Suitable Docking Protocol for the Design of Novel Coumarin Derivatives with Selective MAO-B Effects
DOI:
https://doi.org/10.33084/jmd.v1i1.2357Keywords:
MAO-B inhibitors, Molecular docking, Ensemble docking, CoumarinAbstract
Recently, the application of molecular docking is drastically increasing due to the rapid growth of resolved crystallographic receptors with co-crystallized ligands. However, the inability of docking softwares to correctly score the occurred interactions between ligands and receptors is still a relevant issue. This study examined the Pearson’s correlation coefficient between the experimental monoamine oxidase-B (MAO-B) inhibitory activity of 44 novel coumarins and the obtained GOLD 5.3 docking scores. Subsequently, optimization of the docking protocol was carried out to achieve the best possible pairwise correlation. Numerous modifications in the docking settings such as alteration in the scoring functions, size of the grid space, presence of active waters, and side-chain flexibility were conducted. Furthermore, ensemble docking simulations into two superimposed complexes were performed. The model was validated with a test set. A significant Pearson’s correlation coefficient of 0.8217 was obtained for the latter. In the final stage of our work, we observed the major interactions between the top-scored ligands and the active site of 1S3B.
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References
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2. Behl T, Kaur D, Sehgal A, Singh S, Sharma N, Zengin G, et al. Role of Monoamine Oxidase Activity in Alzheimer’s Disease: An Insight into the Therapeutic Potential of Inhibitors. Molecules. 2021;26(12):3724. doi:10.3390/molecules26123724
3. Finberg JPM. Inhibitors of MAO-B and COMT: their effects on brain dopamine levels and uses in Parkinson's disease. J Neural Transm. 2019;126(4):433-48. doi:10.1007/s00702-018-1952-7
4. Liu Z, Cai W, Lang M, Yan R, Li Z, Zhang G, et al. Neuroprotective Effects and Mechanisms of Action of Multifunctional Agents Targeting Free Radicals, Monoamine Oxidase B and Cholinesterase in Parkinson's Disease Model. J Mol Neurosci. 2017;61(4):498-510. doi:10.1007/s12031-017-0891-3
5. Szökő É, Tábi T, Riederer P, Vécsei L, Magyar K. Pharmacological aspects of the neuroprotective effects of irreversible MAO-B inhibitors, selegiline and rasagiline, in Parkinson's disease. J Neural Transm. 2018;125(11):1735-49. doi:10.1007/s00702-018-1853-9
6. Binda C, Newton-Vinson P, Hubálek F, Edmondson DE, Mattevi A. Structure of human monoamine oxidase B, a drug target for the treatment of neurological disorders. Nat Struct Biol. 2002;9(1):22-6. doi:10.1038/nsb732
7. Pisani L, Farina R, Nicolotti O, Gadaleta D, Soto-Otero R, Catto M, et al. In silico design of novel 2H-chromen-2-one derivatives as potent and selective MAO-B inhibitors. Eur J Med Chem. 2015;89:98-105. doi:10.1016/j.ejmech.2014.10.029
8. Azam F, Madi AM, Ali HI. Molecular Docking and Prediction of Pharmacokinetic Properties of Dual Mechanism Drugs that Block MAO-B and Adenosine A2A Receptors for the Treatment of Parkinson's Disease. J Young Pharm. 2012;4(3):184-92. doi:10.4103/0975-1483.100027
9. Azam F, Abodabos HS, Taban IM, Rfieda AR, Mahmood D, Anwar MJ, et al. Rutin as promising drug for the treatment of Parkinson’s disease: an assessment of MAO-B inhibitory potential by docking, molecular dynamics and DFT studies. Mol Simul. 2019;45(18):1563-71. doi:10.1080/08927022.2019.1662003
10. Leelananda SP, Linden S. Computational methods in drug discovery. Beilstein J Org Chem. 2016;12:2694-718. doi:10.3762/bjoc.12.267
11. Pratama MRF, Gusdinar T. Docking study of secondary metabolites from Glycyrrhiza glabra as PPAR-γ agonist. Biointerface Res Appl Chem. 2019;9(4):4006-10. doi:10.33263/BRIAC94.006010
12. Pratama MRF, Gusdinar T. Between artemisinin and derivatives with neuraminidase: a docking study insight. Asian J Pharm Clin Res. 2017;10(8):304-8. doi:10.22159/ajpcr.2017.v10i8.18667
13. Awuni Y, Mu Y. Reduction of False Positives in Structure-Based Virtual Screening When Receptor Plasticity Is Considered. Molecules. 2015;20(3):5152-64. doi:10.3390/molecules20035152
14. Matthews N, Kitao A, Laycock S, Hayward S. Haptic-Assisted Interactive Molecular Docking Incorporating Receptor Flexibility. J Chem Inf Model. 2019;59(6):2900-12. doi:10.1021/acs.jcim.9b00112
15. Poli G, Granchi C, Rizzolio F, Tuccinardi T. Application of MM-PBSA Methods in Virtual Screening. Molecules. 2020;25(8):1971. doi:10.3390/molecules25081971
16. Mazurek AH, Szeleszczuk L, Simonson T, Pisklak DM. Application of Various Molecular Modelling Methods in the Study of Estrogens and Xenoestrogens. Int J Mol Sci. 2020;21(17):6411. doi:10.3390/ijms21176411
17. Lionta E, Spyrou G, Vassilatis DK, Cournia Z. Structure-Based Virtual Screening for Drug Discovery: Principles, Applications and Recent Advances. Curr Top Med Chem. 2014;14(16):1923-38. doi:10.2174/1568026614666140929124445
18. Jones G, Willett P, Glen RC, Leach AR, Taylor R. Development and validation of a genetic algorithm for flexible docking. J Mol Biol. 1997;267(3):727-48. doi:10.1006/jmbi.1996.0897
19. Sapundzhi F, Dzimbova T. Modelling of the structure-activity relationships of CBR 2. J Chem Technol Metall. 2020;55(4):709-13.
20. Binda C, Li M, Hubalek F, Restelli N, Edmondson DE, Mattevi A. Insights into the mode of inhibition of human mitochondrial monoamine oxidase B from high-resolution crystal structures. Proc Natl Acad Sci U S A. 2003;100(17):9750-5. doi:10.1073/pnas.1633804100
21. Binda C, Hubalek F, Li M, Herzig Y, Sterling J, Edmondson DE, et al. Crystal structures of monoamine oxidase B in complex with four inhibitors of the N-propargylaminoindan class. J Med Chem. 2004;47(7):1767-74. doi:10.1021/jm031087c
22. Binda C, Wang J, Pisani L, Caccia C, Carotti A, Salvati P, et al. Structures of human monoamine oxidase B complexes with selective noncovalent inhibitors: safinamide and coumarin analogs. J Med Chem. 2007;50(23):5848-52. doi:10.1021/jm070677y
23. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, et al. The Protein Data Bank. Nucleic Acids Res. 2000;28(1):235-42. doi:10.1093/nar/28.1.235
24. Mukherjee S, Balius TE, Rizzo RC. Docking Validation Resources: Protein Family and Ligand Flexibility Experiments. J Chem Inf Model. 2010;50(11):1986-2000. doi:10.1021/ci1001982
25. Torres PHM, Sodero ACR, Jofily P, Silva Jr FP. Key Topics in Molecular Docking for Drug Design. Int J Mol Sci. 2019;20(18):4574. doi:10.3390/ijms20184574
26. Feinstein WP, Brylinski M. Calculating an optimal box size for ligand docking and virtual screening against experimental and predicted binding pockets. J Cheminform. 2015;7:18. doi:10.1186/s13321-015-0067-5
27. Xiao W, Wang D, Shen Z, Li S, Li H. Multi-Body Interactions in Molecular Docking Program Devised with Key Water Molecules in Protein Binding Sites. Molecules. 2018;23(9):2321. doi:10.3390/molecules23092321
28. Schiebel J, Gaspari R, Wuldsorf T, Ngo K, Sohn C, Schrader TE, et al. Intriguing role of water in protein-ligand binding studied by neutron crystallography on trypsin complexes. Nat Commun. 2018;9:3559. doi:10.1038/s41467-018-05769-2
29. Ollikainen N, de Jong RM, Kortemme T. Coupling Protein Side-Chain and Backbone Flexibility Improves the Re-design of Protein-Ligand Specificity. PLoS Comput Biol. 2015;11(9):e1004335. doi:10.1371/journal.pcbi.1004335
30. Kokh DB, Wenzel W. Flexible side chain models improve enrichment rates in in silico screening. J Med Chem. 2008;51(19):5919-31. doi:10.1021/jm800217k
31. Nagy PI. Competing Intramolecular vs. Intermolecular Hydrogen Bonds in Solution. Int J Mol Sci. 2014;15(11):19562-633. doi:10.3390/ijms151119562
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Published
2021-06-30
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1.
Mateev EV, Valkova I, Georgieva M, Zlatkov A. Suitable Docking Protocol for the Design of Novel Coumarin Derivatives with Selective MAO-B Effects. J Mol Docking [Internet]. 2021Jun.30 [cited 2024Dec.21];1(1):40-7. Available from: https://journal.umpr.ac.id/index.php/jmd/article/view/2357
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