Computational investigation of phytoalexins as potential antiviral RAP-1 and RAP-2 (Replication Associated Proteins) inhibitor for the management of cucumber mosaic virus (CMV): a molecular modeling, in silico docking and MM-GBSA study

References

• Ahola, T., & Ahlquist, P. (1999). Putative RNA capping activities encoded by brome mosaic virus: Methylation and covalent binding of guanylate by replicase protein RAP-1. Journal of Virology, 73(12), 10061–10069. https://doi.org/10.1128/JVI.73.12.10061-10069.1999
   PubMed Web of Science ®Google Scholar
• Argos, P. (1988). A sequence motif in many polymerases. Nucleic Acids Research, 16(21), 9909–9916. https://doi.org/10.1093/nar/16.21.9909
   PubMed Web of Science ®Google Scholar
• Bailey, J. A. (1973). Production of antifungal compounds in cowpea (Vigna sinensis) and pea (Pisum sativum) after virus infection. Microbiology, 75, 119–123.
   Web of Science ®Google Scholar
• Banerjee, P., Eckert, A. O., Schrey, A. K., & Preissner, R. (2018). ProTox-II: A webserver for the prediction of toxicity of chemicals. Nucleic Acids Research, 46, 257–263. https://doi.org/10.1093/nar/gky318
   PubMed Web of Science ®Google Scholar
• Bona, S. D. G., Bertazzon, N., Angelini, E., & Vincenzi, S. (2020). Influence of pruning time and viral infection on stilbenoid levels in Pinot noir grape canes. Journal of the Science of Food and Agriculture, 100(4), 1741–1747. https://doi.org/10.1002/jsfa.10195
   PubMed Web of Science ®Google Scholar
• Brylinski, M., & Skolnick, J. (2008). A threading-based method (FINDSITE) for ligand-binding site prediction and functional annotation. Proceedings of the National Academy of Sciences, 105(1), 129–134. https://doi.org/10.1073/pnas.0707684105
   PubMed Web of Science ®Google Scholar
• Burden, R. S., Bailey, J. A., & Vincent, G. G. (1975). Glutinosone, a new antifungal sesquiterpene from Nicotiana glutinosa infected with tobacco mosaic virus. Phytochemistry, 14(1), 221–223. https://doi.org/10.1016/0031-9422(75)85043-6
   Web of Science ®Google Scholar
• Chaube, H. S., & Pundhir, V. S. (2005). Crop diseases and their management. PHI Learning Pvt. Ltd.
   Google Scholar
• Daina, A., Michielin, O., & Zoete, V. (2017). SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Scientific Reports, 7(1), 1–3.
   PubMed Web of Science ®Google Scholar
• Fariselli, P., Riccobelli, P., & Casadio, R. (1999). Role of evolutionary information in predicting the disulfide‐bonding state of cysteine in proteins. Proteins: Structure, Function, and Genetics, 36(3), 340–346. https://doi.org/10.1002/(SICI)1097-0134(19990815)36:3<340::AID-PROT8>3.0.CO;2-D
   PubMed Web of Science ®Google Scholar
• Ferrè, F., & Clote, P. (2006). DiANNA 1.1: An extension of the DiANNA web server for ternary cysteine classification. Nucleic Acids Research, 34, 182–185.
   PubMed Web of Science ®Google Scholar
• Friesner, R. A., Banks, J. L., Murphy, R. B., Halgren, T. A., Klicic, J. J., Mainz, D. T., Repasky, M. P., Knoll, E. H., Shelley, M., Perry, J. K., Shaw, D. E., Francis, P., & Shenkin, P. S. (2004). Glide: A new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. Journal of Medicinal Chemistry, 47(7), 1739–1749. https://doi.org/10.1021/jm0306430
   PubMed Web of Science ®Google Scholar
• Gasteiger, E., Hoogland, C., Gattiker, A., Wilkins, M. R., Appel, R. D., & Bairoch, A. (2005). Protein identification and analysis tools on the ExPASy server. In Walker JM (Ed.), The proteomics protocols handbook (pp. 571–607). Humana Press.
   Google Scholar
• Geourjon, C., & Deleage, G. (1995). SOPMA: Significant improvements in protein secondary structure prediction by consensus prediction from multiple alignments. Computer Applications in the Biosciences : CABIOS, 11(6), 681–684. https://doi.org/10.1093/bioinformatics/11.6.681
   PubMedGoogle Scholar
• Gorbalenya, A. E., Koonin, E. V., Donchenko, A. P., & Blinov, V. M. (1988). A novel superfamily of nucleoside triphosphate-binding motif containing proteins which are probably involved in duplex unwinding in DNA and RNA replication and recombination. FEBS Letters, 235(1-2), 16–24. https://doi.org/10.1016/0014-5793(88)81226-2
   PubMed Web of Science ®Google Scholar
• Gorbalenya, A. E., Pringle, F. M., Zeddam, J. L., Luke, B. T., Cameron, C. E., Kalmakoff, J., Hanzlik, T. N., Gordon, K. H., & Ward, V. K. (2002). The palm subdomain-based active site is internally permuted in viral RNA-dependent RNA polymerases of an ancient lineage. Journal of Molecular Biology, 324(1), 47–62. https://doi.org/10.1016/s0022-2836(02)01033-1
   PubMed Web of Science ®Google Scholar
• Gowthaman, U., Jayakanthan, M., & Sundar, D. (2008). Molecular docking studies of dithionitrobenzoic acid and its related compounds to protein disulfide isomerase: Computational screening of inhibitors to HIV-1 entry. BMC Bioinformatics, 9(Suppl 12), S14– 10. https://doi.org/10.1186/1471-2105-9-S12-S14
   PubMedGoogle Scholar
• Guest, D. (2017). Phytoalexins, naturals plant protecction. Encyclopedia of applied plant sciences. Academic press.
   Google Scholar
• Guo, W., Lu, X., Liu, B., Yan, H., & Feng, J. (2021). Anti-TMV activity and mode of action of three alkaloids isolated from Chelidonium majus . Pest Management Science, 77(1), 510–517. https://doi.org/10.1002/ps.6049
   PubMedGoogle Scholar
• Guruprasad, K., Reddy, B. B., & Pandit, M. W. (1990). Correlation between stability of a protein and its dipeptide composition: A novel approach for predicting in vivo stability of a protein from its primary sequence. Protein Engineering, 4(2), 155–161. https://doi.org/10.1093/protein/4.2.155
   PubMedGoogle Scholar
• Hammerschmidt, R. (1999). Phytoalexins: What have we learned after 60 years? Annual Review of Phytopathology, 37, 285–306. https://doi.org/10.1146/annurev.phyto.37.1.285
   PubMed Web of Science ®Google Scholar
• Harder, E., Damm, W., Maple, J., Wu, C., Reboul, M., Xiang, J. Y., Wang, L., Lupyan, D., Dahlgren, M. K., Knight, J. L., Kaus, J. W., Cerutti, D. S., Krilov, G., Jorgensen, W. L., Abel, R., & Friesner, R. A. (2016). OPLS3: A force field providing broad coverage of drug-like small molecules and proteins. Journal of Chemical Theory and Computation, 12(1), 281–296. https://doi.org/10.1021/acs.jctc.5b00864
   PubMed Web of Science ®Google Scholar
• Haseloff, J., Goelet, P., Zimmern, D., Ahlquist, P., Dasgupta, R., & Kaesberg, P. (1984). Striking similarities in amino acid sequence among nonstructural proteins encoded by RNA viruses that have dissimilar genomic organization. Proceedings of the National Academy of Sciences of the United States of America, 81(14), 4358–4362. https://doi.org/10.1073/pnas.81.14.4358
   PubMed Web of Science ®Google Scholar
• Ikai, A. (1980). Thermostability and aliphatic index of globular proteins. Journal of Biochemistry, 88(6), 1895–1898.
   PubMed Web of Science ®Google Scholar
• Jeandet, P. (2015). Phytoalexins: Current progress and future prospects. Molecules, 20(2), 2770–2774. https://doi.org/10.3390/molecules20022770
   Web of Science ®Google Scholar
• Jethra, G., Mishra, A. K., Pandey, P. S., & Chandrasekharan, H. (2012). Structure and function prediction of unknown wheat protein using LOMETS and I-TASSER. Indian Journal of Agricultural Sciences, 82, 867.
   Web of Science ®Google Scholar
• Kant, K., Rawat, R., Bhati, V., Bhosale, S., Sharma, D., Banerjee, S., & Kumar, A. (2020). Computational identification of natural product leads that inhibit mast cell chymase: An exclusive plausible treatment for Japanese encephalitis. Journal of Biomolecular Structure and Dynamics, 39(4), 1–10.
   Web of Science ®Google Scholar
• Ko, J., Park, H., Heo, L., & Seok, C. (2012). GalaxyWEB server for protein structure prediction and refinement. Nucleic Acids Research., 40, 294–307.
   PubMed Web of Science ®Google Scholar
• Kong, F., Sivakumaran, K., & Kao, C. (1999). The N-terminal half of the brome mosaic virus 1a protein has RNA capping-associated activities: specificity for GTP and S-adenosylmethionine. Virology, 259(1), 200–210. https://doi.org/10.1006/viro.1999.9763
   PubMed Web of Science ®Google Scholar
• Laskowski, R. A., MacArthur, M. W., Moss, D. S., & Thornton, J. M. (1993). PROCHECK: A program to check the stereochemical quality of protein structures. Journal of Applied Crystallography, 26(2), 283–291. https://doi.org/10.1107/S0021889892009944
   Web of Science ®Google Scholar
• Li, L., Li, Z., Wang, K., Zhao, S., Feng, J., Li, J., Yang, P., Liu, Y., Wang, L., Li, Y., Shang, H., & Wang, Q. (2014). Design, synthesis, and biological activities of aromatic gossypol Schiff base derivatives. Journal of Agricultural and Food Chemistry, 62(46), 11080–11108. https://doi.org/10.1021/jf504411g
   PubMed Web of Science ®Google Scholar
• Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (1997). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 23(1-3), 3–25. https://doi.org/10.1016/S0169-409X(96)00423-1
   Web of Science ®Google Scholar
• Lygin, A. V., Hill, C. B., Zernova, O. V., Crull, L., Widholm, J. M., Hartman, G. L., & Lozovaya, V. V. (2010). Response of soybean pathogens to glyceollin. Phytopathology, 100(9), 897–903. https://doi.org/10.1094/PHYTO-100-9-0897
   PubMed Web of Science ®Google Scholar
• Naidoo, D., Roy, A., Kar, P., Mutanda, T., & Anandraj, A. (2020). Cyanobacterial metabolites as promising drug leads against the Mpro and PLpro of SARS-CoV-2: An in silico analysis. Journal of Biomolecular Structure and Dynamics, 18, 1–13.
   Google Scholar
• Natesh, J., Mondal, P., Kaur, B., Abdul Salam, A. A., Kasilingam, S., & Meeran, S. M. (2021). Promising phytochemicals of traditional Himalayan medicinal plants against putative replication and transmission targets of SARS-CoV-2 by computational investigation. Computers in Biology and Medicine, 133, 104383. https://doi.org/10.1016/j.compbiomed.2021.104383
   PubMed Web of Science ®Google Scholar
• O'Boyle, N. M., Banck, M., James, C. A., Morley, C., Vandermeersch, T., & Hutchison, G. R. (2011). Open Babel: An open chemical toolbox. Journal of Cheminformatics, 3, 33– 34. https://doi.org/10.1186/1758-2946-3-33
   PubMed Web of Science ®Google Scholar
• Onawole, A. T., Kolapo, T. U., Sulaiman, K. O., & Adegoke, R. O. (2018). Structure based virtual screening of the Ebola virus trimeric glycoprotein using consensus scoring. Computational Biology and Chemistry, 72, 170–180. https://doi.org/10.1016/j.compbiolchem.2017.11.006
   PubMed Web of Science ®Google Scholar
• Pandey, P., Irulappan, V., Bagavathiannan, M. V., & Senthil-Kumar, M. (2017). Impact of combined abiotic and biotic stresses on plant growth and avenues for crop improvement by exploiting physio-morphological traits. Frontiers in Plant Science, 8, 537. https://doi.org/10.3389/fpls.2017.00537
   PubMed Web of Science ®Google Scholar
• Parniske, M., Ahlborn, B., & Werner, D. (1991). Isoflavonoid-inducible resistance to the phytoalexin glyceollin in soybean rhizobia. Journal of Bacteriology, 173(11), 3432–3449. https://doi.org/10.1128/jb.173.11.3432-3439.1991
   PubMed Web of Science ®Google Scholar
• Pathak, R. K., Baunthiyal, M., Shukla, R., Pandey, D., Taj, G., & Kumar, A. (2017). In silico identification of mimicking molecules as defense inducers triggering jasmonic acid mediated immunity against alternaria blight disease in brassica species. Frontiers in Plant Science, 8, 609. https://doi.org/10.3389/fpls.2017.00609
   PubMed Web of Science ®Google Scholar
• Rawat, R., & Verma, S. M. (2020a). An exclusive computational insight toward molecular mechanism of MMV007571, a multitarget inhibitor of Plasmodium falciparum. Journal of Biomolecular Structure & Dynamics, 38(18), 5362–5373. https://doi.org/10.1080/07391102.2019.1700165
   PubMed Web of Science ®Google Scholar
• Rawat, R., & Verma, S. M. (2020b). High-throughput virtual screening approach involving pharmacophore mapping, ADME filtering, molecular docking and MM-GBSA to identify new dual target inhibitors of Pf DHODH and Pf Cytbc1 complex to combat drug resistant malaria. Journal of Biomolecular Structure and Dynamics, 39(14), 1–12.
   Web of Science ®Google Scholar
• Roy, A., Yang, J., & Zhang, Y. (2012). COFACTOR: An accurate comparative algorithm for structure-based protein function annotation. Nucleic Acids Research, 40(Web Server issue), W471–507.
   PubMedGoogle Scholar
• Salánki, K., Gellért, Á., Nemes, K., Divéki, Z., & Balázs, E. (2018). Molecular modeling for better understanding of cucumovirus pathology. Advances in Virus Research, 102, 59–88.
   PubMed Web of Science ®Google Scholar
• Sanner, M. F. (1999). Python: A programming language for software integration and development. Journal of Molecular Graphics & Modelling, 17(1), 57–61.
   PubMed Web of Science ®Google Scholar
• Sidhu, K. S., Bhangu, S. K., Pathak, R. K., Yadav, I. S., & Chhuneja, P. (2020). Identification of natural lead compounds for leaf rust of Wheat: A molecular docking and simulation study. Journal of Proteins and Proteomics, 11(4), 283–295. https://doi.org/10.1007/s42485-020-00048-5
   Google Scholar
• Sirin, S., Kumar, R., Martinez, C., Karmilowicz, M. J., Ghosh, P., Abramov, Y. A., Martin, V., & Sherman, W. (2014). A computational approach to enzyme design: Predicting ω-aminotransferase catalytic activity using docking and MM-GBSA scoring. Journal of Chemical Information and Modeling, 54(8), 2334–2346. https://doi.org/10.1021/ci5002185
   PubMed Web of Science ®Google Scholar
• Sivaramakrishnan, V., Thiyagarajan, C., Kalaivanan, S., Selvakumar, R., Anusuyadevi, M., & Jayachandran, K. S. (2012). Homology modeling, molecular docking and electrostatic potential analysis of MurF ligase from Klebsiella pneumonia. Bioinformation, 8(10), 466–473. https://doi.org/10.6026/97320630008466
   PubMedGoogle Scholar
• Smith, E. C. (2017). The not-so-infinite malleability of RNA viruses: Viral and cellular determinants of RNA virus mutation rates. PLoS Pathogens, 13(4), e1006254. https://doi.org/10.1371/journal.ppat.1006254
   PubMed Web of Science ®Google Scholar
• Song, H., Liu, Y., Liu, Y., Wang, L., & Wang, Q. (2014). Synthesis and antiviral and fungicidal activity evaluation of β-carboline, dihydro-β-carboline, tetrahydro-β-carboline alkaloids, and their derivatives. Journal of Agricultural and Food Chemistry, 62(5), 1010–1018. https://doi.org/10.1021/jf404840x
   PubMed Web of Science ®Google Scholar
• Takasugi, M., Nagao, S., Masamune, T., Shirata, A., & Takahashi, K. (1979). Structures of moracins E, F, G, and H, new phytoalexins from diseased mulberry. Tetrahedron Letters, 20(48), 4675–4678. https://doi.org/10.1016/S0040-4039(01)86680-6
   Google Scholar
• Trott, O., & Olson, A. J. (2010). AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. Journal of Computational Chemistry, 31(2), 455–461. https://doi.org/10.1002/jcc.21334
   PubMed Web of Science ®Google Scholar
• Tzean, Y., Lee, M. C., Jan, H. H., Chiu, Y. S., Tu, T. C., Hou, B. H., Chen, H. M., Chou, C. N., & Yeh, H. H. (2019). Cucumber mosaic virus-induced gene silencing in banana. Scientific Reports, 9(1), 11553–11559. https://doi.org/10.1038/s41598-019-47962-3
   PubMedGoogle Scholar
• Watt, L. G., Crawshaw, S., Rhee, S. J., Murphy, A. M., Canto, T., & Carr, J. P. (2020). The cucumber mosaic virus RAP-1 protein regulates interactions between the 2b protein and ARGONAUTE 1 while maintaining the silencing suppressor activity of the 2b protein. PLOS Pathogens, 16(12), e1009125. https://doi.org/10.1371/journal.ppat.1009125
   PubMed Web of Science ®Google Scholar
• Wu, S., Skolnick, J., & Zhang, Y. (2007). Ab initio modeling of small proteins by iterative TASSER simulations. BMC Biology, 5(1), 17–10. https://doi.org/10.1186/1741-7007-5-17
   PubMed Web of Science ®Google Scholar
• Wu, S. T., & Zhang, Y. (2007). LOMETS: A local meta-threading-server for protein structure prediction. Nucleic Acids Research, 10, 3375–3382.
   Google Scholar
• Yang, J., Roy, A., & Zhang, Y. (2013). Protein–ligand binding site recognition using complementary binding-specific substructure comparison and sequence profile alignment. Bioinformatics, 29(20), 2588–2595. https://doi.org/10.1093/bioinformatics/btt447
   PubMed Web of Science ®Google Scholar
• Zhang, Y. (2008). I-TASSER server for protein 3D structure prediction. BMC Bioinformatics, 9, 40– 48. https://doi.org/10.1186/1471-2105-9-40
   PubMed Web of Science ®Google Scholar
• Zhang, Y., & Skolnick, J. (2004). Automated structure prediction of weakly homologous proteins on a genomic scale. Proceedings of the National Academy of Sciences of the United States of America, 101(20), 7594–7599. https://doi.org/10.1073/pnas.0305695101
   PubMed Web of Science ®Google Scholar
• Zheng, W., Zhou, X., Wuyun, Q., Pearce, R., Li, Y., & Zhang, Y. (2020). FUpred: Detecting protein domains through deep-learning-based contact map prediction. Bioinformatics (Oxford, England), 36(12), 3749–3757. https://doi.org/10.1093/bioinformatics/btaa217
   PubMed Web of Science ®Google Scholar