Abstract
Background:
The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel pathogen that has triggered a pneumonia outbreak, and despite the measures, the pandemic still continues to occur.Objectives:
The molecular docking analysis was used to test whether the human immunodeficiency virus 1 (HIV-1) protease inhibitory peptides. These marine polypeptides were isolated from the hydrolysate of Pacific oyster.Methods:
Molecular docking process was performed using Molegro Virtual Docker software. The protein data bank file of the crystal structure of COVID-19 main protease in complex with an inhibitor N3 (ID 6LU7) was obtained from the PubChem data source. After preparing protein and removing water and internal ligand, the major cavity was selected for the next step, the docking procedure. Afterward, the MolDock score, Rerank score, Total interaction energy (between energy), and HBond item were calculated. The Remdesivir was used as a positive control in the docking project.Results:
The results of the docking step were evaluated based on several bioinformatics docking scores, including MolDock score, Rerank score, Total interaction energy (between energy), and HBond. The hydrogen bond of remdesivir was -6.03673, and Leu-Leu-Glu-Tyr-Ser-Ileu polypeptide was -6.44185. The Rerank score of remdesivir was -98.9254 and for Leu-Leu-Glu-Tyr-Ser-Ileu polypeptide was -107.821. Of the two screened Pacific oyster polypeptides, the score of Leu-Leu-Glu-Tyr-Ser-Ileu ligand was higher than remdesivir.Conclusions:
This study demonstrated that Pacific oyster compounds may have the potency to be evolved as an anti-COVID-19 main protease drug to fight against the novel coronavirus; however, preclinical and clinical trials are needed for further experimental and/or clinical scientific validation.Keywords
1. Background
Coronaviruses (CoVs) are RNA-viruses that belong to the Coronaviridae family which invade the human respiratory system and cause a variety of respiratory infections (1). Other members of this family include severe acute respiratory syndrome (SARS)-CoV and the Middle East respiratory syndrome (MERS)-CoV, which also can cause major respiratory problems (2). The first case of SARS-CoV-2 was reported on December 12, 2019, in Wuhan, Hubei Province, China. With a death rate of 3.4%, it has claimed about 24 257 989 lives worldwide, until August 28, 2020 (3). The World Health Organization (WHO) is trying to control the pandemic and reduce the mortality rate (4, 5).
Currently, there is no treatment for COVID-19; however, immediate measures are needed. Previous studies were mostly focused on developing novel therapeutics mediators, including antivirals drugs and vaccines (6). Interferon (IFN)-α and ribavirin are among the most important therapeutic mediators that are under investigation (7). Based on the currently available data, the following therapeutic options are proved to be effective against COVID-19 infection: Ritonavir (8), lopinavir (8, 9), either alone or in blend with remdesivir (10, 11), oseltamivir (9), chloroquine (12, 13). Among these drugs, ritonavir, remdesivir, and chloroquine are reported to be more effective in reducing the severity of the symptoms (12); however, further evidence are needed (14).
The SARS-CoV-2 is an enveloped positive-stranded RNA virus with ~30,000 nt RNA genome (15, 16). The coronavirus replicase gene expression involves two overlapping polyproteins, named pp1a and pp1ab (17, 18). These polyproteins are divided into mature non-structural proteins, including the main protease (Mpro) and a papain-like protease, in which all of them perform important functions in viral replication and transcription processes (6, 18).
To control viral gene expression and replication, a highly complex network of proteolytic cascades on the polyproteins is required (19). The main protease of the coronavirus mediates this maturation process (20). The N-terminal of Mpro has an important role in the proteolytic activity, and its C-terminal is necessary for dimerization action (21). It’s also suggested as a therapeutic option for SARS-CoV-2 (6, 20). Generally, some biological active peptides are engaged in the immune system of mammals (22-24) and through eukaryotic cells create protection against pathogens such as viruses, bacteria, and fungi (25). Research on the therapeutic activities of natural peptides dates back to the 1970s (22). Such peptides can be originated from natural sources, such as animals, plants, or microorganisms (26). The structure of peptides determines their therapeutic mechanisms. Peptides can be formulated to mimic the ligands or interact with the conserved domain in the protein surface by various software. The peptide sequence can be manipulated to achieve the highest therapeutic efficiency (27). The efficacy, safety, selectivity, and predictability of peptide drugs should be analyzed by in silico methods and to find the appropriate peptides inter to the in vivo demonstration steps (22).
The Pacific oyster, Crassostrea gigas, is a mollusk that naturally presents in marine environments (28). The hemocytes of this oyster, immunocompetent cells, creates an essential object in innate antimicrobial immunity responses. Also, they can produce antimicrobial peptides (AMPs) and release factors such as lectins and reactive oxygen species (ROS), which there are reports on their in vitro and in Molecular Docking method, deals with the strength, properties and specificity of binding a small molecule as a ligand to a larger molecule that acts as a receptor. These computational methods provide information on the binding activity and affinity of ligands and receptors (29).
2. Objectives
Several studies have investigated the effectiveness of different molecules against the new virus main protease; in this line, the current study intended to screen the inhibitory effect of Pacific oyster, Crassostrea gigas two antimicrobial polypeptides on the SARS-CoV-2 main protease, using computational docking techniques, because these polypeptides have an inhibitory effect on HIV-1 protease in vitro situations (30, 31).
3. Methods
3.1. Receptor and Ligand Preparation
The crystallographic structure of the target receptor, main protease (Mpro) protein of SARS-CoV2 in complex with an inhibitor N3, was retrieved from RCSB Protein Data Bank (PDB ID: 6LU7) (32) (https://www.rcsb.org/). In the docking performance step, the PDB file was imputed to Molegro Virtual Docker (MVD 6 edition, a CLC Bio Company, Denmark) software (33) (Figure 1). The first optimization was performed by adding hydrogen atoms, because most of the macromolecular structure data do not contain hydrogen atoms in their corresponding PDB files. The water molecules were removed to make computations easier and to better clear the binding pocket of possible water molecules that would distort the pose search. Remember is a molecule that can create multiple favorable contacts to the protein, water molecules might confound this procedure (Figure 2). This procedure can remarkably increase the calculations and to evade any expected deformity (34). In the PDF file downloaded from the PDB database (ID: 6Lu7), the main protease (Mpro) of SARS-Cov2 binds to an inhibitor called N3. and should be removed when preparing the protein in the pre-analytical process. Therefore we removed this internal ligand from protein. Next, water molecules were removed, and the protein was prepared through the MVD molecule preparation step. The discovery of functional cavities was then applied to find the excellent docking constraints on the protein structure. Four cavities were found, and the fifth had an extra resemblance to the fourth cavity. We selected two Pacific oyster, Crassostrea gigas antimicrobial polypeptides, including HIV-1PIP-1 (HIV-1 polymerase inhibitory polypeptide 1) and HIV-1PIP-2, with amino acids sequences Leu-Leu-Glu-Tyr-Ser-Leu and Leu-Leu-Glu-Tyr-Ser-Ileu, respectively, were selected from the antivirus lists and according to the literature (35-38). These Pacific oyster polypeptides have been documented to have inhibitory effects on HIV-1 polymerase in vitro. Besides, their antiviral effects have been approved in the previous publications (39-42). Similar to various chemicals used to inhibit SARS-CoV-based on antiviral polymerase compounds, we selected these compounds to dock and compare the results with reference compounds such as remdesivir (43-46). The two dimensional (2D) structure, molecular formula, molecular weight, and source of these ligands were obtained from the National Center for Biotechnology Information as well as Explore chemistry databank system PubChem (https://pubchem.ncbi.nlm.nih.gov/) (Table 1).
A, Visualization using Molegro Virtual Docker hydrophobicity surface and B, secondary structure of the protein (6lu7).
The target cavity (A) which was used to specify the docking constraints, dimensions, and coordinates (B). The coordinates properties are: X = -10.76, Y = 12.64 and Z = 68.81.
The Predicted Poses and Standard Drug (i.e. Remdesivir) Docking Scores
Ligand Name | MolDock Score | Rerank Score | Total Interaction Energy (Between Energy) | Torsions | HBond |
---|---|---|---|---|---|
Remdesivir | -161.419 | -98.9254 | -172.705 | 14 | -6.03673 |
HIV-1PIP-1: Leu-Leu-Glu-Tyr-Ser-Leu | -158.545 | -107.821 | 171.915 | 23 | -6.44185 |
HIV-1PIP-2: Leu-Leu-Glu-Tyr-Ser-Ile | -143.864 | -106.631 | -171.402 | 23 | -3.69101 |
The MVD docking software was used. The main protease structure, along with all selected ligands, were picked out for docking procedures. The selective and best binding site constraints were fixed to comprise the largest detected cavity on the main protease protein structure and, then, its sizes were reduced to achieve the desired simulation treating time and increase the accuracy. Then the best docking cavities of the receptor were found, and an excellent docking grid was prepared, with a radius of 10 (Å) and coordinates of X: -10.76, Y: 12.64 and Z: 68.81. In each ligand, five poses were docked with 10 runs. In the present study, the biggest cavity was selected for the docking process, because in the previous studies this cavity is considered as a major candidate for the docking process and as a major region that ingredients can inhibit this protein for coding a major functional structure.
3.2. Docking Process and Analysis
The docking process of the two selected polypeptide was carried out in comparison to remdesivir, as a comparative standard for molecular docking and MD simulation analysis. Using computational docking techniques, we selected two antimicrobial polypeptides on the SARS-CoV-2 main protease, based on their proven in vitro inhibitory effect on HIV-1 protease.
After docking, the results were imported into the Molegro Molecular Viewer (MMV 2.5 edition, a CLC Bio Company, Denmark) software to visualize the 2D structure of each ligand (47). The best pose of each ligand was selected based on scores of MolDock Score, Rerank Score, total interaction energy (between energy), and HBond items. For the best poses, the 2D diagrams of receptor-ligand interaction, interaction poses, the active site of the virus protease enzyme, protein surface, and Hydrogen Bonds were visualized using Molegro Molecular Viewer. Based on MVD software report, the RMSD score was less than 1.
4. Results
The cavity divination by mathematical tools revealed the presence of four cavities on the Mpro surface with an area of about 10.24 - 126.98 Å. The biggest and wider cavity was selected for docking, as it primarily contained the binding ligand 02J-ALA-VAL-LEU-PJE-010 in the used PDB file. The two selected peptide ligands (Figure 3) were appraised for binding likelihood in the same docking session.
Docking pose visualization
The results of the docking process were evaluated based on several bioinformatics docking scores, including MolDock score, Rerank score, Total interaction energy (between energy), and HBond (Table 1). The best polypeptide ligand was selected based on the MolDock score item ranking. Based on the results, the best ligand was HIV-1PIP-1 with amino acid sequences of Leu-Leu-Glu-Tyr-Ser-Leu, which showed a MolDock score closer to the control drug remdesivir (Table 1). Also, the Rerank score showed that the selected ligand has higher binding power and affinity to its receptor compared to the standard compounds of remdesivir, and this bonding strength can be increased by minor molecular modifications. It worth noting that HIV-1PIP-1 (Leu-Leu-Glu-Tyr-Ser-Leu) ligand was similar to the remdesivir concerning the total interaction energy and hydrogen bound or HBond scores (Figure 3). The graphical visualization showed that hydrogen bonds interact with a protein molecule. In all selected items for docking and standard form, the maximum hydrogen bond interaction between ligand and proteins was related to the HIV-1PIP-1 (Leu-Leu-Glu-Tyr-Ser-Leu) ligand, and All the amino acids that interacted with the ligand in the protein structure were visible. (Asn142, Ser144, Cys145, Glu166, Gln192).
5. Discussion
Developing potent and safe drug candidates against viruses like COVID-19, which has turned into a global crisis, is the main goal for drug development programs. Generally, some biological active peptides originated from natural sources, such as mammal tissues and animal venoms, or those with artificial sources have an important role in the immune system of mammals (22-24). These peptides can be potential candidates for protecting eukaryotic cells against a wide spectrum of pathogens, including viruses (25).
The Pacific oyster produces defensive peptides against environmental pathogens (28). In several studies, the antimicrobial role of these peptides has been investigated in vitro and in silico (48-50). In the present study, the binding affinity of the two selected defense peptides of Pacific oyster to coronavirus main protease was investigated.
As mentioned before, in the present study, we used the MolDock score for interpreting COVID-19 protease interaction with the peptides. Because MolDock is a fast algorithm, virtual screening was performed by using this scoring function. The MolDock is based on a new heuristic search algorithm that causes differential developments with a cavity prediction algorithm (33). In total, four cavities were found in the three-dimensional structure of the protease and the largest one was linked to its ligand in the PDB file. Therefore, it was selected for docking with the designed polypeptide ligands. The docking scoring function of the MolDock is an extension of the piecewise linear potential (PLP), including new hydrogen bonding and electrostatic terms (33, 51-53). To further improve the accuracy of docking, the re-ranking scoring function was used (33, 51, 53). The docking accuracy of the MolDock was evaluated by docking flexible ligands to 77 protein targets. MolDock could identify the correct binding mode in 87% of the complexes (54). Therefore, the findings of this method are highly accurate and interpretable (33, 51, 53). The data obtained through screening suggested that HIV-1PIP-1 (Leu-Leu-Glu-Tyr-Ser-Leu) polypeptide ligand can bind to Mpro with an affinity of -158.545 based on MolDock score and total interaction energy of 171.915. The remdesivir MolDock score was -161.419, and its score was very close to the above-mentioned polypeptide, which is an appropriate score for controlling the entropy. Therefore, in major index in industrial comparing in docking process, but as an interesting result, we showed that hydrogen bond of remdesivir was equal to -6.03673 and in HIV-1PIP-1 (Leu-Leu-Glu-Tyr-Ser-Leu) polypeptide was -6.44185; this is an important item in docking properties which can help us to focus on this polypeptide when using inhibitory roles against Mpro of SARS-CoV2. The hydrogen bonds between remdesivir and Mpro are in Glu166 and Cys145 amino acids, but in HIV-1PIP-1 (Leu-Leu-Glu-Tyr-Ser-Leu) polypeptide and Mpro are in Glu166, Ser144, Cys15, and Asn 142. These scores indicate that our designed potential inhibitor can efficiently bind to the structure of the Mpro (Figure 3), which indicates the best pose of the chemical inhibitor in contact with the Mpro structure and interactions between top poses and Mpro. In this figure, contact residues are determined. Compared to the remdesivir, which its effectiveness in viral protease inhibition function is well-documented, the HIV-1PIP-1 (Leu-Leu-Glu-Tyr-Ser-Leu) ligand has high binding strength to main COVID19 protease Mpro. This binding power was even higher than the control drug in the Rerank score. Also, the total interaction energy of this ligand was close to the control drug. Most importantly, the estimated numbers associated with the hydrogen bonding strength of the peptide designed were greater than those for the control drug, which indicates the probable superiority and effectiveness of this ligand in the protease inhibition. While the rerank-score in MVD provides an estimate of the strength of the interaction; however, it is not calibrated to the chemical units and it does not consider complex contributions (e.g. entropy) (51). Also, the rerank score of remdesivir was low, which indicates that unrolled gestures may a good choice for the docking process and targeting preparing goals. The total interaction energy of our compound are very similar, and this issue revealed that all of pose and ligand interaction energy are suitable to good interaction in the docking process. Ligand torsion number is related to the flexibility of ligand and generally incorporated as a crucial variable in the thermodynamic function of binding free energy, according to this issue, the Leu-Leu-Glu-Tyr-Ser-Leu ligand has higher torsion than remdesivir. Therefore, it can be argued that this substance is more appropriate for the docking process. Therefore, the HIV-1PIP-1 (Leu-Leu-Glu-Tyr-Ser-Leu) ligand can be evaluated as a drug precursor. In general, the HIV-1PIP-1 (Leu-Leu-Glu-Tyr-Ser-Leu) ligand is highly similar to standard drugs and can be considered as an appropriate and effective synthetic option. However, further studies are needed.
5.1. Conclusions
This study demonstrated that the HIV-1PIP-1 (Leu-Leu-Glu-Tyr-Ser-Leu) polypeptide isolated from Pacific oyster, Crassostrea gigas can be a potential inhibitory compound versa Mpro of SARS-CoV2, and it can be used for subsequent laboratory studies.
Acknowledgements
References
-
1.
Mohammadi M, Meskini M, do Nascimento Pinto AL. 2019 Novel coronavirus (COVID-19) overview. Z Gesundh Wiss. 2020:1-9. [PubMed ID: 32313806]. [PubMed Central ID: PMC7167217]. https://doi.org/10.1007/s10389-020-01258-3.
-
2.
Rothan HA, Byrareddy SN. The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak. J Autoimmun. 2020:102433.
-
3.
Coronavirus. 2020. Available from: https://covid19.who.int.
-
4.
Zhou P, Yang XL, Wang XG, Hu B, Zhang L, Zhang W, et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature. 2020;579(7798):270-3. [PubMed ID: 32015507]. [PubMed Central ID: PMC7095418]. https://doi.org/10.1038/s41586-020-2012-7.
-
5.
Ruan Q, Yang K, Wang W, Jiang L, Song J. Clinical predictors of mortality due to COVID-19 based on an analysis of data of 150 patients from Wuhan, China. Intensive Care Med. 2020;46(5):846-8. [PubMed ID: 32125452]. [PubMed Central ID: PMC7080116]. https://doi.org/10.1007/s00134-020-05991-x.
-
6.
Mehta P, McAuley DF, Brown M, Sanchez E, Tattersall RS, Manson JJ, et al. COVID-19: consider cytokine storm syndromes and immunosuppression. Lancet. 2020;395(10229):1033-4. [PubMed ID: 32192578]. [PubMed Central ID: PMC7270045]. https://doi.org/10.1016/S0140-6736(20)30628-0.
-
7.
Zhou Y, Hou Y, Shen J, Huang Y, Martin W, Cheng F. Network-based drug repurposing for novel coronavirus 2019-nCoV/SARS-CoV-2. Cell Discov. 2020;6:14. [PubMed ID: 32194980]. [PubMed Central ID: PMC7073332]. https://doi.org/10.1038/s41421-020-0153-3.
-
8.
Cao B, Wang Y, Wen D, Liu W, Wang J, Fan G, et al. A Trial of Lopinavir-Ritonavir in Adults Hospitalized with Severe Covid-19. N Engl J Med. 2020;382(19):1787-99. [PubMed ID: 32187464]. [PubMed Central ID: PMC7121492]. https://doi.org/10.1056/NEJMoa2001282.
-
9.
Muralidharan N, Sakthivel R, Velmurugan D, Gromiha MM. Computational studies of drug repurposing and synergism of lopinavir, oseltamivir and ritonavir binding with SARS-CoV-2 protease against COVID-19. J Biomol Struct Dyn. 2020:1-6. [PubMed ID: 32248766]. https://doi.org/10.1080/07391102.2020.1752802.
-
10.
Grein J, Ohmagari N, Shin D, Diaz G, Asperges E, Castagna A, et al. Compassionate use of remdesivir for patients with severe Covid-19. N Engl J Med. 2020;382(24):2327-36.
-
11.
Al-Tawfiq JA, Al-Homoud AH, Memish ZA. Remdesivir as a possible therapeutic option for the COVID-19. Travel Med Infect Dis. 2020;34:101615. [PubMed ID: 32145386]. [PubMed Central ID: PMC7129391]. https://doi.org/10.1016/j.tmaid.2020.101615.
-
12.
Geleris J, Sun Y, Platt J, Zucker J, Baldwin M, Hripcsak G, et al. Observational Study of Hydroxychloroquine in Hospitalized Patients with Covid-19. N Engl J Med. 2020;382(25):2411-8. [PubMed ID: 32379955]. [PubMed Central ID: PMC7224609]. https://doi.org/10.1056/NEJMoa2012410.
-
13.
Colson P, Rolain JM, Lagier JC, Brouqui P, Raoult D. Chloroquine and hydroxychloroquine as available weapons to fight COVID-19. Int J Antimicrob Agents. 2020;55(4):105932. [PubMed ID: 32145363]. [PubMed Central ID: PMC7135139]. https://doi.org/10.1016/j.ijantimicag.2020.105932.
-
14.
Robson B. COVID-19 Coronavirus spike protein analysis for synthetic vaccines, a peptidomimetic antagonist, and therapeutic drugs, and analysis of a proposed achilles' heel conserved region to minimize probability of escape mutations and drug resistance. Comput Biol Med. 2020;121:103749. [PubMed ID: 32568687]. [PubMed Central ID: PMC7151553]. https://doi.org/10.1016/j.compbiomed.2020.103749.
-
15.
Xue X, Yu H, Yang H, Xue F, Wu Z, Shen W, et al. Structures of two coronavirus main proteases: implications for substrate binding and antiviral drug design. J Virol. 2008;82(5):2515-27. [PubMed ID: 18094151]. [PubMed Central ID: PMC2258912]. https://doi.org/10.1128/JVI.02114-07.
-
16.
Fehr AR, Perlman S. Coronaviruses: an overview of their replication and pathogenesis. Methods Mol Biol. 2015;1282:1-23. [PubMed ID: 25720466]. [PubMed Central ID: PMC4369385]. https://doi.org/10.1007/978-1-4939-2438-7_1.
-
17.
Brown TDK, Brierley I. The Coronavirus Nonstructural Proteins. The Coronaviridae. Springer; 1995. p. 191-217. https://doi.org/10.1007/978-1-4899-1531-3_10.
-
18.
Snijder EJ, Spaan WJ. The coronaviruslike superfamily. The coronaviridae. Springer; 1995.
-
19.
Gorbalenya AE, Koonin EV, Donchenko AP, Blinov VM. Coronavirus genome: prediction of putative functional domains in the non-structural polyprotein by comparative amino acid sequence analysis. Nucleic Acids Res. 1989;17(12):4847-61. [PubMed ID: 2526320]. [PubMed Central ID: PMC318036]. https://doi.org/10.1093/nar/17.12.4847.
-
20.
Xue X, Yang H, Shen W, Zhao Q, Li J, Yang K, et al. Production of authentic SARS-CoV M(pro) with enhanced activity: application as a novel tag-cleavage endopeptidase for protein overproduction. J Mol Biol. 2007;366(3):965-75. [PubMed ID: 17189639]. [PubMed Central ID: PMC7094453]. https://doi.org/10.1016/j.jmb.2006.11.073.
-
21.
Yang H, Yang M, Ding Y, Liu Y, Lou Z, Zhou Z, et al. The crystal structures of severe acute respiratory syndrome virus main protease and its complex with an inhibitor. Proc Natl Acad Sci U S A. 2003;100(23):13190-5. [PubMed ID: 14585926]. [PubMed Central ID: PMC263746]. https://doi.org/10.1073/pnas.1835675100.
-
22.
Skalickova S, Heger Z, Krejcova L, Pekarik V, Bastl K, Janda J, et al. Perspective of Use of Antiviral Peptides against Influenza Virus. Viruses. 2015;7(10):5428-42. [PubMed ID: 26492266]. [PubMed Central ID: PMC4632391]. https://doi.org/10.3390/v7102883.
-
23.
Wiesner J, Vilcinskas A. Antimicrobial peptides: the ancient arm of the human immune system. Virulence. 2010;1(5):440-64. [PubMed ID: 21178486]. https://doi.org/10.4161/viru.1.5.12983.
-
24.
Mandal SM, Silva ON, Franco OL. Recombinant probiotics with antimicrobial peptides: a dual strategy to improve immune response in immunocompromised patients. Drug Discov Today. 2014;19(8):1045-50. [PubMed ID: 24881782]. https://doi.org/10.1016/j.drudis.2014.05.019.
-
25.
Silva RR, Avelino KY, Ribeiro KL, Franco OL, Oliveira MD, Andrade CA. Optical and dielectric sensors based on antimicrobial peptides for microorganism diagnosis. Front Microbiol. 2014;5:443. [PubMed ID: 25191319]. [PubMed Central ID: PMC4138613]. https://doi.org/10.3389/fmicb.2014.00443.
-
26.
Vilas Boas LCP, Campos ML, Berlanda RLA, de Carvalho Neves N, Franco OL. Antiviral peptides as promising therapeutic drugs. Cell Mol Life Sci. 2019;76(18):3525-42. [PubMed ID: 31101936]. [PubMed Central ID: PMC7079787]. https://doi.org/10.1007/s00018-019-03138-w.
-
27.
Fosgerau K, Hoffmann T. Peptide therapeutics: current status and future directions. Drug Discov Today. 2015;20(1):122-8. [PubMed ID: 25450771]. https://doi.org/10.1016/j.drudis.2014.10.003.
-
28.
Schmitt P, Gueguen Y, Desmarais E, Bachere E, de Lorgeril J. Molecular diversity of antimicrobial effectors in the oyster Crassostrea gigas. BMC Evol Biol. 2010;10:23. [PubMed ID: 20100329]. [PubMed Central ID: PMC2823732]. https://doi.org/10.1186/1471-2148-10-23.
-
29.
Parvez MK, Tabish Rehman M, Alam P, Al-Dosari MS, Alqasoumi SI, Alajmi MF. Plant-derived antiviral drugs as novel hepatitis B virus inhibitors: Cell culture and molecular docking study. Saudi Pharm J. 2019;27(3):389-400. [PubMed ID: 30976183]. [PubMed Central ID: PMC6439212]. https://doi.org/10.1016/j.jsps.2018.12.008.
-
30.
Denaro M, Smeriglio A, Barreca D, De Francesco C, Occhiuto C, Milano G, et al. Antiviral activity of plants and their isolated bioactive compounds: An update. Phytother Res. 2020;34(4):742-68. [PubMed ID: 31858645]. https://doi.org/10.1002/ptr.6575.
-
31.
Lee TG, Maruyama S. Isolation of HIV-1 protease-inhibiting peptides from thermolysin hydrolysate of oyster proteins. Biochem Biophys Res Commun. 1998;253(3):604-8. [PubMed ID: 9918775]. https://doi.org/10.1006/bbrc.1998.9824.
-
32.
Jin Z, Du X, Xu Y, Deng Y, Liu M, Zhao Y, et al. Structure of M(pro) from SARS-CoV-2 and discovery of its inhibitors. Nature. 2020;582(7811):289-93. [PubMed ID: 32272481]. https://doi.org/10.1038/s41586-020-2223-y.
-
33.
Thomsen R, Christensen MH. MolDock: a new technique for high-accuracy molecular docking. J Med Chem. 2006;49(11):3315-21. [PubMed ID: 16722650]. https://doi.org/10.1021/jm051197e.
-
34.
Wong SE, Lightstone FC. Accounting for water molecules in drug design. Expert Opin Drug Discov. 2011;6(1):65-74. [PubMed ID: 22646827]. https://doi.org/10.1517/17460441.2011.534452.
-
35.
Witvrouw M, De Clercq E. Sulfated polysaccharides extracted from sea algae as potential antiviral drugs. Gen Pharmacol. 1997;29(4):497-511. [PubMed ID: 9352294]. https://doi.org/10.1016/s0306-3623(96)00563-0.
-
36.
Schaeffer DJ, Krylov VS. Anti-HIV activity of extracts and compounds from algae and cyanobacteria. Ecotoxicol Environ Saf. 2000;45(3):208-27. [PubMed ID: 10702339]. https://doi.org/10.1006/eesa.1999.1862.
-
37.
Luescher-Mattli M. Algae, A Possible Source for New Drugs in the Treatment of HIV and Other Viral Diseases. Curr Med Chem Anti Infect Agents. 2003;2(3):219-25. https://doi.org/10.2174/1568012033483051.
-
38.
El Gamal AA. Biological importance of marine algae. Saudi Pharm J. 2010;18(1):1-25. [PubMed ID: 23960716]. [PubMed Central ID: PMC3731014]. https://doi.org/10.1016/j.jsps.2009.12.001.
-
39.
Wijesekara I, Pangestuti R, Kim SK. Biological activities and potential health benefits of sulfated polysaccharides derived from marine algae. Carbohydr Polym. 2011;84(1):14-21. https://doi.org/10.1016/j.carbpol.2010.10.062.
-
40.
Santoyo S, Jaime L, Plaza M, Herrero M, Rodriguez-Meizoso I, Ibañez E, et al. Antiviral compounds obtained from microalgae commonly used as carotenoid sources. J Appl Phycol. 2011;24(4):731-41. https://doi.org/10.1007/s10811-011-9692-1.
-
41.
Ahmadi A, Zorofchian Moghadamtousi S, Abubakar S, Zandi K. Antiviral Potential of Algae Polysaccharides Isolated from Marine Sources: A Review. Biomed Res Int. 2015;2015:825203. [PubMed ID: 26484353]. [PubMed Central ID: PMC4592888]. https://doi.org/10.1155/2015/825203.
-
42.
Falaise C, Francois C, Travers MA, Morga B, Haure J, Tremblay R, et al. Antimicrobial Compounds from Eukaryotic Microalgae against Human Pathogens and Diseases in Aquaculture. Mar Drugs. 2016;14(9). [PubMed ID: 27598176]. [PubMed Central ID: PMC5039530]. https://doi.org/10.3390/md14090159.
-
43.
Zhao C, Yang C, Liu B, Lin L, Sarker SD, Nahar L, et al. Bioactive compounds from marine macroalgae and their hypoglycemic benefits. Trends Food Sci Technol. 2018;72:1-12. https://doi.org/10.1016/j.tifs.2017.12.001.
-
44.
Mahomoodally MF, Lobine D, Rengasamy KR, Gowrishankar S, Tewari D, Zengin G, et al. Marine Algae: A Potential Resource of Anti-HSV Molecules. Processes. 2019;7(12). https://doi.org/10.3390/pr7120887.
-
45.
Besednova NN, Zvyagintseva TN, Kuznetsova TA, Makarenkova ID, Smolina TP, Fedyanina LN, et al. Marine Algae Metabolites as Promising Therapeutics for the Prevention and Treatment of HIV/AIDS. Metabolites. 2019;9(5). [PubMed ID: 31052506]. [PubMed Central ID: PMC6572556]. https://doi.org/10.3390/metabo9050087.
-
46.
Shen K, Yang Y, Wang T, Zhao D, Jiang Y, Jin R, et al. Diagnosis, treatment, and prevention of 2019 novel coronavirus infection in children: experts' consensus statement. World J Pediatr. 2020;16(3):223-31. [PubMed ID: 32034659]. [PubMed Central ID: PMC7090771]. https://doi.org/10.1007/s12519-020-00343-7.
-
47.
Viewer MM. Version 2.5. Molegro ApS. 2012.
-
48.
Zasloff M. Antimicrobial peptides of multicellular organisms. Nature. 2002;415(6870):389-95. [PubMed ID: 11807545]. https://doi.org/10.1038/415389a.
-
49.
Ganz T. Defensins: antimicrobial peptides of innate immunity. Nat Rev Immunol. 2003;3(9):710-20. [PubMed ID: 12949495]. https://doi.org/10.1038/nri1180.
-
50.
Mahlapuu M, Hakansson J, Ringstad L, Bjorn C. Antimicrobial Peptides: An Emerging Category of Therapeutic Agents. Front Cell Infect Microbiol. 2016;6:194. [PubMed ID: 28083516]. [PubMed Central ID: PMC5186781]. https://doi.org/10.3389/fcimb.2016.00194.
-
51.
Bitencourt-Ferreira G, de Azevedo WJ. Molegro Virtual Docker for Docking. Methods Mol Biol. 2019;2053:149-67. [PubMed ID: 31452104]. https://doi.org/10.1007/978-1-4939-9752-7_10.
-
52.
Chaudhary KK, Mishra N. A review on molecular docking: novel tool for drug discovery. Databases. 2016;3(4).
-
53.
Meng XY, Zhang HX, Mezei M, Cui M. Molecular docking: a powerful approach for structure-based drug discovery. Curr Comput Aided Drug Des. 2011;7(2):146-57. [PubMed ID: 21534921]. [PubMed Central ID: PMC3151162]. https://doi.org/10.2174/157340911795677602.
-
54.
Torktaz I, Mohamadhashem F, Esmaeili A, Behjati M, Sharifzadeh S. Virtual screening and pharmacophore design for a novel theoretical inhibitor of macrophage stimulating factor as a metastatic agent. Bioimpacts. 2013;3(3):141-4. [PubMed ID: 24163807]. [PubMed Central ID: PMC3786797]. https://doi.org/10.5681/bi.2013.026.