The identification of potential inhibitors of SARS-CoV-2 spike protein by virtual screening FDA-approved compound library
Abstract
1. Introduction
T
Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory
syndrome coronavirus (SARS-COV-2), has become the deadliest respiratory disease
after it was first detected in December 2019 in Wuhan, China[1].
Because SARS-COV-2 can be transmitted by aerosols, close contact, respiratory
droplets, and faecal-oral routes, it greatly affects
the global economy, society, healthcare, energy, and environment[2-8].
As of 15 September 2023, there are approximately 690 million confirmed cases
globally, and more than 6.9 million deaths have occurred. Typically, patients
will experience fever, cough, muscle aches, sore throat and diarrhoea,
while severe patients may experience respiratory failure and organ failure[9-11]. The severity of COVID-19 infection is
influenced by the virulence of the SARS-COV-2 variant and the host's immune
response. The National Institutes of Health (NIH) has established a disease
classification system for the degree of COVID-19 infection, with criteria for
asymptomatic, mild, moderate, severe, and critical. These categories are not
mutually exclusive, and patients often progress from one category to the other
over the course of their illness[9]. SARS-CoV-2
encodes four structural proteins: synapsid (S), envelope (E), membrane (M), and
nucleocapsid (N)[12]. The N protein is responsible for binding to the viral
RNA, while the S, E, and M proteins form the envelope[13].
The new coronavirus infects host cells by S protein binding to the
angiotensin-converting enzyme 2 (ACE2) receptor of human cells[14,15].
Thus, the S protein becomes the most promising target for developing drug and
vaccine against SARS-CoV-2.
At
present, in order to curb the battle against COVID-19,
many researchers at home and abroad are actively researching and developing
effective medicines and vaccines. However, the long period, high cost, adverse
reactions and after-effects of the disease have made the research and
development process difficult [16,17]. It is advantageous to use already
marketed drugs to find potentially active compounds against neocoronaviruses.
Computer-aided drug design (CADD) is a technology that uses computational
methods to discover and develop drugs and active molecules with phase-specific
properties. The one of main contributor to CADD is virtual screening (VS) based
on molecular docking [18]. CADD has greatly facilitated drug development in
recent years, not only providing an accelerated pathway to find potential
compounds, but also saving time, money and labour
during the experimental process [19-21].
In
the study, FDA-approved compound library is performed to screen potentially
active compounds based on the S protein of SARS-CoV-2.
2. Materials and methods
2.1 Structure preparation of ligands
3480
FDA-approved compounds from ZINC database were used to screen potential
molecules [22]. Small molecules were prepared using Schrodinger’s LigPrep module of the Schrödinger program [23], which
includes transforming the three-dimensional structure of small molecule,
preserving the original chirality of small molecule, adding hydrogen Chronic Diseases Prevention Review , and
minimization of the structure.
2.2 Structure preparation of the S protein
The
crystal structure of SARS-CoV-2 S protein was downloaded from the Protein Data
Bank (PDB ID: 6M17). The S protein was treated using the Protein Preparation
Wizard module, including the addition of missing side chains and loops,
assigning protonation states and adding hydrogen Chronic Diseases Prevention Review . The OPLS-2005 force
field was selected to minimize the protein.
2.3 Grid generation
The
receptor grids of the S protein were defined by key residues including Tyr449,
Gly496, Gln498, Pro499, Thr500, Asn501, Gly502, Val503, and Tyr505 (Figure 1).
The grids were then generated using the Receptor Grid Generation module.
Fig. (1). Crystal
structure of the spike protein of SARS-CoV-2, and the key residues defining
receptor grids of the protein.
2.4 Molecular docking-based virtual screening
Virtual
screening of the S protein was carried out using virtual screening workflow.
The compounds were without reactive functional groups and obeyed Lipinski's
Rule of 5. After that, the obtained compounds were performed to further
evaluate their binding affinity between the S protein and molecules by using
Glide (high throughput virtual screening, HTVS), (standard precision, SP), and
(extra precision, XP).
2.5 Cluster analysis
The
filtered compounds were clustered into 5 classes by Canvas. Finally, combining
the results of docking scoring, and clustering analysis, some candidate
compounds were selected for further structural analysis.
3. Results and discussion
3.1 Molecular docking of remdesivir
Remdesivir
is an antiviral drug authorized to treat mild-to-moderate COVID-19[24].
Therefore, the molecular docking result of remdesivir and S protein was chosen
as a reference and the docking scores was -5.725 kcal/mol. Remdesivir has the
hydrophobic interactions with Leu45, Val445, and Val503 of S protein (Figure
2a). Additionally, remdesivir forms the hydrogen bonds with Asn49 and Asn330 of
S protein (Figure 2b).
Fig. (2).
Interaction mode of remdesivir with the S protein (a-b). The surface ranging
from orange−red
for the most hydrophobic to dodger blue for the most polar residues, with white
in between.
Fig. (3). Cluster
analysis of compounds screened from FDA-approved compound library.
3.2 Screening of FDA-approved compound library
Table
1. The docking scores of candidate compounds binding with the S protein.
|
Chemical
structures |
Compounds |
Docking scores |
|
|
primaquine |
-8.910 |
|
|
Midodrine |
-7.761 |
|
|
Phenylephrine |
-6.739 |
|
|
Suprofen |
-6.524 |
107
compounds were finally obtained using HTVS, SP and XP, and performed cluster
analysis (Figure 3). These compounds were classified into 5 categories and
representative compounds were selected by combining docking scores and the
interactions. Most of the compounds obtained were concentrated in class 3, with
very few compounds in other classes. Therefore, several compounds with high
docking scores in class 3 were selected to further analysis (Table 1).
The
compounds with docking scores ≤ −6.5
kcal/mol are primaquine[25], midodrine, phenylephrine,
and suprofen. Primaquine has the most favorable
docking score, which is a potent antimalaria agent. The side chain of
primaquine with Glu35, Asp38, and Gly496 formes
hydrogen bonds (Figure 4). In addition, primaquine is involved in cation-π interactions with Lys353. These
interactions contribute to the antiviral activity of primaquine.The important and main findings of the
study should come first in the Results Section. The tables, figures and references
should be given in sequence to emphasize the important information or
observations related to the research. The repetition of data in tables and
figures should be avoided. Results should be precise.
Fig.
(4). Interaction mode of primaquine with the S protein (a-b).
4. Conclusion
Based
on the S protein of SARS-CoV-2, primaquine is identified by virtual screening
of FDA-approved compound library, which has more favorable docking scores than
remdesivir. Primaquine formes hydrogen bonds with
Glu35, Asp38, and Gly496 and cation-π interactions with Lys353, which
contribute to the antiviral activity of primaquine. The study provides a
valuable basis for the development of anti-novel coronavirus drugs.
ACKNOWLEDGEMENTS
This
work was financially supported by the Innovation and Entrepreneurship Training
Program for College Students, Guizhou University of Traditional Chinese
Medicine ([2020]22), Science and Technology Planning Project of Guizhou
Province [QKHF-ZK(2021)G539], Science and Technology
Planning Project of Guizhou Province [QKHF-ZK(2023)G426].
CONFLICT OF INTEREST
The
authors declare no conflict of interest.
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Share and Cite
Ren Z. J., Zeng D.R., Wang P. Q., Wang R., Zhou B. Q., Zhang Y. The identification of potential inhibitors of SARS-CoV-2 spike protein by virtual screening FDA-approved compound library. Chronic Diseases Prevention Review 2024, 8 (29), 1. DOI: 10.54762/CDPR2024.29.1-4.
Ren Z. J., Zeng D.R., Wang P. Q., Wang R., Zhou B. Q., Zhang Y. (2024). The identification of potential inhibitors of SARS-CoV-2 spike protein by virtual screening FDA-approved compound library. Chronic Diseases Prevention Review, 8(29), 1. https://doi.org/10.54762/CDPR2024.29.1-4
Chicago/Turabian StyleRen Z. J., Zeng D.R., Wang P. Q., Wang R., Zhou B. Q., Zhang Y. 2024. "The identification of potential inhibitors of SARS-CoV-2 spike protein by virtual screening FDA-approved compound library." Chronic Diseases Prevention Review 8 (29):1. doi: 10.54762/CDPR2024.29.1-4.