MODELING AND STRUCTURAL ANALYSIS OF ACETYLCHOLINESTERASE ENZYME OF FISHES
Objective: Computational studies on fish brain acetylcholinesterase were conducted, expanding our views and for a deeper understanding of the activity of the fish acetylcholinesterase enzyme.
Methods: Physico-chemical properties of the fish acetylcholinesterase enzyme were studied. Homology model of the acetylcholinesterase enzyme was predicted, validated its quality and active sites were predicted. The amino acid frequency in the active sites was also compared. Similarly, the secondary structure of the sequences was predicted and compared. Phylogenetic analysis was performed by the neighbour joining tree method.
Results: Among the selected fish species stability of acetylcholinesterase was found in fish species namely Esox lucius. The negative GRAVY score value of enzyme in all the fish species ensured better interaction and activity in the aqueous phase. It was found that the molecular weight of the acetylcholinesterase enzyme ranged between 9113 and 15991 Da. Iso-electric (pI) of acetylcholinesterase was found to be acidic in nature. GOR IV was used to predict the secondary structure of acetylcholinesterase, which showed that random coil was dominated. Neighbor joining tree of the enzyme showed that fish species named Amphiprion ocellaris as the most divergent species, while the species Oreochromis niloticus is the most primitive one.
Conclusion: Acetlycholinesterase enzyme of Esox lucius was found to be the best compared to the other species, which possess a high number of active sites with Ile, Set and Glu rich active sites.
2. Hasinoff BB. Kinetics of acetylthiocholine binding to electric eel acetylcholinesterase in glycerol/water solvents of increased viscosity. Evidence for a diffusion-controlled reaction. Biochem Biophys Acta Protein Struct Mol Enzymol 1982;704:52-8.
3. Manjunatha KS, Manu CP, Satyanarayan, Nayak KN, Vinay MS, Vineetha, et al. Acetylcholinesterase inhibitory effect of 3-(1h-indol-3-yl)-1, 3-diphenylpropan-1-one derivatives. Asian J Pharm Clin Res 2017;10:83-6.
4. Malathi S, Vidyashree HM, Ravindran R. Restoration of memory and acetylcholinesterase activity by michelia champaca in chronically noise-stressed Wistar Albino rats. Asian J Pharm Clin Res 2016;9:210-4.
5. Sussman JL, Harel M, Frolow F, Oefner C, Goldman A, Toker L, et al. Atomic structure of acetylcholinesterase from Torpedo californica: a prototypic acetylcholine-binding protein. Science 1991;253:872–9.
6. Raves ML, Harel M, Pang YP, Silman I, Kozikowski AP, Sussman JL. Structure of acetylcholinesterase complexed with the nootropic alkaloid (?)-huperzine A. Nat Struct Mol Biol 1997;4:57–63.
7. Nolte HJ, Rosenberry TL, Neumann E. Effective charge on acetylcholinesterase active sites determined from the ionic strength dependence of association rate constants with cationic ligands. Biochemistry 1980;1916:3705–11.
8. Dougherty DA, Stauffer DA. Acetylcholine binding by a synthetic receptor: implications for biological recognition. Science 1990;250:1558–60.
9. Taylor BK, Holloway D, Printz MP. A unique central cholinergic deficit in the spontaneously hypertensive rat: physostigmine reveals bradycardia associated with sensory stimulation. J Pharmacol Exp Ther 1994;268:1081–90.
10. Saitou N, Nei M. The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol Biol Evol 1987;4:406-25.
11. Gasteiger E, Gattiker A, Hoogland C, Ivanyi I, Appel RD, Bairoch A. ExPASy: the proteomics server for in-depth protein knowledge and analysis. Nucleic Acids Res 2003;31:3784-8.
12. Garnier J, Gibrat JF, Robson B. GOR method for predicting protein secondary structure from amino acid sequence. Method Enzymol 1996;266:540-53.
13. Schwede T, Kopp J, Guex N, Peitsch MC. SWISS-MODEL: an automated protein homology-modeling server. Nucleic Acids Res 2003;31:3381-5.
14. Wiederstein M, Sippl MJ. ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res 2007;35:407-10.
15. Dundas J, Ouyang Z, Tseng J, Binkowski A, Turpaz Y, Liang J. CASTp: computed atlas of surface topography of proteins with the structural and topographical mapping of functionally annotated residues. Nucleic Acids Res 2006;34:116-8.
16. Taylor P, Radic Z. The cholinesterases: from genes to proteins. Annu Rev Pharmacol Toxicol 1994;34:281–320.
17. Lemmon AR, Moriarty EC. The importance of proper model assumption in bayesian phylogenetics. Syst Biol 2004;53:265-77.
18. Ikai AJ. Thermostability and aliphatic index of globular proteins. J Biochem 1980;88:1895-8.
19. Kyte J, Doolittle RF. A simple method for displaying the hydropathic character of a protein. J Mol Biol 1982;157:105-32.
20. Chothia C, Lesk AM. The relation between the divergence of sequence and structure in proteins. EMBO J 1986;54:823-6.
This work is licensed under a Creative Commons Attribution 4.0 International License.