Isolation, characterization and in silico study of propenamide alkaloids from Hymenoepmecis bicolor poison against active μ-opioid receptor

References

• Adams, R. P. (2007). Identification of essential oil components by gas chromatography/mass spectrometry. Journal of the American Society for Mass Spectrometry, 8(6), 1–698.
   Google Scholar
• Ahmadi, M., Jahed Motlagh, M., Rahmani, A. T., Zolfagharzadeh, M. M., Shariatpanahi, P., Chermack, T. J., Coons, L. M., Cotter, J., Eyiah-Donkor, E., Poti, V., Derbyshire, J., Dolan, T. E., Fuller, T., Kishita, Y., McLellan, B. C., Giurco, D., Aoki, K., Yoshizawa, G., Handoh, I. C., … Bose, S. (2005). Chem3D 15.0 user guide. Macromolecules, 24(2), 1–61.
   Google Scholar
• Bai, Q., Tan, S., Xu, T., Liu, H., Huang, J., & Yao, X. (2021). MolAICal: A soft tool for 3D drug design of protein targets by artificial intelligence and classical algorithm. Briefings in Bioinformatics, 22(3), 1–12. https://doi.org/10.1093/bib/bbaa161
   PubMed Web of Science ®Google Scholar
• Baudequin, T., Agnes, C., & Tabrizian, M. (2021). A core-shell guanosine diphosphate crosslinked chitosan scaffold as a potential co-encapsulation platform. Carbohydrate Polymers, 256, 117499. https://doi.org/10.1016/j.carbpol.2020.117499
   PubMed Web of Science ®Google Scholar
• Berendsen, H. J. C., Postma, J. P. M., Van Gunsteren, W. F., Dinola, A., & Haak, J. R. (1984). Molecular dynamics with coupling to an external bath. The Journal of Chemical Physics, 81(8), 3684–3690. https://doi.org/10.1063/1.448118
   Web of Science ®Google Scholar
• Bickerton, G. R., Paolini, G. V., Besnard, J., Muresan, S., & Hopkins, A. L. (2012). Quantifying the chemical beauty of drugs. Nature Chemistry, 4(2), 90–98. https://doi.org/10.1038/nchem.1243
   PubMed Web of Science ®Google Scholar
• Bland, J. M., & Altman, D. G. (1995). Tukey multiple comparison test. British Medical Journal, 310, 170.
   PubMed Web of Science ®Google Scholar
• Boopathi, S., & Garduño-Juárez, R. (2022). Calcium inhibits penetration of Alzheimer’s Aβ1–42 monomers into the membrane. Proteins, 90(12), 2124–2143. https://doi.org/10.1002/prot.26403
   PubMed Web of Science ®Google Scholar
• Brown, T. (2014). ChemDraw. The Science Teacher, 81(2), 67.
   Google Scholar
• Brownstein, M. J. (1993). A brief history of opiates, opioid peptides, and opioid receptors. Proceedings of the National Academy of Sciences of the United States of America, 90(12), 5391–5393. https://doi.org/10.1073/pnas.90.12.5391
   PubMed Web of Science ®Google Scholar
• Cheatham, T. E., Miller, J. L., Fox, T., Darden, T. A., & Kollman, P. A. (1995). Molecular dynamics simulations on solvated biomolecular systems: The particle mesh ewald method leads to stable trajectories of DNA, RNA, and proteins. Journal of the American Chemical Society, 117(14), 4193–4194. (https://doi.org/10.1021/ja00119a045
   Web of Science ®Google Scholar
• Chen, E., Chuang, L.-S., Giri, M., Villaverde, N., Hsu, N.-Y., Sabic, K., Joshowitz, S., Gettler, K., Nayar, S., Chai, Z., Alter, I. L., Chasteau, C. C., Korie, U. M., Dzedzik, S., Thin, T. H., Jain, A., Moscati, A., Bongers, G., Duerr, R. H., … Cho, J. H. (2021). Inflamed ulcerative colitis regions associated with MRGPRX2-mediated mast cell degranulation and cell activation modules, defining a new therapeutic target. Gastroenterology, 160(5), 1709–1724. https://doi.org/10.1053/j.gastro.2020.12.076
   PubMed Web of Science ®Google Scholar
• Chen, F., Sun, H., Wang, J., Zhu, F., Liu, H., Wang, Z., Lei, T., Li, Y., & Hou, T. (2018). Assessing the performance of MM/PBSA and MM/GBSA methods. 8. Predicting binding free energies and poses of protein-RNA complexes. RNA (New York, N.Y.), 24(9), 1183–1194. https://doi.org/10.1261/rna.065896.118
   PubMed Web of Science ®Google Scholar
• Choi, S. K., Kalivretenos, A. G., Usherwood, P. N. R., & Nakanishi, K. (1995). Labeling studies of photolabile philanthotoxins with nicotinic acetylcholine receptors: Mode of interaction between toxin and receptor. Chemistry & Biology, 2(1), 23–32. https://doi.org/10.1016/1074-5521(95)90077-2
   PubMedGoogle Scholar
• Christopher, D. A., Mitchell, R. J., & Karron, J. D. (2020). Pollination intensity and paternity in flowering plants. Annals of Botany, 125(1), 1–9. https://doi.org/10.1093/aob/mcz159
   PubMed Web of Science ®Google Scholar
• Daina, A., Michielin, O., & Zoete, V. (2019). SwissTargetPrediction: Updated data and new features for efficient prediction of protein targets of small molecules. Nucleic Acids Research, 47(W1), W357–W364. https://doi.org/10.1093/nar/gkz382
   PubMed Web of Science ®Google Scholar
• DasGupta, D., Mandalaparthy, V., & Jayaram, B. (2017). A component analysis of the free energies of folding of 35 proteins: A consensus view on the thermodynamics of folding at the molecular level. Journal of Computational Chemistry, 38(32), 2791–2801. https://doi.org/10.1002/jcc.25072
   PubMed Web of Science ®Google Scholar
• DeLano, W. L. (2020). The PyMOL molecular graphics system, version 2.3. Schrödinger LLC, https://doi.org/10.1038/hr.2014.17
   Google Scholar
• Dikolayev, V., Tuganbekov, T., & Nikolaev, V. O. (2019). Visualizing cyclic adenosine monophosphate in cardiac microdomains involved in ion homeostasis. Frontiers in Physiology, 10, 1406–1408. https://doi.org/10.3389/fphys.2019.01406
   PubMed Web of Science ®Google Scholar
• Dollish, F. R., Fateley, W. G., & Bentley, F. F. (1991). Infrared and Raman spectra of common organic compounds—From the aldrich library of FT-IR spectra and the Dollish, Fateley and Bentley collection. In The handbook of infrared and Raman characteristic frequencies of organic molecules (pp. 423–454). , Ed. Elsevier. https://doi.org/10.1016/b978-0-08-057116-4.50025-0
   Google Scholar
• Field, M. J., Albe, M., Bret, C., Proust-De Martin, F., & Thomas, A. (2000). The dynamo library for molecular simulations using hybrid quantum mechanical and molecular mechanical potentials. Journal of Computational Chemistry, 21(12), 1088–1100. https://doi.org/10.1002/1096-987X(200009)21:12<1088::AID-JCC5>3.0.CO;2-8
   Web of Science ®Google Scholar
• Filmore, D. (2004). It’s a GPCR world. Journal of Modern Drug Discovery, 7(11), 24–27.
   Google Scholar
• Gao, K., Mu, C. L., Farzi, A., & Zhu, W. Y. (2020). Tryptophan Metabolism: A Link between the Gut Microbiota and Brain. Advances in Nutrition (Bethesda, Md.), 11(3), 709–723. https://doi.org/10.1093/advances/nmz127
   PubMed Web of Science ®Google Scholar
• Gauld, I. D., & Dubois, J. (2006). Phylogeny of the Polysphincta group of genera (Hymenoptera: Ichneumonidae; Pimplinae): A taxonomic revision of spider ectoparasitoids. Systematic Entomology, 31(3), 529–564. https://doi.org/10.1111/j.1365-3113.2006.00334.x
   Web of Science ®Google Scholar
• Genheden, S., & Ryde, U. (2015). The MM/PBSA and MM/GBSA methods to estimate ligand-binding affinities. Expert Opinion on Drug Discovery, 10(5), 449–461. ( https://doi.org/10.1517/17460441.2015.1032936
   PubMed Web of Science ®Google Scholar
• Genheden, S., & Ryde, U. L. F. (2010). How to obtain statistically converged MM/GBSA results. Journal of Computational Chemistry, 31(4), 837–846. https://doi.org/10.1002/jcc.21366
   PubMed Web of Science ®Google Scholar
• Gfeller, D., Michielin, O., & Zoete, V. (2013). Shaping the interaction landscape of bioactive molecules. Bioinformatics (Oxford, England), 29(23), 3073–3079. https://doi.org/10.1093/bioinformatics/btt540
   PubMed Web of Science ®Google Scholar
• Gleeson, M. P. (2008). Generation of a set of simple, interpretable ADMET rules of thumb. Journal of Medicinal Chemistry, 51(4), 817–834. https://doi.org/10.1021/jm701122q
   PubMed Web of Science ®Google Scholar
• Gohlke, H., & Case, D. A. (2004). Converging free energy estimates: MM-PB(GB) SA studies on the protein-protein complex Ras-Raf. Journal of Computational Chemistry, 25(2), 238–250. https://doi.org/10.1002/jcc.10379
   PubMed Web of Science ®Google Scholar
• Gohlke, H., Kiel, C., & Case, D. A. (2003). Insights into protein-protein binding by binding free energy calculation and free energy decomposition for the Ras-Raf and Ras-RalGDS complexes. Journal of Molecular Biology, 330(4), 891–913. https://doi.org/10.1016/S0022-2836(03)00610-7
   PubMed Web of Science ®Google Scholar
• Gonzaga, M. O., Sobczak, J. F., Penteado-Dias, A. M., & Eberhard, W. G. (2010). Modification of Nephila clavipes (Araneae Nephilidae) webs induced by the parasitoids Hymenoepimecis bicolor and H. robertsae (Hymenoptera Ichneumonidae). Ethology Ecology & Evolution, 22(2), 151–165. https://doi.org/10.1080/03949371003707836
   Web of Science ®Google Scholar
• Gülçin, I. (2009). Antioxidant activity of l-adrenaline: A structure-activity insight. Chemico-Biological Interactions, 179(2–3), 71–80. https://doi.org/10.1016/j.cbi.2008.09.023
   PubMed Web of Science ®Google Scholar
• Halgren, T. A. (1996). Merck molecular force field. I. Basis, form, scope, parameterization, and performance of MMFF94. Journal of Computational Chemistry, 17(5–6), 490–519. https://doi.org/10.1002/(SICI)1096-987X(199604)17:5/6<490::AID-JCC1>3.0.CO;2-P
   Web of Science ®Google Scholar
• Hanwell, M. D., Curtis, D. E., Lonie, D. C., Vandermeersch, T., Zurek, E., & Hutchison, G. R. (2012). Avogadro: An advanced semantic chemical editor, visualization, and analysis platform. Journal of Cheminformatics, 4(1), 17. https://doi.org/10.1186/1758-2946-4-17
   PubMed Web of Science ®Google Scholar
• Harrach, M. F., & Drossel, B. (2014). Structure and dynamics of TIP3P, TIP4P, and TIP5P water near smooth and atomistic walls of different hydroaffinity. The Journal of Chemical Physics, 140(17), 174501–174515. https://doi.org/10.1063/1.4872239
   PubMed Web of Science ®Google Scholar
• Hassan, N. M., Alhossary, A. A., Mu, Y., & Kwoh, C. K. (2017). Protein-ligand blind docking using QuickVina-W with inter-process spatio-temporal integration. Scientific Reports, 7(1), 1–13. https://doi.org/10.1038/s41598-017-15571-7
   PubMedGoogle Scholar
• Hess, B., Bekker, H., Berendsen, H., J., C., & Fraaije, J. G. E. M. (1997). LINCS: A Linear Constraint Solver for molecular simulations. Journal of Computational Chemistry, 18(12), 1463–1472. https://doi.org/10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H
   Web of Science ®Google Scholar
• Huang, W., Manglik, A., Venkatakrishnan, A. J., Laeremans, T., Feinberg, E. N., Sanborn, A. L., Kato, H. E., Livingston, K. E., Thorsen, T. S., Kling, R. C., Granier, S., Gmeiner, P., Husbands, S. M., Traynor, J. R., Weis, W. I., Steyaert, J., Dror, R. O., & Kobilka, B. K. (2015). Structural insights into μ-opioid receptor activation. Nature, 524(7565), 315–321. https://doi.org/10.1038/nature14886
   PubMed Web of Science ®Google Scholar
• Hughes, J. D., Blagg, J., Price, D. A., Bailey, S., DeCrescenzo, G. A., Devraj, R. V., Ellsworth, E., Fobian, Y. M., Gibbs, M. E., Gilles, R. W., Greene, N., Huang, E., Krieger-Burke, T., Loesel, J., Wager, T., Whiteley, L., & Zhang, Y. (2008). Physiochemical drug properties associated with in vivo toxicological outcomes. Bioorganic & Medicinal Chemistry Letters, 18(17), 4872–4875. https://doi.org/10.1016/j.bmcl.2008.07.071
   PubMed Web of Science ®Google Scholar
• Hughes, T. B., Miller, G. P., & Swamidass, S. J. (2015). Modeling epoxidation of drug-like molecules with a deep machine learning network. ACS Central Science, 1(4), 168–180. https://doi.org/10.1021/acscentsci.5b00131
   PubMed Web of Science ®Google Scholar
• Humphrey, W., Dalke, A., & Schulten, K. (1996). VMD: Visual molecular dynamics. Journal of Molecular Graphics, 14(1), 33–38. https://doi.org/10.1016/0263-7855(96)00018-5
   PubMedGoogle Scholar
• Jeong, K. Y., & Park, M. (2021). Poly adenosine diphosphate-ribosylation, a promising target for colorectal cancer treatment. World Journal of Gastrointestinal Oncology, 13(6), 574–588. https://doi.org/10.4251/wjgo.v13.i6.574
   PubMed Web of Science ®Google Scholar
• Jofily, P., Pascutti, P. G., & Torres, P. H. M. (2021). Improving blind docking in DOCK6 through an automated preliminary fragment probing strategy. Molecules, 26(5), 1224–1214. https://doi.org/10.3390/molecules26051224
   PubMed Web of Science ®Google Scholar
• Johnson, T. W., Dress, K. R., & Edwards, M. (2009). Using the golden triangle to optimize clearance and oral absorption. Bioorganic & Medicinal Chemistry Letters, 19(19), 5560–5564. https://doi.org/10.1016/j.bmcl.2009.08.045
   PubMed Web of Science ®Google Scholar
• Jones, A., & Leimkuhler, B. (2011). Adaptive stochastic methods for sampling driven molecular systems. The Journal of Chemical Physics, 135(8), 084125–084112. https://doi.org/10.1063/1.3626941
   PubMed Web of Science ®Google Scholar
• Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W., & Klein, M. L. (1983). Comparison of simple potential functions for simulating liquid water. The Journal of Chemical Physics, 79(2), 926–935. https://doi.org/10.1063/1.445869
   Web of Science ®Google Scholar
• Kachel, H. S., Buckingham, S. D., & Sattelle, D. B. (2018). Insect toxins – selective pharmacological tools and drug/chemical leads. Current Opinion in Insect Science, 30, 93–98. https://doi.org/10.1016/j.cois.2018.10.001
   PubMed Web of Science ®Google Scholar
• Kachel, H. S., Franzyk, H., Strømgaard, K., Tikhonov, D. B., & Mellor, I. R. (2014). Subunit-dependent inhibition of neuronal nicotinic acetylcholine receptors by philanthotoxins. Biophysical Journal, 106(2), 338a. https://doi.org/10.1016/j.bpj.2013.11.1935
   Web of Science ®Google Scholar
• Kachel, H. S., Patel, R. N., Franzyk, H., & Mellor, I. R. (2016). Block of nicotinic acetylcholine receptors by philanthotoxins is strongly dependent on their subunit composition. Scientific Reports, 6, 38116–38113. https://doi.org/10.1038/srep38116
   PubMed Web of Science ®Google Scholar
• Kemp, N. (2021). Pharmacology of opioids and application to practice. The Veterinary Nurse, 12(1), 40–47. https://doi.org/10.12968/vetn.2021.12.1.40
   Google Scholar
• Kenny, P. T., M., Goodnow, R. A., Konno, K., & Nakanishi, K. (1989). Philanthotoxins. A mass spectrometric investigation. Rapid Communications in Mass Spectrometry : RCM, 3(9), 295–297. https://doi.org/10.1002/rcm.1290030906
   PubMedGoogle Scholar
• King, N., Hittinger, C. T., & Carroll, S. B. (2003). Evolution of key cell signaling and adhesion protein families predates animal origins. Science (New York, N.Y.), 301(5631), 361–363. https://doi.org/10.1126/science.1083853
   PubMed Web of Science ®Google Scholar
• Kloss, T. G. (2015). MANIPULAÇÃO COMPORTAMENTAL DE ARANHAS POR VESPAS PARASITOIDES: HISTÓRIA NATURAL E MECANISMO DE AÇÃO. In Proceedings of the National Academy of Sciences. Universidade Federal de Viçosa.
   Google Scholar
• Lansu, K., Karpiak, J., Liu, J., Huang, X. P., McCorvy, J. D., Kroeze, W. K., Che, T., Nagase, H., Carroll, F. I., Jin, J., Shoichet, B. K., & Roth, B. L. (2017). In silico design of novel probes for the atypical opioid receptor MRGPRX2. Nature Chemical Biology, 13(5), 529–536. https://doi.org/10.1038/nchembio.2334
   PubMed Web of Science ®Google Scholar
• Leitão-Filho, H. F. (1992). A flora arbórea da Serra do Japi. In L. P. C. Morellato (Ed.), História natural da Serra do Japi: ecologia e preservação de uma área florestal no Sudeste do Brasil (1st ed., pp. 40–42). Unicamp/Fapesp.
   Google Scholar
• Liang, J., Karagiannis, C., Pitsillou, E., Darmawan, K. K., Ng, K., Hung, A., & Karagiannis, T. C. (2020). Site mapping and small molecule blind docking reveal a possible target site on the SARS-CoV-2 main protease dimer interface. Computational Biology and Chemistry, 89, 107372. https://doi.org/10.1016/j.compbiolchem.2020.107372
   PubMed Web of Science ®Google Scholar
• MacKerell, A. D., Bashford, D., Bellott, M., Dunbrack, R. L., Evanseck, J. D., Field, M. J., Fischer, S., Gao, J., Guo, H., Ha, S., Joseph-McCarthy, D., Kuchnir, L., Kuczera, K., Lau, F. T., Mattos, C., Michnick, S., Ngo, T., Nguyen, D. T., Prodhom, B., … Karplus, M. (1998). All-atom empirical potential for molecular modeling and dynamics studies of proteins. The Journal of Physical Chemistry. B, 102(18), 3586–3616. https://doi.org/10.1021/jp973084f
   PubMed Web of Science ®Google Scholar
• Maier, J. A., Martinez, C., Kasavajhala, K., Wickstrom, L., Hauser, K. E., & Simmerling, C. (2015). ff14SB: Improving the accuracy of protein side chain and backbone parameters from ff99SB. Journal of Chemical Theory and Computation, 11(8), 3696–3713. https://doi.org/10.1021/acs.jctc.5b00255
   PubMed Web of Science ®Google Scholar
• Marín-Aguilar, F., Pavillard, L. E., Giampieri, F., Bullón, P., & Cordero, M. D. (2017). Adenosine monophosphate (AMP)-activated protein kinase: A new target for nutraceutical compounds. International Journal of Molecular Sciences, 18(2), 288–224. https://doi.org/10.3390/ijms18020288
   PubMed Web of Science ®Google Scholar
• Marinho, E. M., Batista de Andrade Neto, J., Silva, J., Rocha da Silva, C., Cavalcanti, B. C., Marinho, E. S., & Nobre Júnior, H. V. (2020). Virtual screening based on molecular docking of possible inhibitors of Covid-19 main protease. Microbial Pathogenesis, 148, 104365. https://doi.org/10.1016/j.micpath.2020.104365
   PubMed Web of Science ®Google Scholar
• Martyna, G. J., Hughes, A., & Tuckerman, M. E. (1999). Molecular dynamics algorithms for path integrals at constant pressure. The Journal of Chemical Physics, 110(7), 3275–3290. https://doi.org/10.1063/1.478193
   Web of Science ®Google Scholar
• Mascoli, V., Liguori, N., Cupellini, L., Elias, E., Mennucci, B., & Croce, R. (2021). Uncovering the interactions driving carotenoid binding in light-harvesting complexes. Chemical Science, 12(14), 5113–5122. https://doi.org/10.1039/d1sc00071c
   PubMed Web of Science ®Google Scholar
• Matos, M. G. C., Da Silva, L. P., Wagner Queiroz Almeida-Neto, F., Machado Marinho, E., Róseo Paula Pessoa Bezerra De Menezes, R., Lima Sampaio, T., Nunes Da Rocha, M., Rodrigues Ribeiro, L., Paula Magalhaes, E., Rodrigues Teixeira, A. M., Dos Santos, H. S., Marinho, E. S., De Lima-Neto, P., Costa Martins, A. M., Monteiro, N. K. V., & Machado Marinho, M. (2022). Quantum mechanical, molecular docking, molecular dynamics, ADMET and antiproliferative activity on Trypanosoma cruzi (Y strain) of chalcone (E)-1-(2-hydroxy-3,4,6-trimethoxyphenyl)-3-(3-nitrophenyl)prop-2-en-1-one derived from a natural product. Physical Chemistry Chemical Physics : PCCP, 24(8), 5052–5069. https://doi.org/10.1039/d1cp04992e
   PubMed Web of Science ®Google Scholar
• Matthes, H. W., Maldonado, R., Simonin, F., Valverde, O., Slowe, S., Kitchen, I., Befort, K., Dierich, A., Le Meur, M., Dollé, P., Tzavara, E., Hanoune, J., Roques, B. P., & Kieffer, B. L. (1996). Loss of morphine-induced analgesia, reward effect and withdrawal symptoms in mice lacking the μ-opioid-receptor gene. Nature, 383(6603), 819–823. https://doi.org/10.1038/383819a0
   PubMed Web of Science ®Google Scholar
• Mazola, Y., Guirola, O., Palomares, S., Chinea, G., Menéndez, C., Hernández, L., & Musacchio, A. (2015). A comparative molecular dynamics study of thermophilic and mesophilic β-fructosidase enzymes. Journal of Molecular Modeling, 21(9), 1–15. https://doi.org/10.1007/s00894-015-2772-4
   PubMed Web of Science ®Google Scholar
• Mazón, M., Sánchez, D., Díaz, F. A., Gaviria, J. C. (2016). Metodología para el monitoreo participativo de la restauración ecológica con estudiantes de primaria en plantaciones de cacao de Mérida, Venezuela. Biota Colombiana, 17(1), 3-24. https://doi.org/10.21068/C2016v17r01a02
   Google Scholar
• Morris, G. M., Huey R Fau- Lindstrom, W., Lindstrom W Fau- Sanner, M. F., Sanner Mf Fau- Belew, R. K., Belew Rk Fau- Goodsell, D. S., Goodsell Ds Fau- Olson, A. J., Olson, A. J., Chem,., & J., C. (2009). AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. Journal of Computational Chemistry, 30(16), 2785–2791. https://doi.org/10.1002/jcc.21256
   PubMed Web of Science ®Google Scholar
• Mossé, Y. P., Laudenslager, M., Longo, L., Cole, K. A., Wood, A., Attiyeh, E. F., Laquaglia, M. J., Sennett, R., Lynch, J. E., Perri, P., Laureys, G., Speleman, F., Kim, C., Hou, C., Hakonarson, H., Torkamani, A., Schork, N. J., Brodeur, G. M., Tonini, G. P., … Maris, J. M. (2008). Identification of ALK as a major familial neuroblastoma predisposition gene. Nature, 455(7215), 930–935. https://doi.org/10.1038/nature07261
   PubMed Web of Science ®Google Scholar
• Negus, S. S., & Moerke, M. J. (2019). Determinants of opioid abuse potential: Insights using intracranial self-stimulation. Peptides, 112, 23–31. https://doi.org/10.1016/j.peptides.2018.10.007
   PubMed Web of Science ®Google Scholar
• Nguyen, D. D., Xiao, T., Wang, M., & Wei, G. W. (2017). Rigidity strengthening: A mechanism for protein-ligand binding. Journal of Chemical Information and Modeling, 57(7), 1715–1721. https://doi.org/10.1021/acs.jcim.7b00226
   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(1), 1–14. https://doi.org/10.1186/1758-2946-3-33
   PubMed Web of Science ®Google Scholar
• Padua, D. G. d. (2014). Taxonomia de Hymenoepimecis Viereck, 1912 (Hymenoptera: Ichneumonidae. Pimplinae) Na Amazônia Brasileira, 39(1), 1–15.
   Google Scholar
• Palacio, E., Broad, G. R., Sääksjärvi, I. E., & Veijalainen, A. (2010). Western amazonian Ticapimpla (Hymenoptera: Ichneumonidae: Pimplinae): Four new species from Colombia, Ecuador, and Peru, with a key to species of the genus. Psyche (London), 2010, 1–8. https://doi.org/10.1155/2010/161595
   Google Scholar
• Pasternak, G. W., & Pan, Y. X. (2013). Mu opioids and their receptors: Evolution of a concept. Pharmacological Reviews, 65(4), 1257–1317. ( https://doi.org/10.1124/pr.112.007138
   PubMed Web of Science ®Google Scholar
• Pergolizzi, J. V., Raffa, R. B., & Rosenblatt, M. H. (2020). Opioid withdrawal symptoms, a consequence of chronic opioid use and opioid use disorder: Current understanding and approaches to management. Journal of Clinical Pharmacy and Therapeutics, 45(5), 892–903. https://doi.org/10.1111/jcpt.13114
   PubMed Web of Science ®Google Scholar
• Phillips, J. C., Braun, R., Wang, W., Gumbart, J., Tajkhorshid, E., Villa, E., Chipot, C., Skeel, R. D., Kalé, L., & Schulten, K. (2005). Scalable molecular dynamics with NAMD. Journal of Computational Chemistry, 26(16), 1781–1802. https://doi.org/10.1002/jcc.20289
   PubMed Web of Science ®Google Scholar
• Piek, T. (1982). δ-philanthotoxin, a semi-irreversible blocker of ion-channels. Comparative Biochemistry and Physiology. C: Comparative Pharmacology, 72(2), 311–315. https://doi.org/10.1016/0306-4492(82)90098-3
   PubMed Web of Science ®Google Scholar
• Pinto, H. S. (1982). Clima na Serra do Japi. In L. P. C. Morellato (Ed.), História Natural da Serra do Japi: ecologia e preservacão de uma área florestal no Sudeste do Brasil (1st ed., pp. 30–38). Editora da Unicamp/Fapesp.
   Google Scholar
• Pires, D. E. V., Kaminskas, L. M., & Ascher, D. B. (2018). Prediction and optimization of pharmacokinetic and toxicity properties of the ligand. Methods in Molecular Biology, 1762, 271–284. https://doi.org/10.1007/978-1-4939-7756-7_14
   Google Scholar
• Podlewska, S., Bugno, R., Kudla, L., Bojarski, A. J., & Przewlocki, R. (2020). Molecular modeling of µ opioid receptor ligands with various functional properties: PZM21, SR-17018, morphine, and fentanyl-simulated interaction patterns confronted with experimental data. Molecules, 25(20), 4636. https://doi.org/10.3390/molecules25204636
   PubMed Web of Science ®Google Scholar
• Qin, X., Zhong, J., & Wang, Y. (2021, February). A mutant T1 lipase homology modeling, and its molecular docking and molecular dynamics simulation with fatty acids. Journal of Biotechnology, 337, 24–34. https://doi.org/10.1016/j.jbiotec.2021.06.024
   PubMed Web of Science ®Google Scholar
• Radchenko, E. V., Dyabina, A. S., Palyulin, V. A., & Zefirov, N. S. (2016). Prediction of human intestinal absorption of drug compounds. Russian Chemical Bulletin, 65(2), 576–580. https://doi.org/10.1007/s11172-016-1340-0
   Web of Science ®Google Scholar
• Ragunathan, A., Malathi, K., & Anbarasu, A. (2018). MurB as a target in an alternative approach to tackle the Vibrio cholerae resistance using molecular docking and simulation study. Journal of Cellular Biochemistry, 119(2), 1726–1732. https://doi.org/10.1002/jcb.26333
   PubMed Web of Science ®Google Scholar
• Roe, D. R., & Brooks, B. R. (2020). A protocol for preparing explicitly solvated systems for stable molecular dynamics simulations. The Journal of Chemical Physics, 153(5), 054123–054129. https://doi.org/10.1063/5.0013849
   PubMed Web of Science ®Google Scholar
• Ryckaert, J. P., Ciccotti, G., & Berendsen, H. J. C. (1977). Numerical integration of the cartesian equations of motion of a system with constraints: Molecular dynamics of n-alkanes. Journal of Computational Physics, 23(3), 327–341. https://doi.org/10.1016/0021-9991(77)90098-5
   Web of Science ®Google Scholar
• Schowalter, T. D., Noriega, J. A., & Tscharntke, T. (2018). Insect effects on ecosystem services—Introduction. Basic and Applied Ecology, 26, 1–7. https://doi.org/10.1016/j.baae.2017.09.011
   Web of Science ®Google Scholar
• Shityakov, S., & Foerster, C. (2014). In silico predictive model to determine vector-mediated transport properties for the blood-brain barrier choline transporter. Advances and Applications in Bioinformatics and Chemistry, 2014(7), 23–26. https://doi.org/10.2147/AABC.S63749
   Google Scholar
• Sobczak, J. F. (2009). Modificações comportamentais em aranhas orbitelas (Areneae: Tetragnathidae, Nephilidae, Araneidae) Atacadas por Vespas Parasitóides (Ichneumonidae, Pimplinae Polysphinctini).
   Google Scholar
• Sobczak, J. F. (2013). Estudos Biológicos da Interação entre Nephila Clavipes (Araneae, Nephilidae) e o Parasitoide Hymenoepimecis Bicolor (Hymenoptera, Ichneumonidae, Pimplinae).
   Google Scholar
• Sobczak, J., Loffredo, A., & Penteado-Dias, A. (2012). Parasitism on Araneus venatrix (Koch, 1838) (Araneae: Araneidae) by Hymenoepimecis silvanae Loffredo and Penteado-Dias, 2009 (Ichneumonidae, Pimplinae) with description of male of the wasp. Brazilian Journal of Biology=Revista Brasleira De Biologia, 72(1), 221–223. https://doi.org/10.1590/S1519-69842012000100028
   PubMed Web of Science ®Google Scholar
• Strømgaard, K., Jensen, L. S., & Vogensen, S. B. (2005). Polyamine toxins: Development of selective ligands for ionotropic receptors. Toxicon : Official Journal of the International Society on Toxinology, 45(3), 249–254. https://doi.org/10.1016/j.toxicon.2004.11.013
   PubMed Web of Science ®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
• Turner, P. (2005). XMGRACE, version 5.1. 19. Center for Coastal and Land-Margin Research, Oregon Graduate Institute of Science and Technology.
   Google Scholar
• Vallejo, R., Barkin, R. L., & Wang, V. C. (2011). Pharmacology of opioids in the treatment of chronic pain syndromes. Pain Physician, 14(4), E343–E360. https://doi.org/10.36076/ppj.2011/14/E343
   PubMed Web of Science ®Google Scholar
• Wager, T. T., Hou, X., Verhoest, P. R., & Villalobos, A. (2010). Moving beyond rules: The development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of druglike properties. ACS Chemical Neuroscience, 1(6), 435–449. https://doi.org/10.1021/cn100008c
   PubMed Web of Science ®Google Scholar
• Wang, N. N., Dong, J., Deng, Y. H., Zhu, M. F., Wen, M., Yao, Z. J., Lu, A. P., Wang, J. B., & Cao, D. S. (2016). ADME properties evaluation in drug discovery: Prediction of Caco-2 cell permeability using a combination of NSGA-II and boosting. Journal of Chemical Information and Modeling, 56(4), 763–773. https://doi.org/10.1021/acs.jcim.5b00642
   PubMed Web of Science ®Google Scholar
• Waterman, P. G. (1996). Identification of essential oil components by gas chromatography/mass spectroscopy. Biochemical Systematics and Ecology, 24(6), 594. https://doi.org/10.1016/0305-1978(96)83708-2
   Google Scholar
• Yan, C. T., Du, Y. N., Han, J., Ren, W., & Liu, Z. Q. (2021). Neurotransmitters and modulators of periaqueductal gray that involved in pain regulation. Progress in Biochemistry and Biophysics, 48(2), 158-170. https://doi.org/10.16476/j.pibb.2020.0187
   Web of Science ®Google Scholar
• Yan, J., Zhang, G., Pan, J., & Wang, Y. (2014). α-Glucosidase inhibition by luteolin: Kinetics, interaction and molecular docking. International Journal of Biological Macromolecules, 64, 213–223. https://doi.org/10.1016/j.ijbiomac.2013.12.007
   PubMed Web of Science ®Google Scholar
• Yu, K., Geng, X., Chen, M., Zhang, J., Wang, B., Ilic, K., & Tong, W. (2014). High daily dose and being a substrate of cytochrome P450 enzymes are two important predictors of drug-induced liver injury. Drug Metabolism and Disposition: The Biological Fate of Chemicals, 42(4), 744–750. https://doi.org/10.1124/dmd.113.056267
   PubMed Web of Science ®Google Scholar
• Yusuf, D., Davis, A. M., Kleywegt, G. J., & Schmitt, S. (2008). An alternative method for the evaluation of docking performance: RSR vs RMSD. Journal of Chemical Information and Modeling, 48(7), 1411–1422. https://doi.org/10.1021/ci800084x
   PubMed Web of Science ®Google Scholar