Archive \ Volume.13 2022 Issue 3

Screening of Phytochemicals Against Snake Venom Metalloproteinase: Molecular Docking and Simulation Based Computational Approaches

Ahmad Mohajja Alshammari
Abstract

Echis coloratus (Carpet viper), which is a snake, produces an enzyme called snake venom metalloproteinase (SVMP), which has multiple functions. The venomous viper Echis coloratus is endemic to the Middle East and Egypt. Its symptoms include severe local bleeding, nervous system impacts and tissue necrosis. The target proteins' three-dimensional (3D) structures were predicted using the I-TASSER server because the 3D structure of SVMP is unknown. Using a molecular docking technique, the molecular operating environment (MOE) application was used to screen a library of 1000 phytochemicals against the interaction residues of the target protein. Additionally, molecular dynamics simulations and the widely used MM-GBSA and MM-PBSA binding free energy techniques were used to assess the molecular docking experiments. The results showed that in the SVMP active region, the selected lead compounds were remarkably stable. Promising potential drug candidates (Rutamarin, Enterodiol, Butyl butyrate, Colchicine, Sanggenon A, Quercetin, Campesterol, and Cholesterol) for novel target against SVMP has been discovered in the conducted studies.


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Vancouver
Alshammari AM. Screening of Phytochemicals Against Snake Venom Metalloproteinase: Molecular Docking and Simulation Based Computational Approaches. Arch Pharm Pract. 2022;13(3):76-84. https://doi.org/10.51847/HIrDcdPCGL
APA
Alshammari, A. M. (2022). Screening of Phytochemicals Against Snake Venom Metalloproteinase: Molecular Docking and Simulation Based Computational Approaches. Archives of Pharmacy Practice, 13(3), 76-84. https://doi.org/10.51847/HIrDcdPCGL

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References

1.        Fry BG, Roelants K, Champagne DE, Scheib H, Tyndall JD, King GF, et al. The toxicogenomic multiverse: convergent recruitment of proteins into animal venoms. Annu Rev Genomics Hum Genet. 2009;10(1):483-511.

2.        Yang S, Liu Z, Xiao Y, Li Y, Rong M, Liang S, et al. Chemical punch packed in venoms makes centipedes excellent predators. Mol Cell Proteomics. 2012;11(9):640-50.

3.        Petrilla V, Polláková M, Bekešová B, Andrejčáková Z, Vlčková R, Marcinčáková D, et al. A Comprehensive Study Monitoring the Venom Composition and the Effects of the Venom of the Rare Ethiopian Endemic Snake Species Bitis parviocula. Toxins. 2021;13(5):299.

4.        Mallow D, Ludwig D, Nilson G. True vipers: natural history and toxinology of old world vipers. Krieger Publishing Company; 2003.

5.        Aoki-Shioi N, Koh CY, Kini RM. Natural inhibitors of snake venom metalloproteinases. Aust J Chem. 2020;73(4):277-86.

6.        Al Masroori S, Al Balushi F, Al Abri S. Evaluation of risk factors of snake envenomation and associated complications presenting to two emergency departments in Oman. Oman Med J. 2022;37(2):e349.

7.        Gutiérrez JM, Albulescu LO, Clare RH, Casewell NR, Abd El-Aziz TM, Escalante T, et al. The search for natural and synthetic inhibitors that would complement antivenoms as therapeutics for snakebite envenoming. Toxins. 2021;13(7):451.

8.        Kalita B, Saviola AJ, Samuel SP, Mukherjee AK. State-of-the-art review-A review on snake venom-derived antithrombotics: Potential therapeutics for COVID-19-associated thrombosis?. Int J Biol Macromol. 2021;192:1040-57.

9.        Tasoulis T, Pukala TL, Isbister GK. Investigating toxin diversity and abundance in snake venom proteomes. Front Pharmacol. 2021;12.

10.      Oyama E, Takahashi H. Structures and functions of snake venom metalloproteinases (SVMP) from Protobothrops venom collected in Japan. Molecules. 2017;22(8):1305.

11.      Adeyi AO, Mustapha KK, Ajisebiola BS, Adeyi OE, Metibemu DS, Okonji RE. Inhibition of Echis ocellatus venom metalloprotease by flavonoid-rich ethyl acetate sub-fraction of Moringa oleifera (Lam.) leaves: in vitro and in silico approaches. Toxin Rev. 2022;41(2):476-86.

12.      Wolfsberg TG, Primakoff P, Myles DG, White JM. ADAM, a novel family of membrane proteins containing A Disintegrin And Metalloprotease domain: multipotential functions in cell-cell and cell-matrix interactions. J Cell Biol. 1995;131(2):275-8.

13.      Pagadala NS, Syed K, Tuszynski J. Software for molecular docking: a review. Biophys Rev. 2017;9(2):91-102.

14.      Boutet E, Lieberherr D, Tognolli M, Schneider M, Bairoch A. Uniprotkb/swiss-prot. InPlant bioinformatics 2007 (pp. 89-112). Humana Press.

15.      Zhang Y. I-TASSER server for protein 3D structure prediction. BMC Bioinform. 2008;9(1):1-8.

16.      Wiederstein M, Sippl MJ. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res. 2007;35(suppl_2):W407-10.

17.      Xia TH, Bushweller JH, Sodano P, Billeter M, Björnberg O, Holmgren A, et al. NMR structure of oxidized Escherichia coli glutaredoxin: comparison with reduced E. coli glutaredoxin and functionally related proteins. Protein Sci. 1992;1(3):310-21.

18.      Lovell SC, Davis IW, Arendall III WB, De Bakker PI, Word JM, Prisant MG, et al. Structure validation by Cα geometry: ϕ, ψ and Cβ deviation. Proteins. 2003;50(3):437-50.

19.      Eisenberg D, Lüthy R, Bowie JU. [20] VERIFY3D: assessment of protein models with three-dimensional profiles. InMethods in enzymology 1997 Jan 1 (Vol. 277, pp. 396-404). Academic Press.

20.      Vilar S, Cozza G, Moro S. Medicinal chemistry and the molecular operating environment (MOE): application of QSAR and molecular docking to drug discovery. Curr Top Med Chem. 2008;8(18):1555-72.

21.      Kim S, Thiessen PA, Bolton EE, Chen J, Fu G, Gindulyte A, et al. PubChem substance and compound databases. Nucleic Acids Res. 2016;44(D1):D1202-13.

22.      Mumtaz A, Ashfaq UA, Ul Qamar MT, Anwar F, Gulzar F, Ali MA, et al. MPD3: a useful medicinal plants database for drug designing. Nat Prod Res. 2017;31(11):1228-36.

23.      Irwin JJ, Shoichet BK. ZINC− a free database of commercially available compounds for virtual screening. J Chem Inf Model. 2005;45(1):177-82.

24.      de Vries SJ, Bonvin AM. CPORT: a consensus interface predictor and its performance in prediction-driven docking with HADDOCK. PloS One. 2011;6(3):e17695.

25.      Podvinec M, Lim SP, Schmidt T, Scarsi M, Wen D, Sonntag LS, et al. Novel inhibitors of dengue virus methyltransferase: discovery by in vitro-driven virtual screening on a desktop computer grid. J Med Chem. 2010;53(4):1483-95.

26.      Khalifa I, Zhu W, Mohammed HH, Dutta K, Li C. Tannins inhibit SARS‐CoV‐2 through binding with catalytic dyad residues of 3CLpro: An in silico approach with 19 structural different hydrolysable tannins. J Food Biochem. 2020;44(10):e13432.

27.      Pettersen EF, Goddard TD, Huang CC, Couch GS, Greenblatt DM, Meng EC, et al. UCSF Chimera—a visualization system for exploratory research and analysis. J Comput Chem. 2004;25(13):1605-12.

28.      Panda M, Purohit P, Meher BR. Structure-based virtual screening, ADMET profiling, and molecular dynamics simulation studies on HIV-1 protease for identification of active phytocompounds as potential anti-HIV agents. Mol Simul. 2022:1-9.

29.      Jeysiha C, Abilasha D, Thusnavis GR, Kumaresan S, Palanisamy P. A combined study on the Molecular Docking, ADMET Profiling and Anti-tuberculosis Activity of Phytocompounds Obtained from the Barks of Cassia auriculata as Potential Inhibitors of Mycobacterium tuberculosis (H37Rv) Protein (5HKF).

30.      Abdul-Hammed M, Adedotun IO, Olajide M, Irabor CO, Afolabi TI, Gbadebo IO, et al. Virtual screening, ADMET profiling, PASS prediction, and bioactivity studies of potential inhibitory roles of alkaloids, phytosterols, and flavonoids against COVID-19 main protease (Mpro). Nat Prod Res. 2022;36(12):3110-6.

31.      Chandrasekaran J, Elumalai S, Murugesan V, Kunjiappan S, Pavadai P, Theivendren P. Computational design of PD-L1 small molecule inhibitors for cancer therapy. Mol Divers. 2022:1-2.

32.      Raghi KR, Sherin DR, Archana TM, Saumya MJ, Sajesha KP, Manojkumar TK. Identification of Potent ABL Inhibitors from Coumestrol: An Integrative In Silico Approach. J Comput Biophys Chem. 2022:1-3.

33.      Release S. 3: Desmond molecular dynamics system, DE Shaw research, New York, NY, 2017. Maestro-Desmond Interoperability Tools, Schrödinger, New York, NY. 2017.

34.      Shivakumar D, Williams J, Wu Y, Damm W, Shelley J, Sherman W. Prediction of absolute solvation free energies using molecular dynamics free energy perturbation and the OPLS force field. J Chem Theory Comput. 2010;6(5):1509-19.

35.      Jorgensen WL, Chandrasekhar J, Madura JD, Impey RW, Klein ML. Comparison of simple potential functions for simulating liquid water. J Chem Phys. 1983;79(2):926-35.

36.      Zhu H, Liu J, Chakraborty C, Chen L. Analysing the effect of mutation on protein function and discovering potential inhibitors of CDK4: molecular modelling and dynamics studies. PLoS One. 2015;10(8):e0133969.

37.      Gutiérrez JM, Calvete JJ, Habib AG, Harrison RA, Williams DJ, Warrell DA. Snakebite envenoming. Nat Rev Dis Primers. 2017;3(1):1-21.

38.      Otero-Patiño R. Epidemiological, clinical and therapeutic aspects of Bothrops asper bites. Toxicon. 2009;54(7):998-1011.

39.      Gutiérrez JM, Rucavado A, Chaves F, Díaz C, Escalante T. Experimental pathology of local tissue damage induced by Bothrops asper snake venom. Toxicon. 2009;54(7):958-75.

40.      Gutiérrez JM, Theakston RD, Warrell DA. Confronting the neglected problem of snake bite envenoming: the need for a global partnership. PLoS Med. 2006;3(6):e150.

41.      Sandesha VD, Darshan B, Tejas C, Girish KS, Kempaiah K. A comparative cross-reactivity and paraspecific neutralization study on Hypnale hypnale, Echis carinatus, and Daboia russelii monovalent and therapeutic polyvalent anti-venoms. PLoS Negl Trop Dis. 2022;16(3):e0010292.

42.      Menzies SK, Dawson CA, Crittenden E, Edge RJ, Hall SR, Alsolaiss J, et al. Virus-like particles displaying conserved toxin epitopes stimulate polyspecific, murine antibody responses capable of snake venom recognition. Sci Rep. 2022;12(1):1-5.

43.      Barua A, Kesavan K, Jayanthi S. Molecular Docking Studies of Plant Compounds to Identify Efficient Inhibitors for Ovarian Cancer. Res J Pharm Technol. 2018;11(9):3811-5.

44.      Vale HF, M Mendes M, S Fernandes R, R Costa T, IS Hage-Melim L, A Sousa M, et al. Protective effect of Schizolobium parahyba flavonoids against snake venoms and isolated toxins. Curr Top Med Chem. 2011;11(20):2566-77.

45.      Preciado LM, Comer J, Núñez V, Rey-Súarez P, Pereañez JA. Inhibition of a snake venom metalloproteinase by the flavonoid myricetin. Molecules. 2018;23(10):2662.

46.      Lengauer T, Rarey M. Computational methods for biomolecular docking. Curr Opin Struct Biol. 1996;6(3):402-6.

47.      ul Qamar MT, Kiran S, Ashfaq UA, Javed MR, Anwar F, Ali MA, et al. Discovery of novel dengue NS2B/NS3 protease inhibitors using pharmacophore modeling and molecular docking based virtual screening of the zinc database. Int J Pharmacol. 2016;12(6):621-32.

48.      Lin B, He S, Yim HJ, Liang TJ, Hu Z. Evaluation of antiviral drug synergy in an infectious HCV system. Antivir Ther. 2016;21(7):595-603.

49.      Tsaioun K, Bottlaender M, Mabondzo A. ADDME–Avoiding Drug Development Mistakes Early: central nervous system drug discovery perspective. BMC Neurol. 2009;9(1):1-1.


 


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