Stability, Hydrogen Bond Occupancy Analysis and Binding Free Energy Calculation from Flavonol Docked in DAPK1 Active Site Using Molecular Dynamic Simulation Approaches

Adi Tiara Zikri; Harno Dwi Pranowo; Winarto Haryadi

doi:10.22146/ijc.56087

Stability, Hydrogen Bond Occupancy Analysis and Binding Free Energy Calculation from Flavonol Docked in DAPK1 Active Site Using Molecular Dynamic Simulation Approaches

https://doi.org/10.22146/ijc.56087

Adi Tiara Zikri⁽¹⁾, Harno Dwi Pranowo^(2*), Winarto Haryadi⁽³⁾

(1) Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, Yogyakarta 55281, Indonesia
(2) Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, Yogyakarta 55281, Indonesia
(3) Department of Chemistry, Faculty of Mathematics and Natural Sciences, Universitas Gadjah Mada, Sekip Utara, Yogyakarta 55281, Indonesia
(*) Corresponding Author

Abstract

Stability and hydrogen bond occupancy analysis of flavonol derivative docked in DAPK1 have been carried out using molecular dynamics simulation approach. Six flavonol derivatives were docked in DAPK1 as protein target, then continued with molecular dynamics simulation. NVT and NPT ensembles were used to equilibrate the system, followed by 20 ns sampling time for each system. Structural stability and hydrogen bond occupancy analyses were carried out at the NVT ensemble, while free binding energy analysis was done at NPT ensemble. From all compounds used in this work, compound B (5,7-dihydroxy-2-(4-hydroxyphenyl)-6-methoxy-4H-chromen-4-one) has a similar interaction with reference ligands (quercetin, kaempferol, and fisetin), and the most stable complex system has the maximum RMSD around 2 Å. Compound C complex has -48.06 kJ/mol binding free energy score, and it was slightly different from quercetin, kaempferol, and fisetin complexes. Even though complex C has similar binding free energy with the reference compound, complex B shows more stable interactions due to their hydrogen bond and occupancy.

Keywords

flavonol; hydrogen bond occupancy; molecular dynamics simulation

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References

[1] Heim, K.E., Tagliaferro, A.R., and Bobilya, D.J., 2002, Flavonoid antioxidant: Chemistry, metabolism and structure activity relationship, J. Nutr. Biochem., 13 (10), 572–584.

[2] Bucar, F., Wube, A., and Schmid, M., 2013, Natural product isolation – How to get from biological material to pure compounds, Nat. Prod. Rep., 30 (4), 525–545.

[3] Rha, C.S., Jeoung, H.W., Park, S., Lee, S., Jung, Y.S., and Kim, D.O., 2019, Antioxidative, anti-inflammatory, and anticancer effects of purified flavonol glycosides and aglycones in green tea, Antioxidants, 8 (8), 278.

[4] Yokoyama, T., Kosaka, Y., and Mizuguchi, M., 2015, Structural insight into the interactions between death-associated protein kinase 1 and natural flavonoids, J. Med. Chem., 58 (18), 7400−7408.

[5] Chen, L.Z., Yao, L., Jiao, M.M., Shi, J.B., Tan, Y., Ruan, B.F., Hua, X., and Liu, 2019, Novel resveratrol-based flavonol derivatives: Synthesis and anti-inflammatory activity in vitro and in vivo, Eur. J. Med. Chem., 175, 114–128.

[6] Bai, J., Zhao, S., Fan, X., Chen, Y., Zou, X., Hu, M., Wang, B., Jin, J., Wang, X., Hu, J., Zhang, D., and Li, Y., 2019, Inhibitory effects of flavonoids on P-glycoprotein in vitro and in vivo: Food/herb-drug interactions and structure–activity relationships, Toxicol. Appl. Pharmacol., 369, 49–59.

[7] Serafini, M., Peluso, I., and Raguzzini, A., 2010, Flavonoids as anti-inflammatory agents, Proc. Nutr. Soc., 69 (3), 273–278.

[8] Bakoyiannis, I., Daskaloupoulou, A., Pergialiotis, V., and Perrea, D., 2019, Phytochemicals and cognitive health: Are flavonoids doing the trick?, Biomed. Pharmacother., 109, 1488–1497.

[9] Hatahet, T., Morille, M., Hommos, A., Devoisselle, J.M., Müller, R.H., and Bégu, S., 2016, Quercetin topical application, from conventional dosage forms to nanodosage forms, Eur. J. Pharm. Biopharm., 108, 41–53.

[10] Hatahet, T., Morille, M., Hommoss, A., Dorandeu, C., Müller, R.H., and Bégu, S., 2016, Dermal quercetin smartCrystalsÒ: Formulation development, antioxidant activity and cellular safety, Eur. J. Pharm. Biopharm., 102, 51–63.

[11] Rho, H.S., Ghimeray, A.K., Yoo, D.S., Ahn, S.M., Kwon, S.S., Lee, K.H., Cho, D.H., and Cho, J.Y., 2011, Kaempferol and kaempferol rhamnosides with depigmenting and anti-inflammatory properties, Molecules, 16 (4), 3338–3344.

[12] Nagula, R.L., and Wairkar, S., 2019, Recent advances in topical delivery of flavonoids: A review, J. Controlled Release, 296, 190–201.

[13] Fan, M., Ding, H., Zhang, G., Hu, X., and Gong, D., 2019, Relationships of dietary flavonoid structure with its tyrosinase inhibitory activity and affinity, LWT Food Sci. Technol., 107, 25–34.

[14] Tu, W., Xu, X., Pheng, L., Zhong, S., Zhang, W., Soudarapandian, M.M., Belal, C., Wang, M., Jia, N., Zhang, W., Lew, F., Chan, S.L., Chen, Y., and Lu, Y., 2010, DAPK1 interaction with NMDA receptor NR2B subunits mediates brain damage in stroke, Cell, 140 (2), 222–234.

[15] Chen, Z., Picaud, S., Filippakopoulos, P., D’Angiolella, V., and Bullock, A.N., 2019, Structural basis for recruitment of DAPK1 to the KLHL20 E3 ligase, Structure, 27 (9), 1395–1404.e4.

[16] Xu, L.Z., Li, B.Q., and Jia, J.P., 2019, DAPK1: A novel pathology and treatment target for Alzheimer’s disease, Mol. Neurobiol., 56 (4), 2838–2844.

[17] Park, G.B., Jeong, J.Y., and Kim, D., 2019, Gliotoxin enhances autophagic cell death via the DAPK1-TAp63 signaling pathway in paclitaxel-resistant ovarian cancer cells, Mar. Drugs, 17 (7), 412.

[18] Wei, R., Zhang, L., Hu, W., Wu, J., and Zhang, W., 2019, Long non-coding RNA AK038897 aggravates cerebral ischemia/reperfusion injury via acting as a ceRNA for miR-26a-5p to target DAPK1, Exp. Neurol., 314, 100–110.

[19] Singh, P., and Talwar, P., 2017, Exploring putative inhibitors of Death Associated Protein Kinase 1 (DAPK1) via targeting Gly-Glu-Leu (GEL) and Pro-Glu-Asn (PEN) substrate recognition motifs, J. Mol. Graphics Modell., 77, 153–167.

[20] Shoichet, B.K., Kuntz, I.D., and Bodian, D.L., 1992, Molecular docking using shape descriptor, J. Comput. Chem., 13 (3), 380–397.

[21] Pinzi, L., and Rastelli, G., 2019, Molecular docking: Shifting paradigms in drug discovery, Int. J. Mol. Sci., 20 (18), 4331.

[22] Torres, P.H.M., Sodero, A.C.R., Jofily, P., and Silva Jr., F.P., 2019, Key topics in molecular docking for drug design, Int. J. Mol. Sci., 20 (18), 4574.

[23] Li, J., Fu, A., and Zhang, L., 2019, An overview of scoring functions used for protein–ligand interactions in molecular docking, Interdiscip. Sci., 11 (2), 320–328.

[24] Turkan, F., Cetin, A., Taslimi, P., Karaman, M., and Gulçin, I., 2019, Synthesis, biological evaluation and molecular docking of novel pyrazole derivatives as potent carbonic anhydrase and acetylcholinesterase inhibitors, Bioorg. Chem., 86, 420–427.

[25] Saikia, S., and Bordoloi, M., 2019, Molecular docking: Challenges, advances and its use in drug discovery perspective, Curr. Drug Targets, 20 (5), 501–521.

[26] Pettersen, E.F., Goddard, T.D., Huang, C.C., Couch, G.S., Greenblatt, D.M., Meng, E.C., and Ferrin, T.E., 2004, UCSF Chimera-A visualization system for exploratory research and analysis, J. Comput. Chem., 25 (13), 1605–1612.

[27] Korb, O., Stützle, T., and Exner, T.E., 2006, PLANTS: Application of ant colony optimization to structure-based drug design, Lect. Notes Comput. Sci., 4150, 247–258.

[28] Hodgkin, E.E., and Richards, W.G., 1987, Molecular similarity based on electrostatic potential and electric field, Int. J. Quantum Chem., 32 (S14), 105–110.

[29] Humphrey, W., Dalke, A., and Schulten, K., 1996, VMD-Visual molecular dynamics, J. Mol. Graphics, 14 (1), 33–38.

[30] de Leeuw, S.W., Perram, J.W., and Smith, E.R., 1980, Simulation of electrostatic systems in periodic boundary conditions. I. Lattice sums and dielectric constants, Proc. R. Soc. London, Ser. A, 373 (1752), 27–56.

[31] Silva, T.F.D., Vila-Viçosa, D., Reis, P.B.P.S., Victor, B.L., Diem, M., Oostenbrink, C., and Machuqueiro, M., 2018, The impact of using single atomistic long-range cutoff schemes with the GROMOS 54A7 force field, J. Chem. Theory Comput., 14 (11), 5823–5833.

[32] Berendsen, H.J.C., van der Spoel, D., and van Drunen, R., 1995, GROMACS: A message-passing parallel molecular dynamics implementation, Comput. Phys. Commun., 91 (1-3), 43–56.

[33] van Gunsteren, W.F., and Berendsen, H.J.C., 1977, Algorithms for macromolecular dynamics and constraint dynamics, Mol. Phys., 34 (5), 1311–1327.

[34] Darden, T., York, D., and Pedersen, L., 1993, Particle mesh Ewald: An N⋅log(N) method for Ewald sums in large systems, J. Chem. Phys., 98 (12), 10089.

[35] Bash, P.A., Singh, U.C., Langridge, R., and Kollman, P.A., 1987, Free energy calculation by computer simulation, Science, 236 (4801), 564–568.

[36] Brandsal, B.O., Österberg, F., Almlöf, M., Feierberg, I., Luzhkov, V.B., and Åqvist, J., 2003, Free energy calculations and ligand binding, Adv. Protein Chem., 66, 123–158.

DOI: https://doi.org/10.22146/ijc.56087