In silico study of the interactions of Pilocarpus microphyllus imidazolic alkaloids with the main protease (M^pro) of SARS-CoV-2

References

• Huynh T, Wang H, Luan B. In silico exploration of the molecular mechanism of clinically oriented drugs for possibly inhibiting SARS-CoV-2’s main protease. J Phys Chem Lett. 2020;11:4413–4420. doi:10.1021/acs.jpclett.0c00994
   PubMed Web of Science ®Google Scholar
• Zhu N, Zhang D, Wang W, et al. A novel coronavirus from patients with pneumonia in China, 2019. New Engl J Med. 2020;382:727–733. doi:10.1056/NEJMoa2001017
   PubMed Web of Science ®Google Scholar
• Lancet T. Global coalition to accelerate COVID-19 clinical research in resource-limited settings. J Lancet Healthy Longevity. 2020;395:1322–1325. doi:10.1016/S0140-6736(20)30798-4.
   Google Scholar
• OPAS/OMS Brazil. (2020). Fact sheet - COVID-19 (disease caused by the new coronavirus). Brasilia, DF, Brazil. https://www.paho.org/bra/ (accessed 30.11.2020).
   Google Scholar
• Zhang L, Lin D, Sun X, et al. Crystal structure of SARS-CoV-2 main protease provides a basis for design of improved a-ketoamide inhibitors. Science. 2020;368:409–412. doi:10.1126/science.abb3405
   PubMed Web of Science ®Google Scholar
• Anand K, Palm GJ, Mesters JR, et al. Structure of coronavirus main proteinase reveals combination of a chymotrypsin fold with an extra α-helical domain. EMBO J. 2002;21:3213–3224. doi:10.1093/emboj/cdf327
   PubMed Web of Science ®Google Scholar
• Yang H, Yang M, Ding Y, et al. The crystal structures of severe acute respiratory syndrome vírus main protease and its complex with an inhibitor. Proc Nat Acad Sci. 2003;100:13190–13195.doi:10.1073/pnas.1835675100
   PubMed Web of Science ®Google Scholar
• Jin Z, Du X, Xu Y, et al. Structure of Mpro from SARS-CoV-2 and discovery of its inhibitors. Nature. 2020;582:289–293. doi:10.1038/s41586-020-2223-y
   PubMed Web of Science ®Google Scholar
• Yang H, Xie W, Xue X, et al. Design of wide-spectrum inhibitors targeting coronavirus main proteases. PLoS Biol. 2005;3:e324. doi:10.1371/journal.pbio.0030324
   PubMed Web of Science ®Google Scholar
• Wang F, Chen C, Tan W, et al. Structure of main protease from human coronavirus NL63: insights for amplo espectro anti-coronavirus drug design. Sci Rep. 2016;6:22677. doi:10.1038/srep22677
   PubMed Web of Science ®Google Scholar
• Aanouz I, Belhassan A, El-Khatabi K, et al. Moroccan medicinal plants as inhibitors against SARS-CoV-2 main protease: computational investigations. J Biomol Struct Dyn. 2020. doi:10.1080/07391102.2020.1758790.
   PubMedGoogle Scholar
• Ferreira ET, Santos ES, Monteiro JS, et al. The use of medicinal and phytotherapy plants: An integrational review on the nurses performance. Braz J Health Rev. 2019;2:1511–1523. https://www.brazilianjournals.com/index.php/BJHR/article/view/1383 (accessed 20.04.2020).
   Google Scholar
• Lima DF, Lima LI, Rocha JA, et al. Seasonal change in main alkaloids of jaborandi (Pilocarpus microphyllus Stapf ex Wardleworth), an economically important species from the Brazilian flora. PLoS ONE. 2017;12:e0170281. doi:10.1371/journal.pone.0170281.
   PubMed Web of Science ®Google Scholar
• Duke JA. Handbook of medicinal herbs. 2nd ed New York: CRC Press; 2002; 896 p.
   Google Scholar
• Devi R, Singh V, Chaudhary AK. Antidiabetic activity of pilocarpus microphyllus extract on streptozotocin-induced diabetic mice. Int J Pharm Sci Rev Res. 2010;5:87–92. https://www.semanticscholar.org/paper/ANTIDIABETIC-ACTIVITY-OF-PILOCARPUS-MICROPHYLLUS-ON-Devi-Singh/9f0c6d63d0de9a46337316684b215293a7e8de7c#citing-papers (accessed 25.04.2020).
   Google Scholar
• Agban Y, Lian J, Prabakar S, et al. Nanoparticle cross-linked collagen shields for sustained delivery of pilocarpine hydrochloride. Int J Pharm. 2016;501:96–101. doi:10.1016/j.ijpharm.2016.01.069
   PubMed Web of Science ®Google Scholar
• Gil-Montoya JA, Silvestre FJ, Barrios R, et al. Treatment of xerostomia and hyposalivation in the elderly: a systematic review. Oral Medicine Oral Pathology and Oral Surgery. 2016;21:e355–e366. doi:10.4317/medoral.20969.
   Google Scholar
• Guimarães MA, Campelo YD, Véras LM, et al. Nanopharmaceutical approach of epiisopiloturine alkaloid carried in liposome system: preparation and in vitro schistosomicidal activity. J Nanosci Nanotechnol. 2014;14:4519–4528. doi:10.1166/jnn.2014.8248
   PubMed Web of Science ®Google Scholar
• Guimarães MA, de Oliveira RN, Véras LMC, et al. Anthelmintic activity in vivo of epiisopiloturine against juvenile and adult worms of Schistosoma mansoni. PLoS Negl Trop Dis. 2015;9:e0003656. doi:10.1371/journal.pntd.0003656
   PubMed Web of Science ®Google Scholar
• Rocha JA, Rego NCS, Carvalho BTS, et al. Computational quantum chemistry, molecular docking, and ADMET predictions of imidazole alkaloids of Pilocarpus microphyllus with schistosomicidal properties. PLoS ONE. 2018;13:e0198476. doi:10.1371/journal.pone.0198476.
   PubMed Web of Science ®Google Scholar
• Silva VG, Silva RO, Damasceno SRB, et al. Anti-inflammatory and antinociceptive activity of epiisopiloturine, an imidazole alkaloid isolated from Pilocarpus microphyllus. J Nat Prod. 2013;76:1071–1077. doi:10.1021/np400099m
   PubMed Web of Science ®Google Scholar
• Nicolau LAD, Carvalho NS, Pacífico DM, et al. Epiisopiloturine hydrochloride, an imidazole alkaloid isolated from Pilocarpus microphyllus leaves, protects against naproxen-induced gastrointestinal damage in rats. Biomed Pharmacother. 2017;87:188–195. doi:10.1016/j.biopha.2016.12.101
   PubMed Web of Science ®Google Scholar
• Rocha JA, Andrade IM, Véras LMC, et al. Anthelmintic, antibacterial and cytotoxicity activity of imidazole alkaloids from Pilocarpus microphyllus leaves. Phytother Res. 2017;31:624–630. doi:10.1002/ptr.5771
   PubMed Web of Science ®Google Scholar
• Lima Neto JX. (2019). Estudo em complexos fármaco-receptor utilizando bioquímica quântica [Quantum biochemistry study in drug-receptor complexes]. 140f. Thesis (Doctorate in Biochemistry). Federal University of Rio Grande do Norte, Natal, Brazil. Portuguese. https://repositorio.ufrn.br/jspui/handle/123456789/26645 (accessed 02.05.2020).
   Google Scholar
• Das S, Sarmah S, Lyndem S, et al. An investigation into the identification of potential inhibitors of SARS-CoV-2 main protease using molecular docking study. J Biomol Struct Dyn. 2020; doi:10.1080/07391102.2020.1763201.
   Google Scholar
• Kadan, R. U., Roy, N. Recent Trends in drug likeness prediction: a comprehensive review of In silico methods. Indian J Pharm Sci. 2007;69: 609–615. doi:10.4103/0250-474X.38464
   Google Scholar
• Berman HM, Westbrook J, Feng Z, et al. The protein data Bank. Nucleic Acids Res. 2000;28:235–242. doi:10.1093/nar/28.1.235
   PubMed Web of Science ®Google Scholar
• Santos AP, Moreno PRH. Pilocarpus spp.: a survey of its chemical constituents and biological activities. Braz J Pharm Sci. 2004;40:115–137. doi:10.1590/S1516-93322004000200002.
   Web of Science ®Google Scholar
• Abreu IN, Mazzafera P, Eberlin MN, et al. Characterization of the variation in the imidazole alkaloid profile of Pilocarpus microphyllus in different seasons and parts of the plant by electrospray ionization mass spectrometry fingerprinting and identification of novel alkaloids by tandem mass spectrometry. Rapid Commun Mass Spectrom. 2007;21:1205–1213. doi:10.1002/rcm.2942
   PubMed Web of Science ®Google Scholar
• Véras LMC, Cunha VRR, Lima FCDA, et al. Industrial scale Isolation, structural and spectroscopic characterization of epiisopiloturine from pilocarpus microphyllus Stapf leaves: a promising alkaloid against schistosomiasis. PLoS ONE. 2013;8:e66702. doi:10.1371/journal.pone.0066702
   PubMed Web of Science ®Google Scholar
• Dennington R, Keith TA, Millam JM. (2016). GaussView, version 6, Semichem Inc., Shawnee Mission, KS. https://gaussian.com/gaussview6/ (accessed 03.05.2020).
   Google Scholar
• Costa RA, Junior ESA, Lopes GBP, et al. Structural, vibrational, UV–vis, quantum-chemical properties, molecular docking and anti-cancer activity study of annomontine and N-hydroxyannomontine β-carboline alkaloids: a combined experimental and DFT approach. J Mol Struct. 2018;1171:682–695. doi:10.1016/j.molstruc.2018.06.054
   Web of Science ®Google Scholar
• Costa RA, Oliveira KMT, Nunomura RCS, et al. Quantum chemical properties investigation and molecular docking analysis with DNA topoisomerase II of β-carboline indole alkaloids from Simaba guianensis: a combined experimental and theoretical DFT study. Struct Chem. 2018;29:299–314. doi:10.1007/s11224-017-1029-5
   Web of Science ®Google Scholar
• Frisch MJ, Trucks GW, Schlegel HB, et al. Gaussian09, Revision C.01. Wallingford (CT): Gaussian, Inc.; 2010; https://gaussian.com (accessed 05.05.2020).
   Google Scholar
• Lee C, Yang W, Parr RG. Development of the colle-salvetti correlation-energy formula into a functional of the electron-density. Phys Rev B. 1988;37:785–789. doi:10.1103/PhysRevB.37.785
   PubMed Web of Science ®Google Scholar
• Becke AD. Density-functional thermochemistry. III. The role of exact exchange. J Chem Phys. 1993;98:5648–5652. doi:10.1063/1.464913
   Web of Science ®Google Scholar
• Mclean AD, Chandler GS. Contracted Gaussian-basis sets for molecular calculations. 1. second row atoms, Z = 11–18. J Chem Phys. 1980;72:5639–5648. doi:10.1063/1.438980
   Web of Science ®Google Scholar
• Krishnan R, Binkey JS, Seeger R, et al. Self-consistent molecular orbital methods. XX. Basis set for correlated wave-functions. J Chem Phys. 1980;72:650–654. doi:10.1063/1.438955
   Web of Science ®Google Scholar
• Janak JF. Proof that in density-functional Theory. Phys Rev B. 1978;18:7165–7168. doi:10.1103/PhysRevB.18.7165
   Web of Science ®Google Scholar
• Perdew JP, Parr RG, Levy M, et al. Density-functional theory for fractional particle number: derivative discontinuities of the energy. Phys Rev Lett. 1982;49:1691–1694. doi:10.1103/PhysRevLett.49.1691
   Web of Science ®Google Scholar
• Parr RG, Chattaraj PK. Principle of maximum hardness. J Am Chem Soc. 1991;113:1854–1855. doi:10.1021/ja00005a072
   Web of Science ®Google Scholar
• Parr RG, Szentpály LV, Liu S. Electrophilicity index. J Am Chem Soc. 1999;121:1922–1924. doi:10.1021/ja983494x
   Web of Science ®Google Scholar
• Pettersen EF, Goddard TD, Huang CC, et al. UCSF Chimera–a visualization system for exploratory research and analysis. J Comput Chem. 2004;25:1605–1612. doi:10.1002/jcc.20084
   PubMed Web of Science ®Google Scholar
• Goodsell DS, Morris G, Olson AJ. Automated docking of flexible ligands: applications of AutoDock. J Mol Recogn. 1996;9:1–5. doi:10.1002/(SICI)1099-1352(199601)9:1<1::AID-JMR241>3.0.CO;2-6
   PubMed Web of Science ®Google Scholar
• Huey R, Morris GM, Forli S. (2012). Using AutoDock4 and AutoDock Vina with AutoDockTools: A tutorial. The Scripps Research Institute. https://www.yumpu.com/en/document/view/52169976/using-autodock-4-and-autodock-vina-with-autodocktools-a-tutorial (accessed 08.05.2020).
   Google Scholar
• 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. 2010;31:455–461. doi:10.1002/jcc.21334.
   PubMed Web of Science ®Google Scholar
• Ravindranath PA, Forli S, Goodsell DS, et al. AutoDockFR: advances in protein-ligand docking with explicitly specified binding site flexibility. PLoS Comput Biol. 2015;11:e1004586. doi:10.1371/journal.pcbi.1004586
   PubMed Web of Science ®Google Scholar
• Morris GM, Goodsell DS, Halliday RS, et al. Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function. J Comput Chem. 1998;19:1639–1662. doi:10.1002/(SICI)1096-987X(19981115)19:14<1639::AID-JCC10>3.0.CO;2-B
   Web of Science ®Google Scholar
• Barros RO, Junior FLCC, Pereira JWS, et al. Interaction of drugs candidates with various SARS-CoV-2 receptors: an in silico study to combat COVID-19. J Proteome Res. 2020; doi:10.1021/acs.jproteome.0c00327.
   PubMed Web of Science ®Google Scholar
• Biovia DS. (2020). Discovery studio visualizer, San Diego: Dassault Systèmes. https://www.3dsbiovia.com/products/collaborative-science/biovia-discovery-studio/visualization.html (accessed 15.05.2020).
   Google Scholar
• Breneman CM, Wiberg KB. Determining atom-centered monopoles from molecular electrostatic potentials. The need for high sampling density in formamide conformational analysis. J Comput Chem. 1990;11:361–373. doi:10.1002/jcc.540110311
   Web of Science ®Google Scholar
• Chirlian LE, Francl MM. Atomic charges derived from electrostatic potentials: a detailed study. J Comput Chem. 1987;8:894–905. doi:10.1002/jcc.540080616
   Web of Science ®Google Scholar
• Mei Y, Simmonett AC, Pickard FC, et al. Numerical study on the partitioning of the molecular polarizability into fluctuating charge and induced atomic dipole contributions. J Phys Chem A. 2015;119:5865–5882. doi:10.1021/acs.jpca.5b03159
   PubMed Web of Science ®Google Scholar
• Gordon JC, Myers JB, Folta T, et al. Hþþ: a server for estimating pKas and adding missing hydrogens to macromolecules. Nucleic Acids Res. 2005;33:w368–w371. doi:10.1093/nar/gki464
   PubMed Web of Science ®Google Scholar
• Abraham MJ, Van Der Spoel D, Lindahl E, et al. (2018). The GROMACS development team. GROMACS user manual version 2018.1. www.gromacs.org (accessed 20.05.2020).
   Google Scholar
• Oostenbrink C, Villa A, Mark AE, et al. A biomolecular force field based on the free enthalpy of hydration and solvation: the GROMOS force-field parameter sets 53A5 and 53A6. J Comput Chem. 2004;25:1656–1676. doi:10.1002/jcc.20090
   PubMed Web of Science ®Google Scholar
• Arcanjo DDR, Vasconcelos AG, Nascimento LA, et al. Structure-function studies of BPP-BrachyNH 2 and synthetic analogues thereof with Angiotensin I-converting enzyme. Eur J Med Chem. 2017;139:401–411. doi:10.1016/j.ejmech.2017.08.019
   PubMed Web of Science ®Google Scholar
• Van der Spoel D, Van Maaren PJ, Berendsen HJC. A systematic study of water models for molecular simulation: derivation of water models optimized for use with a reaction field. J Chem Phys. 1998;108:10220–10230. doi:10.1063/1.476482
   Web of Science ®Google Scholar
• Ramos RM, Perez JM, Baptista LA, et al. Interaction of wild type, G68R and L125M isoforms of the arylamineN-acetyltransferase from mycobacterium tuberculosis with isoniazid: a computational study on a new possible mechanism of resistance. J Mol Model. 2012;18:4013–4024. doi:10.1007/s00894-012-1383-6
   PubMed Web of Science ®Google Scholar
• Nosé S, Klein ML. Constant pressure molecular dynamics for molecular systems. Mol Phys. 1983;50:1055–1076. doi:10.1080/00268978300102851
   Web of Science ®Google Scholar
• Parrinello M, Rahman A. Polymorphic transitions in single crystals: a new molecular dynamics method. J Appl Phys. 1981;52:7182–7190. doi:10.1063/1.328693
   Web of Science ®Google Scholar
• Hess B, Bekker H, Berendsen HJC, et al. LINCS: a linear constraint solver for molecular simulations. J Comput Chem. 1997;18:1463–1472. doi:10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H.
   Web of Science ®Google Scholar
• Darden T, York D, Pedersen L. Particle mesh Ewald: an N, log(N) method for Ewald sums in large systems. J Appl Phys. 1993;98:10089–10092. doi:10.1063/1.464397.
   Google Scholar
• Lemkul J. From proteins to perturbed hamiltonians: a suite of tutorials for the GROMACS-2018 molecular simulation package [Article v1.0]. Living J Comput Mol Sci. 2019;1:1–53. doi:10.33011/livecoms.1.1.5068
   Google Scholar
• Verli H. Bioinformática da biologia à flexibilidade molecular [Bioinformatics from biology to molecular flexibility]. 1st ed São Paulo: SBBq; 2014; 282 p. Portuguese. https://www.ufrgs.br/bioinfo/ebook/ (accessed 23.12.2020).
   Google Scholar
• Lagorce D, Bouslama L, Becot J, et al. FAF-Drugs4: free ADME-tox filtering computations for chemical biology and early stages drug discovery. Bioinformatics. 2017;33:3658–3660. doi:10.1093/bioinformatics/btx491
   PubMed Web of Science ®Google Scholar
• Lee SK, Chang GS, Lee IH, et al. The PreADME: pc-based program for batch prediction of adme properties. EuroQSAR. 2004;9:5–10. https://scholar.google.com/scholar?cluster=9485303528805910143&hl=pt-BR&as_sdt=2005&sciodt=0,5 (accessed 10.06.2020).
   Google Scholar
• Daiana A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep. 2017;7:1–13. doi:10.1038/srep42717
   PubMed Web of Science ®Google Scholar
• Filimonov DA, Lagunin AA, Gloriozova TA, et al. Prediction of the biological activity spectra of organic compounds using the PASS online web resource. Chem Heterocycl Compd (NY). 2014;50:444–457. doi:10.1007/s10593-014-1496-1
   Web of Science ®Google Scholar
• Kramer C, Ting A, Zheng H, et al. Learning medicinal chemistry absorption, distribution, metabolism, excretion, and toxicity (ADMET) rules from cross-company matched molecular Pairs analysis (MMPA). J Med Chem. 2018;61:3277–3292. doi:10.1021/acs.jmedchem.7b00935
   PubMed Web of Science ®Google Scholar
• Sá ERA, Nascimento LA, Lima FCA. Termodinâmica: Uma Proposta de Ensino a partir da Química Computacional [Thermodynamics: a teaching proposal based on computational chemistry]. Virtual J Chem. 2020;12:795–808. Portuguese. doi:10.21577/1984-6835.20200062.
   Google Scholar
• Honório KM, da Silva ABF. An AM1 study on the electron-donating and electron-accepting character of biomolecules. Int J Quantum Chem. 2003;95:126–132. doi:10.1002/qua.10661
   Web of Science ®Google Scholar
• Da Silva RR, Ramalho TC, Santos JM, et al. On the limits of highest-occupied molecular orbital driven reactions: the frontier effective-for-reaction molecular orbital concept. J Phys Chem. 2006;110:1031–1040. doi:10.1021/jp054434y
   PubMed Web of Science ®Google Scholar
• Maltarollo VG, Silva DC, Honório KM. Advanced QSAR studies on PPARδ ligands related to metabolic diseases. J Braz Chem Soc. 2012;23:85–95. doi:10.1590/S0103-50532012000100013
   Web of Science ®Google Scholar
• Pang X, Zhou L, Zhang M, et al. Two rules on the protein-ligand interaction. Open Conf Proc J. 2012;3:70–80. doi:10.2174/2210289201203010070
   Google Scholar
• Costa AN, Sá ERA, Bezerra RDS, et al. Constituents of buriti oil (Mauritia flexuosa L.) like inhibitors of the SARS-coronavirus main peptidase: an investigation by docking and molecular dynamics. J Biomol Struct Dyn. 2020. doi:10.1080/07391102.2020.1778538.
   Web of Science ®Google Scholar
• Arnott JA, Planey SL. The influence of lipophilicity in drug discovery and design. Expert Opin Drug Discov. 2012;7:863–875. doi:10.1517/17460441.2012.714363
   PubMed Web of Science ®Google Scholar
• Storpirtis S, Gai MN, Campos DR, et al. Farmacocinética básica e aplicada [Basic and applied pharmacokinetics]. Rio de Janeiro: Guanabara Koogan; 2011; 240 p. Portuguese.
   Google Scholar
• Gurunga AB, Bhattacharjeea A, Ali MA. Exploring the physicochemical profile and the binding patterns of selected novel anticancer himalayan plant derived active compounds with macromolecular targets. Inf Med Unlocked. 2016;5:1–14. doi:10.1016/j.imu.2016.09.004
   Google Scholar
• Ertl P, Rohde B, Selzer P. Fast calculation of molecular polar surface area as a sum of fragment-based contributions and its application to the prediction of drug Transport properties. J Med Chem. 2000;43:3714–3717. doi:10.1021/jm000942e
   PubMed Web of Science ®Google Scholar
• Lipinski CA, Lombardo F, Dominy BW, et al. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev. 2001;46:3–26. doi:10.1016/S0169-409X(00)00129-0
   PubMed Web of Science ®Google Scholar
• Lagorce D, Douguet D, Miteva MA, et al. Computational analysis of calculated physicochemical and ADMET properties of protein-protein interaction inhibitors. Sci Rep. 2017;7:46277. doi:10.1038/srep46277
   PubMed Web of Science ®Google Scholar
• Bickerton GR, Paolini GV, Besnard J, et al. Quantifying the chemical beauty of drugs. Nat Chem. 2012;4:90–98. doi:10.1038/nchem.1243
   PubMed Web of Science ®Google Scholar
• Brown RD, Hassan M, Waldman M. Combinatorial library design for diversity, cost efficiency, and drug-like character. J Mol Graphics Model. 2000;18:427–437. doi:10.1016/S1093-3263(00)00072-3
   PubMed Web of Science ®Google Scholar
• Kobayashi M, Sada N, Sugawara M, et al. Development of a new system for prediction of drug absorption that takes into account drug dissolution and pH change in the gastro-intestinal tract. Int J Pharm. 2001;221:87–94. doi:10.1016/S0378-5173(01)00663-9
   PubMed Web of Science ®Google Scholar
• Irvine JD, Takahashi L, Lockhart K, et al. MDCK (Madin-Darby Canine Kidney) cells: a tool for membrane permeability screening. J Pharm Sci. 1999;88:28–33. doi:10.1021/js9803205
   PubMed Web of Science ®Google Scholar
• Souza J, Freitas ZMF, Storpirtis S. In vitro models for the determination of drug absorption and a prediction of dissolution/absorption relationships. Braz J Pharm Sci. 2007;43:515–527. doi:10.1590/S1516-93322007000400004.
   Google Scholar
• Sripriya N, Ranjith Kumar M, Ashwin Karthick N, et al. In silico evaluation of multispecies toxicity of natural compounds. Drug Chem Toxicol. 2019;21:1–7. doi:10.1080/01480545.2019.1614023.
   Google Scholar
• Costa LF. (2012). Rinovírus humano em infecções respiratórias agudas em crianças menores de cinco anos de idade: fatores envolvidos no agravamento da doença [Human rhinovirus in acute respiratory infections in children under five years of age: factors involved in the worsening of the disease]. 71f. Thesis (Doctorate in Biological Sciences) - Federal University of Uberlândia, Uberlândia, Brazil. Portuguese. https://repositorio.ufu.br/handle/123456789/16573 (accessed 08.08.2020).
   Google Scholar
• Kuskoski EM, Asuero AG, Troncoso AM, et al. Application of several chemical methods to determine antioxidant activity in fruit pulp. Food Sci Tech. 2005;25:726–732. doi:10.1590/S0101-20612005000400016.
   Google Scholar