Molecular in Silico Screening and Docking of Potential Inhibitors of Enzyme Activity of Plant Raw Materials

Introduction. Lipolysis of triacylglycerols under the action of its own enzymatic system in sunflower seeds is a natural biochemical process in which mono- and diglycerides of fatty acids are formed. These substances are precursors of toxic food contaminants - glycidol and monochloropropanediol esters, which are formed in the technology of fat processing. In order to reduce the likelihood of their formation, it is of high practical interest to study the effect of the components of the composition of oilseed raw materials on the natural biochemical processes in sunflower seeds in storage.

Methods. The work used modeling of the three-dimensional structure of lipase by homology, phylogenetic analysis, multiple alignment of amino acid sequences, analysis of Ramanchandran maps, molecular docking.

Results. It is shown that the closest to the lipase of sunflower seeds in the amino acid sequence is the pancreatic lipase of a dog (Canis lupus familiaris), encoded by the MPL1 gene. It was determined that according to the multiple alignment of amino acid sequences, the active centers of the studied sunflower lipases ATLIP1, LIPG, MPL1 are not included in the conservative sites, but the active centers of sunflower lipase MPL1 are closest to the conservative sites of a potential template for modeling.

Conclusions. Based on the results of multiple alignment of amino acid sequences and phylogenetic analysis, it was determined that the selected templates for constructing a model of sunflower lipases are closely related and can be used for homologous modeling. Inhibitors of lipase activity of microbial origin showed a stable correlation with the values of the concentration of semi-maximal inhibition of IC50. According to the results of molecular docking of minor components of oilseed raw materials, it was shown that chlorogenic and neochlorogenic acids and daidzein have the greatest affinity for lipase.

1. Code of practice for the reduction of 3-monochloropropane-1,2- diol esters (3-mcpdes) and glycidyl esters (ges) in refined oils and food products made with refined oils. (2019). CXC 79-2019.

2. Schultrich, K., Henderson, C. J., Braeuning, A., & Buhrke, T. (2020). Correlation between 3-MCPD-induced organ toxicity and oxidative stress response in male mice. Food and Chemical Toxicology, 136, 110957. https://doi.org/10.1016/j.fct.2019.110957

3. Sagiroglu, A., Arabaci, N. (2005) Sunflower Seed Lipase: Extraction, Purification, and Characterization, Preparative Biochemistry and Biotechnology, 35:1, 37-51, DOI: https://doi.org/10.1081/PB-200041442

4. Nebeg, H., Benarous, K., Serseg, T., Lazreg, A., Hassani, H., & Yousfi, M. (2019). Seeds, Leaves and Roots of Thapsia garganica as a Source of New Potent Lipases Inhibitors: In vitro and In silico Studies. Endocrine, Metabolic & Immune Disorders - Drug Targets, 19(5). https://doi.org/10.2174/1871530319666190128122211

5. Kumar, S., Stecher, G., Li, M., Knyaz, C., & Tamura, K. (2018). MEGA X: Molecular evolutionary genetics analysis across computing platforms. Molecular Biology and Evolution, 35(6), 1547–1549. https://doi.org/10.1093/molbev/msy096

6. Jones D.T., Taylor W.R., and Thornton J.M. (1992). The rapid generation of mutation data matrices from protein sequences. Computer Applications in the Biosciences 8: 275-282.

7. Waterhouse, A., Bertoni, M., Bienert, S., Studer, G., Tauriello, G., Gumienny, R., Heer, F. T., de Beer, T. A. P., Rempfer, C., Bordoli, L., Lepore, R., & Schwede, T. (2018). SWISS-MODEL: Homology modelling of protein structures and complexes. Nucleic Acids Research, 46(W1), W296–W303. https://doi.org/10.1093/nar/gky427

8. Biasini, M., Bienert, S., Waterhouse, A., Arnold, K., Studer, G., Schmidt, T., Kiefer, F., Gallo Cassarino, T., Bertoni, M., Bordoli, L., & Schwede, T. (2014). SWISS-MODEL: modelling protein tertiary and quaternary structure using evolutionary information. Web Server Issue Published Online, 42. https://doi.org/10.1093/nar/gku340

9. Altschul, S. F., Madden, T. L., Schäffer, A. A., Zhang, J., Zhang, Z., Miller, W., & Lipman, D. J. (1997). Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. In Nucleic Acids Research (Vol. 25, Issue 17). Oxford University Press. https://academic.oup.com/nar/article/25/17/3389/1061651

10. Camacho, C., Coulouris, G., Avagyan, V., Ma, N., Papadopoulos, J., Bealer, K., Madden, T. L. (2009). BLAST+: architecture and applications. https://doi.org/10.1186/1471-2105-10-421

11. Bertoni, M., Kiefer, F., Biasini, M., Bordoli, L., Schwede, T. (2018). Modeling protein quaternary structure of homo-and hetero-oligomers beyond binary interactions by homology OPEN. https://doi.org/10.1038/s41598-017-09654-8

12. Benkert, P., Biasini, M., & Schwede, T. (2011). Toward the estimation of the absolute quality of individual protein structure models. 27(3), 343–350. https://doi.org/10.1093/bioinformatics/btq662

13. Bienert, S., Waterhouse, A., de Beer, T. A. P., Tauriello, G., Studer, G., Bordoli, L., Schwede, T. (2016). The SWISS-MODEL Repository-new features and functionality. Nucleic Acids Research, 45, 313–319. https://doi.org/10.1093/nar/gkw1132

14. Pettersen, E. F., Goddard, T. D., Huang, C. C., Couch, G. S., Greenblatt, D. M., Meng, E. C., & Ferrin, T. E. (2004). UCSF Chimera - A visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605–1612. https://doi.org/10.1002/jcc.20084

15. Meng, E. C., Pettersen, E. F., Couch, G. S., Huang, C. C., & Ferrin, T. E. (2006). Tools for integrated sequence-structure analysis with UCSF Chimera. BMC Bioinformatics, 7, 1–10. https://doi.org/10.1186/1471-2105-7-339

16. Trott, O., Olson A. (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://10.1002/jcc.21334

17. Schöning, K., Schöning-Stierand, S., Diedrich, K., Ahrrolfes, R. F. ¨, Flachsenberg, F., Meyder, A., Nittinger, E., Steinegger, R., & Rarey, M. (2020). ProteinsPlus: interactive analysis of protein-ligand binding interfaces. Web Server Issue Published Online, 48. https://doi.org/10.1093/nar/gkaa235

18. O’boyle, N. M., Banck, M., James, C. A., Morley, C., Vandermeersch, T., & Hutchison, G. R. (2011). Open Babel: An open chemical toolbox. https://doi.org/10.1186/1758-2946-3-33

19. Wu, C. H., Nikolskaya, A., Huang, H., Yeh, L. S., Natale, D. A., Vinayaka, C. R., Hu, Z. Z., Mazumder, R., Kumar, S., Kourtesis, P., Ledley, R. S., Suzek, B. E., Arminski, L., Chen, Y., Zhang, J., Cardenas, J. L., Chung, S., Castro-Alvear, J., Dinkov, G., & Barker, W. C. (2004). PIRSF: Family classification system at the Protein Information Resource. Nucleic Acids Research, 32(DATABASE ISS.), 112–114. https://doi.org/10.1093/nar/gkh097

20. Ameis, D., Merkel, M., Eckerskornz, C., Greten, H. (1994). Purification, characterization and molecular cloning of human hepatic lysosomal acid lipase. In Eur. J. Biochem (Vol. 219).

21. Warner TG, Dambach L M, Shin, J H, O'Brien, J S (1981). Purification of the lysosomal acid lipase from human liver and its role in lysosomal lipid hydrolysis. J Biol Chem 25; 256(6): 2952-7. PMID: 7204383

22. Ries, S., Büchler, C., Schindler, G., Aslanidis, C., Ameis, D., Gasche, C., Jung, N., Schambach, A., Fehringer, P., Vanier, M. T., Belli, D. C., Greten, H., & Schmitz, G. (1998). Different missense mutations in histidine-108 of lysosomal acid lipase cause cholesteryl ester storage disease in unrelated compound heterozygous and hemizygous individuals. Human Mutation, 12(1), 44–51. https://doi.org/10.1002/(SICI)1098-1004(1998)12:1<44::AID-HUMU7>3.0.CO;2-O

23. Roussel, A., Canaan, S., Egloff, M. P., Rivière, M., Dupuis, L., Verger, R., & Cambillau, C. (1999). Crystal structure of human gastric lipase and model of lysosomal acid lipase, two lipolytic enzymes of medical interest. Journal of Biological Chemistry, 274(24), 16995–17002. https://doi.org/10.1074/jbc.274.24.16995

24. Rogalska, E., Ransac, S., Verger, R. (1990) Stereoselectivity of lipases. II. Stereoselective hydrolysis of triglycerides by gastric and pancreatic lipases. J Biol Chem 25; 265(33): 20271-6. PMID: 2243091

25. Carriere, F., Moreau, H., Vhronique, R. R., Laugier, C. B., Junien, J.-L., Verger, R. (1991). Purification and biochemical characterization of dog gastric lipase. In Eur. J. Biochem (Vol. 202).

26. Carrière, F., Raphel, V., Moreau, H., Bernadac, A., Devaux, M. A., Grimaud, R., Barrowman, J. A., Bénicourt, C., Junien, J. L., Laugier, R., & Verger, R. (1992). Dog gastric lipase: Stimulation of its secretion in vivo and cytolocalization in mucous pit cells. Gastroenterology, 102(5), 1535–1545. https://doi.org/10.1016/0016-5085(92)91711-C

27. David, L., Cheah, E., Cygler, M., Dijkstra, B., Frolow, F., Sybille, M., Harel, M., James Remington, S., Silman, I., Schrag, J., Joel, L., Koen, H. G. V., & Goldman, A. (1992). The α/β hydrolase fold. Protein Engineering, Design and Selection, 5(3), 197–211. https://doi.org/10.1093/protein/5.3.197

28. Selvan, A., Chandrabhan, S., Srinivas N.C., Nithyanand S., Sharmila A., Gautam, P. (2010) Molecular dynamics simulations of human and dog gastric lipases: Insightsinto domain movements. FEBS Letters. Vol. 584 (22) P. 4599-4605.

29. Messaoudi, A., Belguith, hatem, & ben hamida, J. (2011). Three-Dimensional structure of Arabidopsis thaliana Lipase predicted by Homology Modeling Method. Evolutionary Bioinformatics, 99–105. https://doi.org/10.4137/EBO.S7122

30. Wahab, H. A., Khairudin, N. B. A., Samian, M. R., & Najimudin, N. (2006). Sequence analysis and structure prediction of type II Pseudomonas sp. USM 4-55 PHA synthase and an insight into its catalytic mechanism. BMC Structural Biology, 6, 1–14. https://doi.org/10.1186/1472-6807-6-23

31. Birari, R. B., & Bhutani, K. K. (2007). Pancreatic lipase inhibitors from natural sources: unexplored potential. In Drug Discovery Today (Vol. 12, Issues 19–20, pp. 879–889). https://doi.org/10.1016/j.drudis.2007.07.024

32. Tingli B., Daozhong Z., Shuangjun L., Qingshan L., Yemin W., Hongyu O., Qianjin K., Zixin D., Wen L. (2014) Operon for Biosynthesis of Lipstatin, the Beta-Lactone Inhibitor of Human Pancreatic Lipase. Appl Environmental Microbiology, 80 (24): 7473-83. doi: 10.1128/AEM.01765-14.