR on three datasets. (A) Performance comparison between VDA-BNNR and VDA-GBNNR on dataset 1. (B) Performance comparison between VDA-BNNR and VDA-GBNNR on dataset 2. (C) Performance comparison between VDA-BNNR and VDA-GBNNR on dataset 3.
FIGURE 4
FIGURE 4
Molecular docking between the predicted six anti-SARS-CoV-2 drugs and the domain of the S protein bound to ACE2.
See this image and copyright information in PMC

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References

    1. Ahmed F. (2020). A network-based analysis reveals the mechanism underlying vitamin d in suppressing cytokine storm and virus in SARS-CoV-2 infection. Front. Immunol. 11:590459. 10.3389/fimmu.2020.590459 - DOI - PMC - PubMed
    1. Alakus T. B., Turkoglu I. (2021). A novel protein mapping method for predicting the protein interactions in COVID-19 disease by deep learning. Interdiscip. Sci. 13 44–60. 10.1007/s12539-020-00405-4 - DOI - PMC - PubMed
    1. Amirian E. S., Levy J. K. (2020). Current knowledge about the antivirals remdesivir (GS-5734) and GS-441524 as therapeutic options for coronaviruses. One Health 9:100128. 10.1016/j.onehlt.2020.100128 - DOI - PMC - PubMed
    1. Burley S. K., Berman H. M., Kleywegt G. J., Markley J. L., Nakamura H., Velankar S. (2017). Protein data bank (PDB): the single global macromolecular structure archive. Methods Mol. Biol. 1607 627–641. 10.1007/978-1-4939-7000-1_26 - DOI - PMC - PubMed
    1. Cai Q., Yang M., Liu D., Chen J., Shu D., Xia J., et al. (2020). Experimental treatment with favipiravir for COVID-19: an open-label control study. Engineering (Beijing) 6 1192–1198. 10.1016/j.eng.2020.03.007 - DOI - PMC - PubMed