Abstract
The newly emerged human coronavirus, SARS-CoV-2, had begun to spread last year and sparked worldwide. In this study, molecular docking is utilized to test some previously approved drugs against the SARS-CoV-2 nonstructural protein 15 (Nsp15). We screened 23 drugs, from which three (saquinavir, valrubicin and aprepitant) show a paramount predicted binding affinity (-9.1, -9.6 and -9.2 kcal/mol, respectively) against SARS-CoV-2 Nsp15. Moreover, saquinavir and aprepitant make nonbonded interactions with Leu201 in the active site cavity of Nsp15, while the drug valrubicin interacts with Arg199 and Leu201. This binding pattern may be effective against the targeted protein, leading to Nsp15 blockage and virus abolition. Additionally, the pharmacological properties of the screened drugs are known since they have been approved against different viruses.
Keywords: : COVID-19, endoribonuclease, molecular docking, Nsp15, SARS-CoV-2
Graphical abstract

In December 2019, a novel coronavirus, SARS-CoV-2, sparked in Wuhan, China, and became a pandemic in March 2020 [1]. Almost 142 million people are infected, with more than 3 million reported deaths. The common symptoms of this disease include cough, fever, shortness of breath, fatigue, loss of taste and muscle and abdominal pain. The timeframe from exposure to the appearance of symptoms can generally be around 5 days but may range from 2 to 14 days [2,3].
The whole RNA genome of SARS-CoV-2 is 28–32 kb long. It encodes; four structural proteins (spike [S], matrix [M], envelope [E] and nucleocapsid [N]), open reading frame (ORF), nonstructural polyprotein and five accessory proteins (ORF3a, ORF6, ORF7, ORF8, ORF9) required for the function and assembly of SARS-CoV-2 [4–6]. The replicase gene of this virus encodes two ORFs and is translated into pp1a and pp1ab. The viral proteases (papain-like protease and 3C-like protease) are processed from these polypeptides [6,7]. It helps to hide viral RNA from host defense (RNA degradation) [8]. Additionally, the nonstructural protein 15 (Nsp15) has endoribonuclease activity and reported interfering with IFN-β production and associated with retinoblastoma tumor suppressor protein in coronaviruses [9–11]. Nsp15 has endoribonuclease activity as it cleaves RNA at the 3′ of uridylates, followed by the formation of 2′-3′ cyclic products, just like the RNase A activity [12]. Targeting such essential viral protein could interfere with the SARS-CoV-2 life cycle [13].
Several bioactive compounds (phytochemicals) were previously tested in silico against Nsp15 of SARS-CoV-2, including asparoside-C, asparoside-F, asparoside-D, rutin and racemoside-A [14]. These compounds have predicted binding affinities greater than -7.17 kcal/mol. On the other hand, glyasperin A, isoliquiritinapioside, among other phytochemicals from Glycyrrhiza glabra, show lower (better) predicted binding affinities (down to -9.2 kcal/mol) against SARS-CoV-2 Nsp15 [15]. The safety profiles of these phytochemical-based compounds are missing, while other studies tested two US FDA-approved drugs (of known safety profiles) against the SARS-CoV-2 Nsp15, namely glisoxepide and idarubicin [16]. These two drugs show stronger binding against Nsp15 compared with the physiological uridine triphosphate [16].
We are trying in the current study to test different groups of successfully approved drugs, in other viruses, against SARS-CoV-2 Nsp15. A conventional antipsychotic drug, perphenazine, works by decreasing abnormal excitement in the brain. It is frequently used in the US to treat schizophrenia to control severe nausea and vomiting in adults [17]. On the other hand, ribavirin is a synthetic guanosine nucleoside used for its broad-spectrum activity against several RNA and DNA viruses [18]. Remdesivir is a promising antiviral drug against various RNA viruses, including the Ebola virus, SARS-CoV and Middle East respiratory syndrome (MERS) coronavirus [19–21]. At the same time, it was recently approved by the FDA for the treatment of the Ebola virus and SARS-CoV-2 (emergency use only approval) [22,23]. Additionally, epirubicin is used in chemotherapy as an active antineoplastic agent against malignancies such as breast cancer, lymphoma, lung cancer, ovarian, liver cancers and sarcomas [24].
Moreover, amprenavir, lopinavir, fosamprenavir, atazanavir, saquinavir, indinavir and tipranavir are HIV protease inhibitors. Among these drugs, amprenavir has received marketing approval from the FDA, while fosamprenavir (nucleoside reverse transcriptase inhibitors) has been approved in more than 40 countries. In contrast, nelfinavir has been used since the mid-90s against HIV [25–29]. Moreover, vapreotida has anticancer activity and is being used in photothermal therapy [30]. Bepotastine has been approved in Japan as a second-generation antihistamine for the treatment of allergic rhinitis [31]. Recently, lopinavir, along with ritonavir, has already been used as a trial at Jin Yin-Tan Hospital (Wuhan, China) to give comfort to hospitalized adult patients affected severely with COVID-19 [32,33]. Moreover, galidesivir has broad-spectrum antiviral activity against many RNA virus families like bunyaviruses, arenaviruses, paramyxoviruses, coronaviruses, flaviviruses and phleboviruses [34].
In this study, chemically active and structurally diverse drugs are selected and tested for their possible inhibitory effect against SARS-CoV-2 Nsp15 using molecular modeling. The in silico methods such as molecular docking and dynamics simulations are successful in finding viable solutions for emerging infections [35–40]. Computational methods help reduce the time, effort and money in finding a solution in the drug design, especially with such pandemic infectious diseases [41,42].
Materials & methods
Ligands & protein preparations
The chemical compounds are downloaded from the PubChem database [43] as a structure data file format then subjected to geometry optimization. The Merck molecular force field 94 is employed through the steepest gradient descent algorithm with 2000 minimization steps [44,45]. Twenty-three previously approved drugs are selected based on their potential inhibitory activity against different viruses (see Supplementary Table 1). They include anti-HIV, anti-SARS-CoV, anti-MERS coronavirus, anti-HCV, anti-Ebola virus and other approved medicines. On the other hand, the x-ray diffraction solved structure of SARS-CoV-2 Nsp15 endoribonuclease (Protein Data Bank [PDB] ID: 6W01) was downloaded from the PDB database (1.9 Å resolution) [46]. The water molecules and heteroatoms are removed using Discovery Studio software [47]. Finally, the protein structure was minimized in the Swiss PDB Viewer software [48] with the help of the GROMOS 43B1 force field [49].
Molecular docking
The molecular docking study is employed to test and predict the possible binding pattern of the drugs against SARS-CoV-2 Nsp15 endoribonuclease. The docking method is validated through docking the citrate compound into the Nsp15 structure (redocking) PDB ID: 6W01 chain A. Supplementary Figure 1 shows how the docked citrate molecule coincides with the citrate found in the solved structure. Additionally, the docking score (-5.1 kcal/mol) was in agreement with previous work [50]. After that, both the protein and the ligand files were converted into PDBQT format, the acceptable file format in AutoDock Vina (Scripps Research, CA, USA), after the addition of any missed hydrogen atoms and charges (Kollman and Gasteiger) utilizing AutoDock Tools software [51,52]. The center of the grid box was set at (-54.9, 51.0, 24.0 Å), while the box dimensions were set to be large enough to cover the entire protein active site region (62.3 × 72.0 × 59.7 Å3). This box covers the entire Nsp15 active site residues (HIS235, HIS250, LYS290, SER294, THR341 and TYR343) to check for the possible binding sites with the tested ligands [10]. Finally, the drug protein–ligand complexes are screened based on the calculated binding energies and subjected to analysis using Discovery Studio (Dassault Systèmes, Vélizy-Villacoublay, France). At the same time, PyMOL (Schrödinger, Inc., NY, USA) was utilized as additional software to visualize the complexes [53].
Results
Molecular docking was performed using AutoDock Vina software to test and rank the 23 candidate drugs against SARS-CoV-2 Nsp15. As shown in Figure 1A, the binding affinities range from -5.5 kcal/mol (nelfinavir) down to -9.6 kcal/mol (valrubicin). The drugs ranked by its binding affinity against SARS-CoV-2 Nsp15 are: valrubicin, aprepitant, saquinavir, favipiravir, indinavir, vapreotida, remdesivir, ribavirin, fosamprenavir, ritonavir, icatibant, lopinavir, perphenazine, epirubicin, bepotastine, caspofungin, amprenavir, colistin, atazanavir, galidesivir, tipranavir, darunavir and nelfinavir. The drugs valrubicin, aprepitant and saquinair show excellent binding affinities to SARS-CoV-2 Nsp15 (-9.1, -9.6 and -9.2 kcal/mol, respectively) as shown in Figure 1A. The 2D structures of the best three compounds are shown in Figure 1B.
Figure 1. Molecular docking of the compounds to the nonstructural protein 15.

Molecular docking (A) The binding affinities (in kcal/mol) calculated for the selected drugs against SARS-CoV-2 nonstructural protein 15 using AutoDock Vina software. (B) The 2D structures of the best three compounds (valrubicin, aprepitant and saquinavir), based on the binding affinity.
By analyzing the docking complexes, saquinavir formed two hydrogen bonds with Lys90 and Asp268 of the SARS-CoV-2 Nsp15. Additionally, one π-sigma bond with Leu201, one π-π-T shaped with Phe259, one Alkyl with Lys277 and two π-alkyl (Leu252 and Leu266) are established in the saquinavir-SARS-CoV-2 Nsp15 complex (Figure 2). On the other hand, valrubicin shows more nonbonded interaction with the endoribonuclease compared with saquinavir (Figure 2). The valrubicin-SARS-CoV-2 Nsp15 complex shows eight hydrogen bonds (Thr167, Ser198, Arg199, Leu201, Gln202, Glu203, Arg207 and Thr275), two π-alkyl bonds (Leu252 and Val295) and one alkyl bond (Leu266). Interestingly, three more halogen bonds are also formed (Thr167, Gln197 and Ser198) for this complex, which was absent for the saquinavir-SARS-CoV-2 Nsp15 complex.
Figure 2. Post-docking analysis.

The 3D structures (left) and the 2D interaction scheme (right) of the complexes formed upon docking the drugs to SARS-CoV-2 nonstructural protein 15. (A) Saquinavir. (B) Valrubicin. (C) Aprepitant. A variety of bonded patterns, including hydrogen (green), halogen bond (cyan), alkyl (pink), π-alkyl (violet), and π-π-T-shaped (red) bonds are depicted as dashed colored lines on the three complexes. The amino acids are colored according to the interaction involved.
Table 1 lists the formed interactions established upon docking the best three drugs (saquinavir, valrubicin and aprepitant) into SARS-CoV-2 Nsp15 active site. Additionally, the bond distances are listed between the brackets to indicate the bond strength.
Table 1. Interactions established upon docking the drugs saquinair, valrubicin and aprepitant into the active site of SARS-CoV-2 nonstructural protein 15.
| Drug name | PubChem CID | Hydrogen bond (distance Å) | Hydrophobic interaction (distance Å) | Halogen (distance Å) |
|---|---|---|---|---|
| Saquinavir | 441243 | Asp268 (2.20) Lys90 (2.74) |
π-sigma Leu201 (2.66) π-π-T-shaped Phe259 (5.47) Alkyl Lys277 (4.16) π-alkyl Leu252 (5.39) Leu266 (5.31) |
- |
| Valrubicin | 454216 | Glu203 (2.59) Thr167 (2.25) Leu201 (2.37) Arg207 (2.21) Gln202 (2.86) Thr275 (2.85) Ser198 (2.77) Arg199 (2.66) |
Alkyl Leu266 (4.68) π-alkyl Leu252 (5.28) Val295 (5.38) |
Thr167 (3.17) Gln197 (3.52) Ser198 (3.05) |
| Aprepitant | 135413536 | Leu266 (1.92) Asp297 (2.86) Asp268 (2.90) Lys90 (2.77) Ser198 (2.40) |
Alkyl Leu201 (3.94) Leu252 (4.76) Lys277 (4.75) Val 295 (4.60) |
Asp273 (3.69) Val295 (3.12) Ile296 (3.93) |
Docked complexes are analyzed using Discovery Studio and also by PyMOL software.
Discussion
Molecular docking has become the most widely used approach and has substantial success stories during pandemics [54,55]. Docking, combined with other computational methods, may play an essential role in determining drug–protein relationships and their binding pattern [56,57].
It was reported that the π-alkyl bonds contribute well to better binding, which is responsible for the more stable and more durable binding in biological systems [58,59]. Since valrubicin and saquinavir both contribute several π-alkyl interactions with Nsp15, it may play a crucial role in improved affinity compared with other drugs. Similarly, the aprepitant-SARS-CoV-2 Nsp15 complex is stabilized by five hydrogen bonds (Lys90, Ser198, Leu266, Asp268 and Asp297) and four alkyl bonds (Leu201, Leu252, Lys277 and Val295). Like valrubicin, aprepitant also forms halogen contacts with Nsp15 but at different positions (Asp273, Val295 and Ile296). These halogen bonds contribute to the binding affinity with the macromolecular systems [60]. The screened drugs, valrubicin and aprepitant, provide more hydrogen bonds with SARS-CoV-2 Nsp15, where this bonding pattern impacts the overall complex stability and molecular recognition of the system [61].
Some of the interacting residues in Figure 2 are surface accessible (gray shadowed circles) that reflect its surface exposed property. These residues are LEU266 in the three drugs, LYS90 and ASP268 in saquinavir and aprepitant and LEU201 in saquinavir and valrubicin. Valrubicin has more surface accessible residues such as S198, ARG199, GLN202 and GLU203. These residues lie near the active site cavity of the Nsp15 (HIS235, HIS250, LYS290, SER294, THR341 and TYR343)
To be considered a possible drug candidate, the drug molecules have to maintain specific parameters, although violations can sometimes be present [62]. The tested drugs are already approved and hence its toxicity and their ADMET properties are known. Additionally, the drug saquinavir has been reported as a potential SARS-CoV-2 RdRp main protease (Mpro) inhibitor [63]. It was tested through docking to the dimeric Mpro and then molecular dynamics simulation followed by molecular mechanics/generalized Born surface area calculations [64]. Saquinavir was the best among 12 FDA-approved drugs in the study and was suggested as a potential SARS-CoV-2 Mpro inhibitor [63].
In summary, the three approved drugs, saquinavir, valrubicin and aprepitant, may be potential candidates that can bind to SARS-CoV-2 Nsp15 protein effectively with excellent in silico binding affinity values. Moreover, the binding of these three drug molecules in the active sites of Nsp15 may contradict viral infection. However, further in-depth simulation studies (dynamics) and experimental validation is suggested as future work. Additionally, optimization of these drugs may help in finding a better cure against SARS-CoV-2.
Conclusion
The WHO declared COVID-19 as a pandemic in March 2020. This study tested the binding affinity and mode of 23 clinically trialed, approved (FDA) drugs to repurpose it against SARS-CoV-2 Nsp15. Valrubicin, saquinavir and aprepitant showed promising results in binding the viral protein Nsp15, among other drugs. Besides, saquinavir was suggested as a potential inhibitor of SARS-CoV-2 Mpro as well in a previous study. So, it can be a double-target medicine that could inhibit SARS-CoV-2 infectivity. This needs more in-depth simulation work and experimental validation studies before the clinical trials. Moreover, the efficacy and reactivity of the drugs could be improved by modifying them to fit the SARS-CoV-2 Nsp15 active site pocket precisely.
Executive summary.
US FDA-approved drugs can target SARS-CoV-2 nonstructural protein 15 (Nsp15).
Molecular docking reveals that valrubicin, aprepitant and saquinavir are strongly associated with Nsp15 of SARS-CoV-2.
Both H-bonds and halogen bonds are the driving force for the binding in the case of valrubicin and aprepitant, while few hydrophobic contacts are present.
Saquinavir forms mainly hydrophobic contacts with Nsp15 and could be a double blocker targeting both Nsp15 and Mpro of SARS-CoV-2.
Supplementary Material
Author contributions
S Mahmud and A Amin conceived and designed research. S Mahmud and E Rahman conducted experiments. UK Acharjee, AA Elfiky and A Saleh contributed to the analysis. S Mahmud, AA Elfiky and A Amin wrote the manuscript. All authors read and approved the manuscript, and all data were generated in-house and no paper mill was used.
Financial & competing interests disclosure
The authors have no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties. The authors declare that there is no competing interest.
No writing assistance was utilized in the production of this manuscript.
Ethical conduct of research
All the study is computational and no ethical approval is needed.
Supplementary data
To view the supplementary data that accompany this paper please visit the journal website at: www.future-science.com/doi/suppl/10.2217/fvl-2020-0233
References
- 1.Wu F, Zhao S, Yu B et al. A new coronavirus associated with human respiratory disease in China. Nature 579(7798), 265–269 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Hui DS, IA E, Madani TA et al. The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health - the latest 2019 novel coronavirus outbreak in Wuhan, China. Int. J. Inf. Dis. 91, 264–266 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Cherry G, Rocke J, Chu M et al. Loss of smell and taste: a new marker of COVID-19? Tracking reduced sense of smell during the coronavirus pandemic using search trends. Expert Rev. Anti. Infect. Ther. 18(11), 1165–1170 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Lu R, Zhao X, Li J et al. Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding. Lancet 395(10224), 565–574 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Xu X, Chen P, Wang J et al. Evolution of the novel coronavirus from the ongoing Wuhan outbreak and modeling of its spike protein for risk of human transmission. Sci. China Life Sci. 63(3), 457–460 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Cui J, Li F, Shi ZL. Origin and evolution of pathogenic coronaviruses. Nat. Rev. Microbiol. 17(3), 181–192 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Ortega JT, Serrano ML, Pujol FH, Rangel HR. Unrevealing sequence and structural features of novel coronavirus using in silico approaches: the main protease as molecular target. EXCLI J. 19, 400–409 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Baez-Santos YM, St John SE, Mesecar AD. The SARS-coronavirus papain-like protease: structure, function and inhibition by designed antiviral compounds. Antiviral Res. 115, 21–38 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Liu X, Fang P, Fang L et al. Porcine deltacoronavirus nsp15 antagonizes interferon-beta production independently of its endoribonuclease activity. Mol. Immunol. 114, 100–107 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Kim Y, Jedrzejczak R, Maltseva NI et al. Crystal structure of Nsp15 endoribonuclease NendoU from SARS-CoV-2. Protein Sci. 29(7), 1596–1605 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Bhardwaj K, Liu P, Leibowitz JL, Kao CC. The coronavirus endoribonuclease Nsp15 interacts with retinoblastoma tumor suppressor protein. J. Virol. 86(8), 4294–4304 (2012). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Bhardwaj K, Sun J, Holzenburg A, Guarino LA, Kao CC. RNA recognition and cleavage by the SARS coronavirus endoribonuclease. J. Mol. Biol. 361(2), 243–256 (2006). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Sharma J, Kumar Bhardwaj V, Singh R, Rajendran V, Purohit R, Kumar S. An in-silico evaluation of different bioactive molecules of tea for their inhibition potency against non structural protein-15 of SARS-CoV-2. Food Chem. 346, 128933 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Chikhale RV, Sinha SK, Patil RB et al. In-silico investigation of phytochemicals from Asparagus racemosus as plausible antiviral agent in COVID-19. J. Biomol. Struct. Dyn. 1–15 (2020) (Epub ahead of print). [DOI] [PubMed] [Google Scholar]
- 15.Sinha SK, Prasad SK, Islam MA et al. Identification of bioactive compounds from Glycyrrhiza glabra as possible inhibitor of SARS-CoV-2 spike glycoprotein and non-structural protein-15: a pharmacoinformatics study. J. Biomol. Struct. Dyn. 1–15 (2020) (Epub ahead of print). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Chandra A, Gurjar V, Qamar I, Singh N. Identification of potential inhibitors of SARS-COV-2 endoribonuclease (EndoU) from FDA approved drugs: a drug repurposing approach to find therapeutics for COVID-19. J. Biomol. Struct. Dyn. 1–11 (2020) (Epub ahead of print). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Rosenheck RA, Leslie DL, Sindelar J et al. Cost–effectiveness of second-generation antipsychotics and perphenazine in a randomized trial of treatment for chronic schizophrenia. Am. J. Psychiatry 163(12), 2080–2089 (2006). [DOI] [PubMed] [Google Scholar]
- 18.Glue P. Glue P. The clinical pharmacology of ribavirin. Semin Liver Dis. 19(Suppl 1), 17–24 (1999). [PubMed] [Google Scholar]
- 19.Elfiky AA, Azzam EB, Shafaa MW. The anti-HCV, sofosbuvir, versus the anti-EBOV remdesivir against SARS-CoV-2 RNA dependent RNA polymerase in silico. Mol. Divers (2021) (Epub ahead of print). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Elfiky AA. Ribavirin, Remdesivir, Sofosbuvir, Galidesivir, and Tenofovir against SARS-CoV-2 RNA dependent RNA polymerase (RdRp): a molecular docking study. Life Sci. 253, 117592 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Elfiky AA, Azzam EB. Novel guanosine derivatives against MERS CoV polymerase: an in silico perspective. J. Biomol. Struct. Dyn. 39(8), 2923–2931 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Mulangu S, Dodd LE, Davey RT Jr et al. A randomized, controlled trial of Ebola virus disease therapeutics. N. Engl. J. Med. 381(24), 2293–2303 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Sheahan TP, Sims AC, Graham RL et al. Broad-spectrum antiviral GS-5734 inhibits both epidemic and zoonotic coronaviruses. Sci. Transl. Med. 9(396), eaal3653 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Yang F, Lei Q, Li L et al. Delivery of epirubicin via slow infusion as a strategy to mitigate chemotherapy-induced cardiotoxicity. PLoS ONE 12(11), e0188025 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Fung HB, Kirschenbaum HL, Hameed R. Amprenavir: a new human immunodeficiency virus type 1 protease inhibitor. Clin. Ther. 22(5), 549–572 (2000). [DOI] [PubMed] [Google Scholar]
- 26.Chandwani A, Shuter J. Lopinavir/ritonavir in the treatment of HIV-1 infection: a review. Ther. Clin. Risk Manag. 4(5), 1023–1033 (2008). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Fukuda A, Nagao T, Kitaichi T, Koga I, Kobayashi A, Miura T. Safety analysis of Lexiva tablets 700 (fosamprenavir calcium hydrate) in post-marketing surveillance in Japan. Curr. Med. Res. Opin. 36(3), 455–464 (2020). [DOI] [PubMed] [Google Scholar]
- 28.Swainston Harrison T, Scott LJ. Atazanavir: a review of its use in the management of HIV infection. Drugs 65(16), 2309–2336 (2005). [DOI] [PubMed] [Google Scholar]
- 29.Doyon L, Tremblay S, Bourgon L, Wardrop E, Cordingley MG. Selection and characterization of HIV-1 showing reduced susceptibility to the non-peptidic protease inhibitor tipranavir. Antiviral Res. 68(1), 27–35 (2005). [DOI] [PubMed] [Google Scholar]
- 30.Zhu R, Li Y, Zhang X et al. Vapreotide-mediated hierarchical mineralized Ag/Au nanoshells for photothermal anti-tumor therapy. Nanotechnology 30(5), 055602 (2019). [DOI] [PubMed] [Google Scholar]
- 31.Takahashi H, Ishida-Yamamoto A, Iizuka H. Effects of bepotastine, cetirizine, fexofenadine, and olopatadine on histamine-induced wheal-and flare-response, sedation, and psychomotor performance. Clin. Exp. Dermatol. 29(5), 526–532 (2004). [DOI] [PubMed] [Google Scholar]
- 32.Cao B, Wang Y, Wen D et al. A trial of lopinavir-ritonavir in adults hospitalized with severe Covid-19. N. Engl. J. Med. 382(19), 1787–1799 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Du YX, Chen XP. Favipiravir: pharmacokinetics and concerns about clinical trials for 2019-nCoV infection. Clin. Pharmacol. Ther. 108(2), 242–247 (2020). [DOI] [PubMed] [Google Scholar]
- 34.Warren TK, Wells J, Panchal RG et al. Protection against filovirus diseases by a novel broad-spectrum nucleoside analogue BCX4430. Nature 508(7496), 402–405 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Elfiky AA. Novel guanosine derivatives against Zika virus polymerase in silico. J. Med. Virol. 92(1), 11–16 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Elfiky AA. The antiviral sofosbuvir against mucormycosis: an in silico perspective. Future Virol. 14(11), 739–744 (2019). [Google Scholar]
- 37.Elfiky AA, Ibrahim IM. Host-cell recognition through GRP78 is enhanced in the new UK variant of SARS-CoV-2, in silico. J. Infect. 82(5), 186–230 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Elfiky AA, Ismail A. Molecular dynamics and docking reveal the potency of novel GTP derivatives against RNA dependent RNA polymerase of genotype 4a HCV. Life Sci. 238, 116958 (2019). [DOI] [PubMed] [Google Scholar]
- 39.Singh R, Bhardwaj VK, Sharma J, Das P, Purohit R. Discovery and in silico evaluation of aminoarylbenzosuberene molecules as novel checkpoint kinase 1 inhibitor determinants. Genomics 113(1 Pt 2), 707–715 (2021). [DOI] [PubMed] [Google Scholar]
- 40.Bhardwaj VK, Singh R, Sharma J, Rajendran V, Purohit R, Kumar S. Identification of bioactive molecules from tea plant as SARS-CoV-2 main protease inhibitors. J. Biomol. Struct. Dyn. 1–10 (2020) (Epub ahead of print). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Elfiky AA. Reply to a letter to the editor. Life Sci. 252, 117715 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Bhardwaj VK, Singh R, Das P, Purohit R. Evaluation of acridinedione analogs as potential SARS-CoV-2 main protease inhibitors and their comparison with repurposed anti-viral drugs. Comput. Biol. Med. 128, 104117 (2021). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Kim S, Thiessen PA, Bolton EE et al. PubChem substance and compound databases. Nucleic Acids Res. 44(D1), D1202–1213 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Halgren TA. Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. J. Comput. Chem. 17(5–6), 490–519 (1996). [Google Scholar]
- 45.Halgren TA. Merck molecular force field. II. MMFF94 van der Waals and electrostatic parameters for intermolecular interactions. J. Comput. Chem. 17(5–6), 520–552 (1996). [Google Scholar]
- 46.Berman H, Henrick K, Nakamura H. Announcing the worldwide Protein Data Bank. Nat. Struct. Biol. 10(12), 980 (2003). [DOI] [PubMed] [Google Scholar]
- 47.Studio D. Discovery Studio. Accelrys [2.1] (2008). [Google Scholar]
- 48.Guex N, Peitsch MC. SWISS-MODEL and the Swiss-Pdb Viewer: an environment for comparative protein modeling. Electrophoresis 18(15), 2714–2723 (1997). [DOI] [PubMed] [Google Scholar]
- 49.Scott WRP, Hünenberger PH, Tironi IG et al. The GROMOS biomolecular simulation program package. J. Phys. Chem. A 103(19), 3596–3607 (1999). [Google Scholar]
- 50.Chandra A, Gurjar V, Qamar I, Singh N. Identification of potential inhibitors of SARS-CoV-2 endoribonuclease (EndoU) from FDA approved drugs: a drug repurposing approach to find therapeutics for COVID-19. J. Biomol. Struct. Dyn. 1–11 (2020) (Epub ahead of print). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 51.Trott O, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem. 31(2), 455–461 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 52.Morris GM, Huey R, Lindstrom W et al. AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J. Comput. Chem. 30(16), 2785–2791 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 53.The PyMOL Molecular Graphics System, Version 2.4.1 Schrödinger, LLC.
- 54.Elfiky AA. Anti-HCV, nucleotide inhibitors, repurposing against COVID-19. Life Sci. 248, 117477 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 55.Jokhakar PH, Kalaria R, Patel HK. In silico docking studies of antimalarial drug hydroxychloroquine to SARS-CoV proteins: an emerging pandemic worldwide. ChemRxiv. (2020) (Epub ahead of print). [Google Scholar]
- 56.Turnbull AP, Boyd SM. Targeting cancer using fragment based drug discovery. Anticancer Agents Med. Chem. 12(1), 40–48 (2012). [DOI] [PubMed] [Google Scholar]
- 57.Meng XY, Zhang HX, Mezei M, Cui M. Molecular docking: a powerful approach for structure-based drug discovery. Curr. Comput. Aided Drug Des. 7(2), 146–157 (2011). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 58.Egli M, Tereshko V, Mushudov GN, Sanishvili R, Liu X, Lewis FD. Face-to-face and edge-to-face pi-pi interactions in a synthetic DNA hairpin with a stilbenediether linker. J. Am. Chem. Soc. 125(36), 10842–10849 (2003). [DOI] [PubMed] [Google Scholar]
- 59.Uddin N, Ahmed S, Khan AM, Mazharol Hoque M, Halim MA. Halogenated derivatives of methotrexate as human dihydrofolate reductase inhibitors in cancer chemotherapy. J. Biomol. Struct. Dyn. 38(3), 901–917 (2020). [DOI] [PubMed] [Google Scholar]
- 60.Costa PJ. The halogen bond: nature and applications. Phys. Sci. Rev. 2(11), 1–16 (2017). [Google Scholar]
- 61.Pedersen SW, Hultqvist G, Stromgaard K, Jemth P. The role of backbone hydrogen bonds in the transition state for protein folding of a PDZ domain. PLoS ONE 9(4), e95619 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 62.Van De Waterbeemd H, Gifford E. ADMET in silico modelling: towards prediction paradise? Nat. Rev. Drug Discov. 2(3), 192–204 (2003). [DOI] [PubMed] [Google Scholar]
- 63.Bello M, Martinez-Munoz A, Balbuena-Rebolledo I. Identification of saquinavir as a potent inhibitor of dimeric SARS-CoV2 main protease through MM/GBSA. J. Mol. Model 26(12), 340 (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
- 64.Genheden S, Ryde U. The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opin. Drug Discov. 10(5), 449–461 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
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