Sains Malaysiana 49(3)(2020): 537-544

http://dx.doi.org/10.17576/jsm-2020-4903-08

 

Computational Quest for Finding Potential Ebola VP40 Inhibitors: A Molecular Docking Study

(Pencarian Pengiraan untuk Mencari Potensi Perencat Ebola VP40: Suatu Kajian Mengedok Molekul)

MOHAMAD ARIFF MOHAMAD YUSSOFF1, AZZMER AZZAR ABD HAMID1,3, SHAFIDA ABD HAMID2 & KHAIRUL BARIYYAH ABD HALIM1,3*

1Department of Biotechnology, Kulliyyah of Science, International Islamic University Malaysia, 25200 Kuantan, Pahang Darul Makmur, Malaysia

2Department of Chemistry, Kulliyyah of Science, International Islamic University Malaysia, 25200 Kuantan, Pahang Darul Makmur, Malaysia 

3Research Unit for Bioinformatics and Computational Biology, Kulliyyah of Science, International Islamic University Malaysia, 25200 Kuantan, Pahang Darul Makmur, Malaysia 

Diserahkan: 1 Ogos 2019/Diterima: 5 Disember 2019

 

ABSTRACT

Interaction of Ebola virus matrix protein VP40 with RNA is crucial in the early infection stage to facilitate the transcription of the viral gene. Thus, VP40 is a promising target to inhibit the Ebola virus from spreading. This study aims to identify and optimize ligands that can potentially block the VP40-RNA binding site. A total of 42 compounds from previously studied ligands from the literature were simulated against the RNA binding site using Autodock Vina. The top ten ligands were used as templates for similarity search in ZINC database followed by structured-based virtual screening. Then, the ADME properties of the top compounds were predicted computationally using SwissADME server. Our results showed that Q-96 (ZINC ID: 1338855) is the best docked compound with binding free energy of -7.5 kcal/mol. The compound also has satisfactory ADME properties prediction with good lipophilicity value, moderate water solubility and high gastrointestinal absorption. Besides, this ligand does not violate any drug likeness rules as well as no PAINS and Brenk alerts, indicate it has the properties as a drug. Thus, it is worth to carry out further investigations on this structure more in silico as well as in vitro and in vivo levels towards finding the treatment for Ebola virus disease.

Keywords: ADME; Ebola virus; molecular docking: VP40 matrix protein

ABSTRAK

Interaksi matriks virus Ebola VP40 dengan RNA adalah penting dalam peringkat jangkitan awal untuk memudahkan transkripsi gen virus. Oleh itu, VP40 adalah sasaran yang sesuai bagi menghalang virus Ebola daripada terus merebak. Kajian ini bertujuan untuk mengenal pasti dan mengoptimumkan ligan yang berpotensi menghalang tapak pengikat VP40-RNA. Sejumlah 42 sebatian daripada kajian terdahulu telah disimulasi di tapak pengikat RNA menggunakan Autodock Vina. Sepuluh ligan terbaik telah dipilih sebagai templat pencarian persamaan dalam pangkalan data ZINC diikuti oleh penyaringan maya berasaskan struktur. Ciri-ciri ADME sebatian telah diramalkan secara komputasi menggunakan pelayan SwissADME. Keputusan kajian kami menunjukkan bahawa Q-96 (ZINC ID: 1338855) adalah sebatian terbaik dengan tenaga bebas pengikat -7.5 kcal/mol. Sebatian ini juga menunjukkan sifat ADME yang memuaskan dengan nilai kelipofilikan yang baik, kelarutan air secara sederhana dan penyerapan gastrousus yang tinggi. Selain itu, ligan ini tidak melanggar sebarang hukum persamaan drug juga tidak memberi sebarang amaran PAINS dan Brenk, menjustifikasikan ia mempunyai ciri-ciri sebagai drug. Oleh itu, adalah wajar untuk menjalankan kajian lanjutan yang lebih dalam mengenai struktur ini secara in silico, in vitro dan in vivo ke arah pencarian rawatan terhadap penyakit virus Ebola.

Kata kunci: ADME; cantuman molekul; protein matriks VP40; virus Ebola

 

RUJUKAN

Abazari, D., Moghtadaei, M., Behvarmanesh, A., Ghannadi, B., Aghaei, M., Behruznia, M. & Rigi, G. 2015. Molecular docking based screening of predicted potential inhibitors for VP40 from Ebola virus. Bioinformation 11: 243-247.

Adu-Gyamfi, E., Digman, M.A., Gratton, E. & Stahelin, R.V. 2012. Investigation of Ebola VP40 assembly and oligomerization in live cells using number and brightness analysis. Biophys. J. 102: 2517-2525.

Adu-Gyamfi, E., Johnson, K.A., Fraser, M.E., Scott, J.L., Soni, S.P., Jones, K.R., Digman, M.A., Gratton, E., Tessier, C.R. & Stahelin, R.V. 2015. Host cell plasma membrane phosphatidylserine regulates the assembly and budding of Ebola virus. J. Virol. 89: 9440-9453.

Akers, M.J. 2002. Excipient-drug interactions in parenteral formulations. J. Pharm. Sci. 91: 2283-2300.

Arnott, J.A. & Planey, S.L. 2012. The influence of lipophilicity in drug discovery and design. Expert Opin. Drug Discov. 7: 909-921.

Baell, J.B. & Holloway, G.A. 2010. New substructure filters for removal of pan assay interference compounds (PAINS) from screening libraries and for their exclusion in bioassays. J. Med. Chem. 53: 2719-2740.

Booth, T.F., Rabb, M.J. & Beniac, D.R. 2013. How do filovirus filaments bend without breaking? Trends Microbiol. 21: 583-593.

Bornholdt, Z.A., Noda, T., Abelson, D.M., Halfmann, P., Wood, M.R., Kawaoka, Y. & Saphire, E.O. 2013. Structural rearrangement of Ebola virus VP40 begets multiple functions in the virus life cycle. Cell 154: 763-774.

Brenk, R., Schipani, A., James, D., Krasowski, A., Gilbert, I.H., Frearson, J. & Wyatt, P.G. 2008. Lessons learnt from assembling screening libraries for drug discovery for neglected diseases. ChemMedChem. 3: 435-444.

Castro-Alvarez, A., Costa, A.M. & Vilarrasa, J. 2017. The performance of several docking programs at reproducing protein-macrolide-like crystal structures. Molecules 22: 1-14.

Clark, D.E. 2011. What has polar surface area ever done for drug discovery? Future Med. Chem. 3: 469-484.

Daina, A., Michielin, O. & Zoete, V. 2017. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci. Rep. 7: 42717.

Del Vecchio, K., Frick, C.T., Gc, J.B., Oda, S., Gerstman, B.S., Saphire, E.O., Chapagain, P.P. & Stahelin, R.V. 2018. A cationic, C-terminal patch and structural rearrangements in Ebola virus matrix VP40 protein control its interactions with phosphatidyserine. J. Biol. Chem. 293: 3335-3349.

Egan, W.J., Merz, K.M. & Baldwin, J.J. 2000. Prediction of drug absorption using multivariate statistics. J. Med. Chem. 43: 3867-3877.

Fabozzi, G., Nabel, C.S., Dolan, M.A. & Sullivan, N.J. 2011. Ebola virus proteins suppress the effects of small interfering RNA by direct interaction with the mammalian RNA interference pathway. J. Virol. 85: 2512-2523.

Feldmann, H. & Geisbert, T.W. 2011. Ebola haemorrhagic fever. Lancet. 377: 849-862.

Gc, J.B., Gerstman, B.S. & Chapagain, P.P. 2017. Membrane association and localization dynamics of the Ebola virus matrix protein VP40. Biochim. Biophys. Acta - Biomembr. 1859: 2012-2020.

Ghose, A.K., Viswanadhan, V.N. & Wendoloski, J.J. 1999. A knowledge-based approach in designing combinatorial or medicinal chemistry libraries for drug discovery. 1. A qualitative and quantitative characterization of known drug databases. J. Comb. Chem. 1: 55-68.

Gleeson, M.P. 2008. Generation of a set of simple, interpretable ADMET rules of thumb. J. Med. Chem. 51: 817-834.

Gomis-Rüth, F.X., Dessen, A., Timmins, J., Bracher, A., Kolesnikowa, L., Becker, S., Klenk, H.D. & Weissenhorn, W. 2003. The matrix protein VP40 from Ebola virus octamerizes into pore-like structures with specific RNA binding properties. Structure 11: 423-433.

Gonzalez, J.P., Wauquier, N. & Vincent, T. 2018. Revisiting Ebola, a quiet river in the heart of Africa. Med. Sante Trop. 28: 12-17.

Gupta, U., Agashe, H.B., Asthana, A. & Jain, N.K. 2006. Dendrimers: Novel polymeric nanoarchitectures for solubility enhancement. Biomacromolecules 7: 649-658.

Hoenen, T., Volchkov, V., Kolesnikova, L., Mittler, E., Timmins, J., Ottmann, M., Reynard, O., Becker, S. & Weissenhorn, W. 2005. VP40 octamers are essential for Ebola virus replication. J. Virol. 79: 1898-1905.

Jasenosky, L.D., Neumann, G., Lukashevich, I. & Kawaoka, Y. 2001. Ebola virus VP40-induced particle formation and association with the lipid bilayer. J. Virol. 75: 5205-5214.

Johnson, K.A., Taghon, G.J.F., Scott, J.L. & Stahelin, R.V. 2016. The Ebola virus matrix protein, VP40, requires phosphatidylinositol 4,5-bisphosphate (PI(4,5)P2) for extensive oligomerization at the plasma membrane and viral egress. Sci. Rep. 6: 19125.

Karthick, V., Nagasundaram, N., Doss, C.G.P., Chakraborty, C., Siva, R., Lu, A., Zhang, G. & Zhu, H. 2016. Virtual screening of the inhibitors targeting at the viral protein 40 of Ebola virus. Infect. Dis. Poverty 5: 12. Doi: 10.1186/s40249-016-0105-1.

Li, H., Leung, K.S., Wong, M.H. & Ballester, P.J. 2016. USR-VS: A web server for large-scale prospective virtual screening using ultrafast shape recognition techniques. Nucleic Acids Res. 44: W436-W441.

Lipinski, C. 2002. Poor aqueous solubility - An industry wide problem in drug discovery. Am. Pharm. Rev. 5: 82-85.

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. Adv. Drug Deliv. Rev. 46: 3-26.

M Alam El-Din, H., A Loutfy, S., Fathy, N., H Elberry, M., M Mayla, A., Kassem, S. & Naqvi, A. 2016. Molecular docking based screening of compounds against VP40 from Ebola virus. Bioinformation 12: 192-196.

Martin, B., Canard, B. & Decroly, E. 2017. Filovirus proteins for antiviral drug discovery: Structure/function bases of the replication cycle. Antiviral Res. 141: 48-61.

Martin, B., Hoenen, T., Canard, B. & Decroly, E. 2016. Filovirus proteins for antiviral drug discovery: A structure/function analysis of surface glycoproteins and virus entry. Antiviral Res. 135: 1-14.

Mirza, M.U. & Ikram, N. 2016. Integrated computational approach for virtual hit identification against Ebola viral proteins VP35 and VP40. Int. J. Mol. Sci. 17(11): 1748.

Muegge, I., Heald, S.L. & Brittelli, D. 2001. Simple selection criteria for drug-like chemical matter. J. Med. Chem. 44: 1841-1846.

Olejnik, J., Ryabchikova, E., Corley, R.B. & Mühlberger, E. 2011. Intracellular events and cell fate in filovirus infection. Viruses 3: 1501-1531.

Raj, U. & Varadwaj, P.K. 2016. Flavonoids as multi-target inhibitors for proteins associated with Ebola virus: In silico discovery using virtual screening and molecular docking studies. Interdiscip. Sci. Comput. Life Sci. 8: 132-141.

Ruigrok, R.W., Schoehn, G., Dessen, A., Forest, E., Volchkov, V., Dolnik, O., Klenk, H.D. & Weissenhorn, W. 2000. Structural characterization and membrane binding properties of the matrix protein VP40 of Ebola virus. J. Mol. Biol. 300: 103-112.

Schreyer, A.M. & Blundell, T. 2012. USRCAT: Real-time ultrafast shape recognition with pharmacophoric constraints. J. Cheminform. 4: 27.

Serajuddin, A.T.M. 2007. Salt formation to improve drug solubility. Adv. Drug Deliv. Rev. 59: 603-616.

Setlur, A.S., Naik, S.Y. & Skariyachan, S. 2017. Herbal lead as ideal bioactive compounds against probable drug targets of Ebola virus in comparison with known chemical analogue: A computational drug discovery perspective. Interdiscip. Sci. Comput. Life Sci. 9: 254-277.

Shah, R., Panda, P.K., Patel, P., Mumbai, N., Farm, A. & Road, G.D. 2015. Pharmacophore based virtual screening and molecular docking studies of inherited compounds against Ebola virus receptop proteins. World J. Pharm. Pharm. Sci. 4: 1268-1282.

Strickley, R.G. 2004. Solubilizing excipients in oral and injectable formulations. Pharm. Res. 21: 201-230.

Tamilvanan, T. & Hopper, W. 2013. High-throughput virtual screening and docking studies of matrix protein VP40 of Ebola virus. Bioinformation 9: 286-292.

Taylor, R.D., Maccoss, M. & Lawson, A.D.G. 2014. Rings in drugs. J. Med. Chem. 57: 5845-5859.

Trott, O. & Olson, A.J. 2009. Software news and update AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem. 31: 455-461.

Van de Waterbeemd, H., Smith, D.A., Beaumont, K. & Walker, D.K. 2001. Property-based design: Optimization of drug absorption and pharmacokinetics. J. Med. Chem. 44: 1313-1333.

Veber, D.F., Johnson, S.R., Cheng, H., Smith, B.R., Ward, K.W. & Kopple, K.D. 2002. Molecular properties that influence the oral bioavailability of drug candidates. J. Med. Chem. 45: 2615-2623.

Vyas, A., Saraf, Shailendra. & Saraf, Swarnlata. 2008. Cyclodextrin based novel drug delivery systems. J. Incl. Phenom. Macrocycl. Chem. 62: 23-42.

WHO | Ebola Situation Reports: Democratic Republic of the Congo, 2019.

WHO | Ebola Virus Disease 2017.

Yang, J., Roy, A. & Zhang, Y. 2013a. Protein-ligand binding site recognition using complementary binding-specific substructure comparison and sequence profile alignment. Bioinformatics 29: 2588-2595.

Yang, J., Roy, A. & Zhang, Y. 2013b. BioLiP: A semi-manually curated database for biologically relevant ligand-protein interactions. Nucleic Acids Res. 41: 1096-1103.

Yuan, S. 2015. Possible FDA-approved drugs to treat Ebola virus infection. Infect. Dis. Poverty 4: 23.

*Pengarang untuk surat-menyurat; email: kbariyyah@iium.edu.my

 

 

 

 

sebelumnya