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Research Articles

Identification of molecular descriptors for design of novel Isoalloxazine derivatives as potential Acetylcholinesterase inhibitors against Alzheimer’s disease

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Pages 1729-1742 | Received 21 Mar 2016, Accepted 18 May 2016, Published online: 28 Jul 2016

References

  • Ambure, P., Kar, S., & Roy, K. (2014). Pharmacophore mapping-based virtual screening followed by molecular docking studies in search of potential acetylcholinesterase inhibitors as anti-Alzheimer’s agents. Biosystems, 116, 10–20. doi:10.1016/j.biosystems.2013.12.002
  • Barnard, E. A. (1974). Neuromuscular transmission – Enzymatic destruction of acetylcholine. In J. I. Hubbard (Ed.), The peripheral nervous system (Vol. 1, pp. 201–224). New York, NY: Springer.
  • Barthel, A., Trieschmann, L., Ströhl, D., Kluge, R., Böhm, G., & Csuk, R. (2009). Synthesis of dimeric quinazolin-2-one, 1,4-benzodiazepin-2-one, and isoalloxazine compounds as inhibitors of amyloid peptides association. Archiv der Pharmazie – Chemistry in Life Sciences, 342, 445–452. doi:10.1002/ardp.200800196
  • Bhatiya, R., Vaidya, A., Kashaw, S. K., Jain, A. K., & Agrawal, A. K. (2011). QSAR analysis of furanone derivatives as potential COX-2 inhibitors: kNN MFA approach. Journal of Saudi Chemical Society, 18, 977–984. doi:10.1016/j.jscs.2011.12.002
  • Cereto-Massague, A., Guasch, L., Valls, C., Mulero, M., Pujadas, G., & Garcia-Vallve, S. (2012). DecoyFinder: An easy-to-use python GUI application for building target-specific decoy sets. Bioinformatics, 28, 1661–1662. doi:10.1093/bioinformatics/bts249
  • Chadha, N., Tiwari, A. K., Kumar, V., Lal, S., Milton, M. D., & Mishra, A. K. (2015). Oxime-dipeptides as anticholinesterase, reactivator of phosphonylated-serine of AChE catalytic triad: Probing the mechanistic insight by MM-GBSA, dynamics simulations and DFT analysis. Journal of Biomolecular and Structure Dynamics, 33, 978–990. doi:10.1080/07391102.2014.921793
  • Cheung, J., Rudolph, M. J., Burshteyn, F., Cassidy, M. S., Gary, E. N., Love, J., … Height, J. J. (2012). Structures of human acetylcholinesterase in complex with pharmacologically important ligands. Journal of Medicinal Chemistry, 55, 10282–10286. doi:10.1021/jm300871x
  • da Silva Gonçalves, A., França, T. C., & Vital de Oliveira, O. (2016). Computational studies of acetylcholinesterase complexed with fullerene derivatives: A new insight for Alzheimer disease treatment. Journal of Biomolecular and Structure Dynamics, 34, 1307–1316. doi:10.1080/07391102.2015.1077345
  • de Almeida, J. S., Cuya Guizado, T. R., Guimarães, A. P., Ramalho, T. C., Gonçalves, A. S., de Koning, M. C., & França, T. C. (2016). Docking and molecular dynamics studies of peripheral site ligand-oximes as reactivators of sarin-inhibited human acetylcholinesterase. Journal of Biomolecular and Structure Dynamics, 9, 1-11. Retrieved from http://www.tandfonline.com/doi/full/10.1080/07391102.2015.1124807
  • Elumalai, P., Liu, H. L., Zhao, J. H., Chen, W., Lin, D. S., Chuang, C. K., … Ho, Y. (2012). Pharmacophore modeling, virtual screening and docking studies to identify novel HNMT inhibitors. Journal of the Taiwan Institute of Chemical Engineers, 43, 493–503. doi:10.1016/j.jtice.2012.01.004
  • Ferrari, A. M., Degliesposti, G., Sgobba, M., & Rastelli, G. (2007). Validation of an automated procedure for the prediction of relative free energies of binding on a set of aldose reductase inhibitors. Bioorganic and Medicinal Chemistry, 15, 7865–7877. doi:10.1016/j.bmc.2007.08.019
  • Froede, H. C., & Wilson, I. B. (1971). Acetycholinesterase. In P. D. Boyer (Ed.), The enzymes (Vol. 5, pp. 87-114). New York, NY: Academic Press.
  • Giacoppo, J. O., C C França, T., Kuča, K., Cunha, E. F., Abagyan, R., Mancini, D. T., & Ramalho, T. C. (2015). Molecular modeling and in vitro reactivation study between the oxime BI-6 and acetylcholinesterase inhibited by different nerve agents. Journal of Biomolecular and Structure Dynamics, 33, 2048–2058. doi:10.1080/07391102.2014.989408
  • 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, 891–913. doi:10.1016/S0022-2836(03)00610-7
  • Goyal, M., Grover, S., Dhanjal, J. K., Goyal, S., Tyagi, C., & Grover, A. (2014). Molecular modelling studies on flavonoid derivatives as dual site inhibitors of human acetyl cholinesterase using 3D-QSAR, pharmacophore and high throughput screening approaches. Medicinal Chemistry Research, 23, 2122–2132. doi:10.1007/s00044-013-0810-2
  • Graham, D. W., & Rogers, E. F. (1979). U.S. Patent No. 4,173,631. Washington, DC: U.S. Patent and Trademark Office.
  • Grover, A., Shandilya, A., Agrawal, V., Bisaria, V. S., & Sundar, D. (2012). Computational evidence to inhibition of human acetyl cholinesterase by withanolide a for Alzheimer treatment. Journal of Biomolecular Structure and Dynamics, 29, 651–662. doi:10.1080/07391102.2012.10507408
  • Hess, B., Kutzner, C., van der Spoel, D., & Lindahl, E. (2008). GROMACS 4: Algorithms for highly efficient, load-balanced, and scalable molecular simulation. Journal of Chemical Theory and Computation, 4, 435–447. doi:10.1021/ct700301q
  • Januar, H. I., Dewi, A. S., Marraskuranto, E., & Wikanta, T. (2012). In silico study of fucoxanthin as a tumor cytotoxic agent. Journal of Pharmacy and Bioallied Sciences, 4, 56–59. doi:10.4103/0975-7406.92733
  • Kanhed, A. M., Sinha, A., Machhi, J., Tripathi, A., Parikh, Z. S., Pillai, P. P., … Yadav, M. R. (2015). Discovery of isoalloxazine derivatives as a new class of potential anti-Alzheimer agents and their synthesis. Bioorganic Chemistry, 61, 7–12. doi:10.1016/j.bioorg.2015.05.005
  • Kollman, P. A., Massova, I., Reyes, C., Kuhn, B., Huo, S., Chong, L., …Cheatham, T. E. (2000). Calculating structures and free energies of complex molecules: Combining molecular mechanics and continuum models. Accounts of Chemical Research, 33, 889–897. doi:10.1021/ar000033j
  • Kuca, K., Soukup, O., Maresova, P., Korabecny, J., Nepovimova, E., Klimova, B., … França, T. C. (2016). Current approaches against Alzheimer’s disease in clinical trials. Journal of the Brazilian Chemical Society, 27, 641–649. Retrieved from http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-50532016000400641
  • Kuhn, B., & Kollman, P. A. (2000). Binding of a diverse set of ligands to avidin and streptavidin: An accurate quantitative prediction of their relative affinities by a combination of molecular mechanics and continuum solvent models. Journal of Medicinal Chemistry, 43, 378–3791. doi:10.1021/jm000241 h
  • Kumar, V., Chadha, N., Tiwari, A. K., Sehgal, N., & Mishra, A. K. (2014). Prospective atom-based 3D-QSAR model prediction, pharmacophore generation, and molecular docking study of carbamate derivatives as dual inhibitors of AChE and MAO-B for Alzheimer’s disease. Medicinal Chemistry Research, 23, 1114–1122. doi:10.1007/s00044-013-0704-3
  • Kumari, R., Kumar, R., Open Source Drug Discovery Consortium, & Lynn, A. (2014). g_mmpbsa – A GROMACS tool for high-throughput MM-PBSA calculations. Journal of Chemical Information and Modeling, 54, 1951–1962. doi:10.1021/ci500020m
  • Laskowski, R. A., & Swindells, M. B. (2011). LigPlot+: Multiple ligand–protein interaction diagrams for drug discovery. Journal of Chemical Information and Modeling, 51, 2778–2786. doi:10.1021/ci200227u
  • Lee, S., & Barron, M. G. (2015). Development of 3D-QSAR model for acetylcholinesterase inhibitors using a combination of fingerprint, molecular docking, and structure-based pharmacophore approaches. Toxicological Sciences, 148, 60–70. doi:10.1093/toxsci/kfv160
  • Manavalan, P., Taylor, P., & Curtis Johnson, W. Jr. (1985). Circular dichroism studies of acetylcholine sterase conformation. Comparison of the 11 S and 5.6 S species and the differences induced by inhibitory ligands. Biochimica et Biophysica Acta (BBA) – Protein Structure and Molecular Enzymology, 829, 365–370. doi:10.1016/0167-4838(85)90246-8
  • Martis, E. A., Chandarana, R. C., Shaikh, M. S., Ambre, P. K., D’Souza, J. S., Iyer, K. R., … Pissurlenkar, R. R. (2015). Quantifying ligand-receptor interactions for gorge-spanning acetylcholinesterase inhibitors for the treatment of Alzheimer’s disease. Journal of Biomolecular and Structure Dynamics, 33, 1107–1125. doi:10.1080/07391102.2014.931824
  • Mehta, M., Adem, A., & Sabbagh, M. (2012). New acetylcholinesterase inhibitors for alzheimer’s disease. International Journal of Alzheimer’s Disease, 2012, 728983. doi:10.1155/2012/728983
  • Mooser, G., & Sigman, D. S. (1974). Ligand binding properties of acetylcholinesterase determined with fluorescent probes. Biochemistry, 13, 2299–2307. doi:10.1021/bi00708a010
  • Morris, G. M., Huey, R., Lindstrom, W., Sanner, M. F., Belew, R. K., Goodsell, D. S., & Olson, A. J. (2009). AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. Journal of Computational Chemistry, 30, 2785–2791. doi:10.1002/jcc.21256
  • Munoz-Torrero, D. (2008). Acetylcholinesterase inhibitors as disease-modifying therapies for Alzheimers disease. Current Medicinal Chemistry, 15, 2433–2455. doi:10.2174/092986708785909067
  • Nachmansohn, D., & Wilson, I. B. (1951). The enzymic hydrolysis and synthesis of acetylcholine. In F. F. Nord (Ed.), Advances in enzymology and related subjects of biochemistry (Vol. 12, pp. 259–339). New York, NY: Interscience.
  • Ojha, P. K., Mitra, I., Das, R. N., & Roy, K. (2011). Further exploring rm2 metrics for validation of QSPR models. Chemometrics and Intelligent Laboratory Systems, 107, 194–205. doi:10.1016/j.chemolab.2011.03.011
  • Ramalho, T. C., de Castro, A. A., Silva, D. R., Cristina Silva, M., Franca, T. C., Bennion, B. J., & Kuca, K. (2016). Computational enzymology and organophosphorus degrading enzymes: Promising approaches toward remediation technologies of warfare agents and pesticides. Current Medicinal Chemistry, 23, 1041–1061. doi:10.2174/0929867323666160222113504
  • Roy, K., Chakraborty, P., Mitra, I., Ojha, P. K., Kar, S., & Das, R. N. (2013). Some case studies on application of “r(m)2” metrics for judging quality of quantitative structure-activity relationship predictions: Emphasis on scaling of response data. Journal of Computational Chemistry, 34, 1071–1082. doi:10.1002/jcc.23231
  • Roy, K., Kar, S., & Ambure, P. (2015). On a simple approach for determining applicability domain of QSAR models. Chemometrics and Intelligent Laboratory Systems, 145, 22–29. doi:10.1016/j.chemolab.2015.04.013
  • Schüttelkopf, A. W., & van Aalten, D. M. (2004). PRODRG: A tool for high-throughput crystallography of protein–ligand complexes. Acta Crystallographica Section D Biological Crystallography, 60, 1355–1363. doi:10.1107/S0907444904011679
  • Valasani, K. R., Chaney, M. O., Day, V. W., & ShiDu Yan, S. (2013). Acetylcholinesterase inhibitors: Structure based design, synthesis, pharmacophore modeling, and virtual screening. Journal of Chemical Information and Modeling, 53, 2033–2046. doi:10.1021/ci400196z
  • Venken, T., Krnavek, D., Münch, J., Kirchhoff, F., Henklein, P., De Maeyer, M., & Voet, A. (2011). An optimized MM/PBSA virtual screening approach applied to an HIV-1 gp41 fusion peptide inhibitor. Proteins: Structure, Function, and Bioinformatics, 79, 3221–3235. doi:10.1002/prot.23158
  • VLife, Molecular Design Suite (4.4), VLife Sciences Technologies Pvt. Ltd. (2015). Retrieved from www.Vlifesciences.com
  • Wallach, I., & Lilien, R. (2011). Virtual decoy sets for molecular docking benchmarks. Journal of Chemical Information and Modeling, 51, 196–202. doi:10.1021/ci100374f
  • Wilson, I. B., & Quan, C. (1958). Acetylcholinesterase studies on molecular complementariness. Archives of Biochemistry and Biophysics, 73, 131–143. doi:10.1016/0003-9861(58)90248-0
  • Wolber, G., & Langer, T. (2005). LigandScout: 3-D pharmacophores derived from protein-bound ligands and their use as virtual screening filters. Journal of Chemical Information and Modeling, 45, 160–169. doi:10.1021/ci049885e
  • Yang, S. Y. (2010). Pharmacophore modeling and applications in drug discovery: Challenges and recent advances. Drug Discovery Today, 15, 444–450. doi:10.1016/j.drudis.2010.03.013
  • Zhang, S. (2011). Computer-aided drug discovery and development. Methods in Molecular Biology, 716, 23–38. doi:10.1007/978-1-61779-012-6_2

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