QSAR applications during last decade on inhibitors of acetylcholinesterase in Alzheimer's disease

Mini-Reviews in Medicinal Chemistry

Volumn 12, Issue 10, 2012, Pages 936-946

  Wong, K Y ^a   Duchowicz, P R ^a   Mercader, A G ^b   Castro, E A ^a  

^a INSTITUTO DE INVESTIGACIONES FISICOQUÍMICAS TEÓRICAS Y APLICADAS INIFTA   (Argentina)

^b UNIVERSIDAD DE BUENOS AIRES   (Argentina)

Author keywords

Acetylcholinesterase; Alzheimer's disease; CoMFA; CoMSIA; Medicinal chemistry; Molecular descriptors; QSAR theory

Indexed keywords

AMLODIPINE BESYLATE; BENZODIAZEPINE; CARBAMIC ACID; CHLORDIAZEPOXIDE; CHOLINESTERASE INHIBITOR; DIAZEPAM; DONEPEZIL; GALANTAMINE; HYDRALAZINE; KETONE; MEVINOLIN; NIFEDIPINE; PHYSOSTIGMINE; RIVASTIGMINE; SIMVASTATIN; TACRINE;

ALZHEIMER DISEASE; ARTICLE; CHEMICAL STRUCTURE; COMPARATIVE STUDY; DRUG POTENCY; DRUG SCREENING; HUMAN; METHODOLOGY; QUANTITATIVE STRUCTURE ACTIVITY RELATION;

ACETYLCHOLINESTERASE; ALZHEIMER DISEASE; ANIMALS; CHOLINESTERASE INHIBITORS; HUMANS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP;

EID: 84866466056     PISSN: 13895575     EISSN: 18755607     Source Type: Journal    
DOI: 10.2174/138955712802762365     Document Type: Article

References (106)

1. Goedert, M., Spillantini, M. G. A Century of Alzheimer's Disease. Science, 2006, 314, 777-781.
2. McDowell, I. Alzheimer's Disease: Insights from Epidemiology. Aging: Milano, 2001, 13, 143-162.
3. Schmidt, R., Neff, F., Lampl, C., Benke, T., Anditsch, M., Bancher, C., Dal-Bianco, P., Reiseker, F., Marksteiner, J., Rainer, M., Kapeller, P., Dodel, R. Therapy of Alzheimer's disease: current status and future development. Neuropsychiatrie, 2008, 22, 153-171.
4. Haq, Z.U., Uddin, R. In: Alzheimer's Disease Pathogenesis-Core Concepts, Shifting Paradigms and Therapeutic Targets. De La Monte, S., Ed.; InTech, http://www.intechweb.org/, 2011.
5. Alcala, M.D.M., Vivas, N. M., Hospital, S., Camps, P., Munoz-Torrero, D., Badia, A. Characterisation of the anticholinesterase activity of two new tacrine-huperzine A hybrids. Neuropharmacology, 2003, 44, 749-755.
6. Quinn, D.M., Feaster, S. R., Nair, H. K., Baker, N. A., Radic, Z., Taylor, P. Delineation and decomposition of energies involved in quaternary ammonium binding in the active site of acetylcholinesterase. J. Am. Chem. Soc., 2000, 122, 2975-2980.
7. Bartus, R.T., Dean III L. D., Beer, B., Lippa, A. S. The cholinergic hypothesis of geriatric memory dysfunction. Science, 1982, 217, 408-417.
8. Gualtieri, F., Dei, S., Manetti, D., Romanelli, M. N., Scapecchi, S., Teodori, E. The medicinal chemistry of Alzheimer's and Alzheimer-like diseases with emphasis on the cholinergic hypothesis. Farmaco, 1995, 50, 489-503.
9. Racchi, M., Mazzucchelli, M., Porrello, E., Lanni, C., Govoni, S. Acetylcholinesterase inhibitors: novel activities of old molecules. Pharmacol. Res., 2004, 50, 441-451.
10. Hansch, C., Leo, A. Exploring QSAR. Fundamentals and Applications in Chemistry and Biology. American Chemical Society: Washington, D. C., 1995.
11. Kubinyi, H. QSAR: Hansch Analysis and Related Approaches. Wiley-Interscience: New York, 2008.
12. Puzyn, T., Leszczynski, J., Cronin, M. T. Recent Advances in QSAR Studies: Methods and Applications. First Edition ed. Springer: New York, 2009.
13. Trinajstic, N. Chemical Graph Theory. CRC Press: Boca Raton (FL), 1992.
14. Katritzky, A.R., Lobanov, V. S., Karelson, M. QSPR: the correlation and quantitative prediction of chemical and physical properties from structure. Chem. Soc. Rev., 1995, 24, 279-287.
15. Diudea, M.V. QSPR/QSAR Studies by Molecular Descriptors. Nova Science Publishers: New York, 2001.
16. Todeschini, R., Consonni, V. Molecular Descriptors for Chemoinformatics. Wiley-VCH: Weinheim, 2009.
17. Golbraikh, A., Tropsha, A. Beware of q2! J. Mol. Graphics Modell., 2002, 20, 269-276.
18. Hawkins, D.M., Basak, S. C., Mills, D. Assessing Model Fit by Cross Validation. J. Chem. Inf. Model., 2003, 43, 579-586.
19. Goodarzi, M., Duchowicz, P. R., Wu, C. H., Fernández, F. M., Castro, E. A. New Hybrid Genetic Based Support Vector Regression as QSAR Approach for Analyzing Flavonoids-GABA(A) Complexes. J. Chem. Inf. Model., 2009, 49, 1475-1485.
20. Chicu, S.A., Putz, M. V. Köln-Timişoara Molecular Activity Combined Models toward Interspecies Toxicity Assessment Int. J. Mol. Sci., 2009, 10, 4474-4497.
21. Putz, M.V., Putz, A. M., Lazea, M., Lenciu, L., Chiriac, A. Quantum-SAR Extension of the Spectral-SAR Algorithm. Application to Polyphenolic Anticancer Bioactivity Int. J. Mol. Sci., 2009, 10, 1193-1214.
22. Lacrǎmǎ, A.M., Putz, M. V., Ostafe, V. A Spectral-SAR Model for the Anionic-Cationic Interaction in Ionic Liquids: Application to Vibrio fischeri Ecotoxicity. Int. J. Mol. Sci., 2007, 8, 842-863.
23. Putz, M.V., Ionaşcu, C., Putz, A. M., Ostafe, V. Alert-QSAR. Implications for Electrophilic Theory of Chemical Carcinogenesis. Int. J. Mol. Sci., 2011, 12, 5098-5134.
24. Putz, M.V. Residual-QSAR. Implications for Genotoxic Carcinogenesis. Chem. Cent. J., 2011, 5, doi: 10.1186/1752-1153X-1185-1129.
25. Akula, N., Lecanu, L., Greeson, J., Papadopoulos, V. 3D QSAR studies of AChE inhibitors based on molecular docking scores and CoMFA. Bioorg. Med. Chem. Lett., 2006, 16, 6277-6280.
26. Rawal, R.K.; Prabhakar, Y.S.; Katti, S.B.; De Clercq, E. 2-(Aryl)-3-furan-2-ylmethyl-thiazolidin-4-ones as selective HIV-RT Inhibitors. Bioorg Med Chem, 2005, 13, (24), 6771-6776.
27. Yao, X.; Liu, H.; Zhang, R.; Liu, M.; Hu, Z.; Panaye, A.; Doucet, J.P.; Fan, B. QSAR and classification study of 1,4-dihydropyridine calcium channel antagonists based on least squares support vector machines. Mol Pharm, 2005, 2, (5), 348-356.
28. Dapson, R.W. Dye-tissue interactions: mechanisms, quantification and bonding parameters for dyes used in biological staining. Biotech Histochem, 2005, 80, (2), 49-72.
29. Rodriguez-Morales, S.; Compadre, R.L.; Castillo, R.; Breen, P.J.; Compadre, C.M. 3D-QSAR, synthesis, and antimicrobial activity of 1-alkylpyridinium compounds as potential agents to improve food safety. Eur J Med Chem, 2005, 40, (9), 840-849.
30. Maurici, D.; Aardema, M.; Corvi, R.; Kleber, M.; Krul, C.; Laurent, C.; Loprieno, N.; Pasanen, M.; Pfuhler, S.; Phillips, B.; Prentice, D.; Sabbioni, E.; Sanner, T.; Vanparys, P. Carcinogenicity. Altern Lab Anim, 2005, 33 Suppl 1, 177-182.
31. Fernández, M., Carreiras, M. C., Marco, J. L., Caballero, J. Modeling of acetylcholinesterase inhibition by tacrine analogs using Bayesian-regularized Genetic Neral Networks and ensemble averaging. J. Enzym. Inhib. Med. Ch., 2006, 21, 647-661.
32. Dragon Milano Chemometrics and QSAR Research Group, http://michem.disat.unimib.it/chm.
33. Zuang, V.; Alonso, M.A.; Botham, P.A.; Eskes, C.; Fentem, J.; Liebsch, M.; van de Sandt, J.J. Skin irritation and corrosion. Altern Lab Anim, 2005, 33 Suppl 1, 35-46.
34. Jung, M., Tak, J., Lee, Y. N., Jung, Y. G. Quantitative structureactivity relationship (QSAR) of tacrine derivatives against acetylcholinesterase (AChE) activity using variable selections. Bioorg. Med. Chem. Lett., 2007, 17, 1082-1090.
35. Vedani, A.; Dobler, M.; Lill, M.A. Virtual test kits for predicting harmful effects triggered by drugs and chemicals mediated by specific proteins. Altex, 2005, 22, (3), 123-134.
36. Figueiredo, L.J.; Garrido, F.M.; Kunisawa, V.Y.; Aboim, C.E.; Licks, O.B. A chemometric study of phosphodiesterase 5 inhibitors. J Mol Graph Model, 2005.
37. Bak, A.; Polanski, J. A 4D-QSAR study on anti-HIV HEPT analogs. Bioorg Med Chem, 2006, 14, (1), 273-279.
38. Jojart, B.; Martinek, T.A.; Marki, A. The 3D structure of the binding pocket of the human oxytocin receptor for benzoxazine antagonists, determined by molecular docking, scoring functions and 3D-QSAR methods. J Comput Aided Mol Des, 2005, 19, (5), 341-356.
39. Riviere, J.E.; Brooks, J.D. Predicting skin permeability from complex chemical mixtures. Toxicol Appl Pharmacol, 2005, 208, (2), 99-110.
40. Saracoglu, M., Kandemirli, F. The Investigation of Structure-Activity Relationships of Tacrine Analogs: Electronic-Topological Method. Open Med. Chem. J., 2008, 2, 75-80.
41. Dimoglo, A.S., Shvets, N. M., Tetko, I. V., Livingstone, D. J. Electronic-topological investigation of the structureacetylcholinesterase inhibitor activity relationship in the series of nbenzylpiperidine derivatives. Quant. Struct.-Act. Rel., 2001, 20, 31-45.
42. Chen, N., Liu, C. K., Zhao, L. Z., Zhang, H. B. 3D-QSAR study of multi-target-directed AchE inhibitors based on autodocking. Med. Chem. Res., 2010, 1-12 doi:10.1007/s00044-00010-09516-x Key: citeulike:8597115.
43. Raska, I., Jr.; Toropov, A. QSAR of the testosterone binding globulin affinity by means of correlation weighting of local invariants of the graph of atomic orbitals. Bioorg Med Chem, 2005, 13, (24), 6830-6835.
44. Lin, G. Structure-reactivity Relationships as Probes to Acetylcholinesterase Inhibition Mechanisms by Aryl Carbamates. II. Hammett-Taft Cross-interaction Correlations. J. Chin. Chem. Soc.-Taip, 2004, 51, 423-429.
45. Lin, G., Liu, Y. C., Lin, Y. F., Wu, Y. G. Ortho Effects in Quantitative Structure-activity Relationships for Acetylcholinesterase Inhibition by Aryl Carbamates. J. Enzym. Inhib. Med. Ch., 2004, 19, 395-401.
46. Roy, K.K., Dixit, A., Saxena, A. K. An investigation of structurally diverse carbamates for acetylcholinesterase (AChE) inhibition using 3D-QSAR analysis. J. Mol. Graphics Modell., 2008, 27, 197-208.
47. Chadhaery, S.S., Roy, K. K., Saxena, A. K. Consensus Superiority of the Pharmacophore-Based Alignment, Over Maximum Common Substructure (MCS): 3D-QSAR Studies on Carbamates as Acetylcholinesterase Inhibitors. J. Chem. Inf. Model., 2009, 49, 1590-1601.
48. Rackova, L.; Firakova, S.; Kostalova, D.; Stefek, M.; Sturdik, E.; Majekova, M. Oxidation of liposomal membrane suppressed by flavonoids: Quantitative structure-activity relationship. Bioorg Med Chem, 2005, 13, (23), 6477-6484.
49. Khlebnikov, A.I.; Schepetkin, I.A.; Quinn, M.T. Quantitative structure-activity relationships for small non-peptide antagonists of CXCR2: Indirect 3D approach using the frontal polygon method. Bioorg Med Chem, 2005.
50. Liu, J.; Li, Y.; Pan, D.; Hopfinger, A.J. Predicting permeability coefficient in ADMET evaluation by using different membranesinteraction QSAR. Int J Pharm, 2005, 304, (1-2), 115-123.
51. Chadhaery, S.S., Roy, K. K., Shakya, N., Saxena, G., Sammi, S. R., Nazir, A., Nath, C., Saxena, A. K. Novel Carbamates as Orally Active Acetylcholinesterase Inhibitors Found to Improve Scopolamine-Induced Cognition Impairment: Pharmacophore-Based Virtual Screening, Synthesis and Pharmaycology. J. Med. Chem., 2010, 53, 6490-6505.
52. Kandemirli, F., Saraçoglu, M., Kovalishyn, V. Human Acetylcholinesterase Inhibitors: Electronic-Topological and Neural Network Approaches to the Structure-Activity Relationships study. Mini Rev. Med. Chem., 2005, 5, 479-487.
53. Haq, Z.U., Mahmood, U., Jehangir, B. Ligand-based 3D-QSAR Studies of Physostigmine Analogs as Acetylcholinesterase Inhibitors. Chem. Biol. Drug. Des., 2009, 74, 571-581.
54. Swaan, P.W.; Ekins, S. Reengineering the pharmaceutical industry by crash-testing molecules. Drug Discov Today, 2005, 10, (17), 1191-1200.
55. Araújo, J.Q., de Brito, M. A., Hoelz, L. V., de Alencastro, R. B., Castro, H. C., Rodrigues, C. R., Albuquerque, M. G. Receptordependent (RD) 3D-QSAR approach of a series of benzylpiperidine inhibitors of human acetylcholinesterase (HuAChE). Eur. J. Med. Chem., 2011, 46, 39-51.
56. Rogers, D., Hopfinger, A. J. Application of genetic function approximation to quantitative structure-activity-relationships and quantitative structure-property relationships. J. Chem. Inf. Comput. Sci., 1994, 34, 854-866.
57. Snyder, R.D.; Smith, M.D. Computational prediction of genotoxicity: room for improvement. Drug Discov Today, 2005, 10, (16), 1119-1124.
58. Pratuangdejkul, J.; Schneider, B.; Jaudon, P.; Rosilio, V.; Baudoin, E.; Loric, S.; Conti, M.; Launay, J.M.; Manivet, P. Definition of an uptake pharmacophore of the serotonin transporter through 3DQSAR analysis. Curr Med Chem, 2005, 12, (20), 2389-2406.
59. Netzeva, T.I.; Worth, A.; Aldenberg, T.; Benigni, R.; Cronin, M.T.; Gramatica, P.; Jaworska, J.S.; Kahn, S.; Klopman, G.; Marchant, C.A.; Myatt, G.; Nikolova-Jeliazkova, N.; Patlewicz, G.Y.; Perkins, R.; Roberts, D.; Schultz, T.; Stanton, D.W.; van de Sandt, J.J.; Tong, W.; Veith, G.; Yang, C. Current status of methods for defining the applicability domain of (quantitative) structure-activity relationships. The report and recommendations of ECVAM Workshop 52. Altern Lab Anim, 2005, 33, (2), 155-173.
60. Gerner, I.; Liebsch, M.; Spielmann, H. Assessment of the eye irritating properties of chemicals by applying alternatives to the Draize rabbit eye test: the use of QSARs and in vitro tests for the classification of eye irritation. Altern Lab Anim, 2005, 33, (3), 215-237.
61. Gieleciak, R.; Magdziarz, T.; Bak, A.; Polanski, J. Modeling robust QSAR. 1. Coding molecules in 3D-QSAR--from a point to surface sectors and molecular volumes. J Chem Inf Model, 2005, 45, (5), 1447-1455.
62. Yazal, J.E., Rao, S. N., Mehl, A., Slikker Jr., W. Prediction of Organophosphorus Acetylcholinesterase Inhibition Using Three-Dimensional Quantitative Structure-Activity Relationship (3DQSAR) Methods. Toxicol. Sci., 2001, 63, 223-232.
63. Clare, B.W.; Supuran, C.T. Predictive flip regression: a technique for QSAR of derivatives of symmetric molecules. J Chem Inf Model, 2005, 45, (5), 1385-1391.
64. Roy, K.; Leonard, J.T. QSAR analyses of 3-(4-benzylpiperidin-1-yl)-N-phenylpropylamine derivatives as potent CCR5 antagonists. J Chem Inf Model, 2005, 45, (5), 1352-1368.
65. Zhao, J.S., Wang, B., Dai, Z. X., Wang, X. D., Kong, L. R., Wang, L. S. 3D-quantitative structure-activity relationship study of organophosphate compounds. Chinese Sci. Bull., 2004, 49, 240-245.
66. Kuzmin, V.E., Muratov, E. N., Artemenko, A. G., Varlamova, E. V., Gorb, L., Wang, J., Leszczynski, J. Consensus QSAR Modeling of Phosphor-containing Chiral AChE Inhibitors. QSAR Comb. Sci., 2009, 28, 664-677.
67. Liu, A., Guang, H. M., Zhu, L. Y., Du, G. H., Lee, S. M. Y., Wang, Y. T. 3D-QSAR analysis of a new type of acetylcholinesterase inhibitors. Sci. China Ser. C 2007, 50, 726-730.
68. Wei, H.Y.; Tsai, K.C.; Lin, T.H. Modeling ligand-receptor interaction for some MHC class II HLA-DR4 peptide mimetic inhibitors using several molecular docking and 3D QSAR techniques. J Chem Inf Model, 2005, 45, (5), 1343-1351.
69. Sheng, R., Shen, Y. H., Lin, X., Luo, Y., Fan, Y. J., Li, J. Y., Xia, H. R., Hu, Y. Z. 3D-QSAR studies on AChE inhibitory activities of 2-phenoxy-indan-1-one derivatives. Chin. J. Med. Chem., 2007, 17, 348-353.
70. Shen, L.L., Liu, G. X., Tang, Y. Molecular docking and 3D-QSAR studies of 2-substituted 1-indanone derivatives as acetylcholinesterase inhibitors. Acta Pharm. Sinic., 2007, 28, 2053-2063.
71. Papa, E.; Villa, F.; Gramatica, P. Statistically validated QSARs, based on theoretical descriptors, for modeling aquatic toxicity of organic chemicals in Pimephales promelas (fathead minnow). J Chem Inf Model, 2005, 45, (5), 1256-1266.
72. Sharma, A., Mishra, A., Prajapat, R. P., Jain, S., Bhandari, A. QSAR analysis of indanone and aurone derivatives as acetylcholinesterase inhibitors. J. Chem. Pharm. Res., 2010, 2, 682-689.
73. Debnath, A.K. Application of 3D-QSAR techniques in anti-HIV-1 drug design--an overview. Curr Pharm Des, 2005, 11, (24), 3091-3110.
74. Burlet, S.; Pietrancosta, N.; Laras, Y.; Garino, C.; Quelever, G.; Kraus, J.L. Prospects for the resistance to HIV protease inhibitors: current drug design approaches and perspectives. Curr Pharm Des, 2005, 11, (24), 3077-3090.
75. Sippl, W., Contreras, J. M., Parrot, I., Rival, Y. M., Wermuth, C. G. Structure-based 3D QSAR and design of novel acetylcholinesterase inhibitors. J. Comput. Aided Mol. Des., 2001, 15, 395-410.
76. Lin, G.; Chen, G.H.; Yeh, S.C.; Lu, C.P. Probing the peripheral anionic site of acetylcholinesterase with quantitative structure activity relationships for inhibition by biphenyl-4-acyoxylate-4'-NButylcarbamates. J Biochem Mol Toxicol, 2005, 19, (4), 234-243.
77. Pasha, F.A.; Srivastava, H.K.; Singh, P.P. Comparative QSAR study of phenol derivatives with the help of density functional theory. Bioorg Med Chem, 2005, 13, (24), 6823-6829.
78. Gonzalez-Diaz, H.; Uriarte, E. Proteins QSAR with Markov average electrostatic potentials. Bioorg Med Chem Lett, 2005, 15, (22), 5088-5094.
79. Spassova, D.P., Singh, A. K. QSAR for acetylcholinesterase inhibition and toxicity of two classes of phosphoramidothioates. SAR QSAR Environ. Res., 2001, 11, 453-471.
80. Aptula, A.O.; Patlewicz, G.; Roberts, D.W. Skin sensitization: reaction mechanistic applicability domains for structure-activity relationships. Chem Res Toxicol, 2005, 18, (9), 1420-1426.
81. Medina-Franco, J.L.; Golbraikh, A.; Oloff, S.; Castillo, R.; Tropsha, A. Quantitative structure-activity relationship analysis of pyridinone HIV-1 reverse transcriptase inhibitors using the k nearest neighbor method and QSAR-based database mining. J Comput Aided Mol Des, 2005, 19, (4), 229-242.
82. Haq, Z.u., Wellenzohn, B., Tonmunphean, S., Khalid, A., Choudhary, M. I., Rode, B. M. 3D-QSAR Studies on Natural Acetylcholinesterase inhibitors of Sarcococca saligna by comparative molecular field analysis (CoMFA). Bioorg. Med. Chem. Lett., 2003, 13, 4375-4380.
83. Li, Y.; Liu, J.; Pan, D.; Hopfinger, A.J. A Study of the Relationship between Cornea Permeability and Eye Irritation Using Membrane-Interaction QSAR Analysis. Toxicol Sci, 2005, 88, (2), 434-446.
84. Chiou, S.Y., Lai, G. W., Tsai, Y. H., Lin, L. Y., Lin, G. Qsar for Acetylcholinesterase and Butyrylcholinesterase Inhibition by Cardiovascular Drugs and Benzodiazepines. Med. Chem. Res., 2005, 14, (5), 297-308.
85. Solomon, K.A., Sundararajan, S., Abirami, V. QSAR Studies on Naryl Derivative Activity Towards Alzheimer's Disease. Molecules, 2009, 14, 1448-1455.
86. Kotsikorou, E.; Song, Y.; Chan, J.M.; Faelens, S.; Tovian, Z.; Broderick, E.; Bakalara, N.; Docampo, R.; Oldfield, E. Bisphosphonate inhibition of the exopolyphosphatase activity of the Trypanosoma brucei soluble vacuolar pyrophosphatase. J Med Chem, 2005, 48, (19), 6128-6139.
87. Gupta, S., Fallarero, A., Vainio, M. J., Saravanan, P., Puranen, J. S., Järvinen, P., Johnson, M. S., Vuorela, P. M., Mohan, C. G. Molecular Docking Guided Comparative GFA, G/PLS, SVM and ANN Models of Structurally Diverse Dual Binding Site Acetylcholinesterase Inhibitors. Mol. Inf., 2011, 30, 689-706.
88. Lu, S.H., Wu, W. J., Liu, H. L., Zhao, J. H., Liu, K. T., Chuang, C. K., Lin, H. Y., Tsai, W. B., Ho, Y. The discovery of potential acetylcholinesterase inhibitors: A combination of pharmacophore modeling, virtual screening, and molecular docking studies. J. Biomed. Sci., 2011, 18, doi:10.1186/1423-0127-1118-1188.
89. Asadabadi, E.B., Abdolmaleki, P., Barkooie, S. M. H., Jahandideh, S., Rezaei, M. A. A combinatorial feature selection approach to describe the QSAR of dual site inhibitors of acetylcholinesterase. Comput. Biol. Med., 2009, 39, 1089-1095.
90. Keizers, P.H.; de Graaf, C.; de Kanter, F.J.; Oostenbrink, C.; Feenstra, K.A.; Commandeur, J.N.; Vermeulen, N.P. Metabolic regio- and stereoselectivity of cytochrome P450 2D6 towards 3,4-methylenedioxy-N-alkylamphetamines: in silico predictions and experimental validation. J Med Chem, 2005, 48, (19), 6117-6127.
91. Tsai, K.C., Chen, Y. C., Hsiao, N. W., Wang, C. K., Lin, C. L., Lee, Y. C., Li, M. Y., Wang, B. H. A comparison of different electrostatic potentials on prediction accuracy in CoMFA and CoMSIA studies. Eur. J. Med. Chem., 2010, 45, 1544-1551.
92. Ersmark, K.; Nervall, M.; Hamelink, E.; Janka, L.K.; Clemente, J.C.; Dunn, B.M.; Blackman, M.J.; Samuelsson, B.; Aqvist, J.; Hallberg, A. Synthesis of malarial plasmepsin inhibitors and prediction of binding modes by molecular dynamics simulations. J Med Chem, 2005, 48, (19), 6090-6106.
93. Procopio, A.; Alcaro, S.; Cundari, S.; De Nino, A.; Ortuso, F.; Sacchetta, P.; Pennelli, A.; Sindona, G. Molecular modeling, synthesis, and preliminary biological evaluation of glutathione-Stransferase inhibitors as potential therapeutic agents. J Med Chem, 2005, 48, (19), 6084-6089.
94. Gasparini, L., Racchi, M., Binetti, G., Trabucchi, M., Solerte, S. B., Alkon, D. Peripheral markers in testing pathophysiological hypotheses and diagnosing Alzheimer's disease. Faseb J., 1998, 12, 17-34.
95. Racchi, M., Govoni, S. Rationalizing a pharmacological intervention on the amyloid precursor protein metabolism. Trends. Pharmacol. Sci., 1999, 20, 418-423.
96. Fu, H.J., Li, W. M., Luo, J. L., Lee, N. T. K., Li, M. T., Tsim, K. W. K., Pang, T. P., Youdim, M. B. H., Han, Y. F. Promising anti-Alzheimer's dimer bis(7)-tacrine reduces β-amyloid generation by directly inhibiting BACE-1 activity. Biochem. Biophys. Res. Commun., 2008, 366, 631-636.
97. Fu, H., Li, W., Lao, Y., Luo, J., Lee, N. T., Kan, K. K., Tsang, H. W., Tsim, K. W., Pang, Y., Li, Z., Chang, D. C., Li, M., Han, Y. Bis(7)-tacrine attenudates beta amyloid-induced neuronal apoptosis by regulating L-type calcium channels. J. Neurochem., 2006, 98, 1400-1410.
98. Zhang, H.Y. One-compound-multiple-targets strategy to combat Alzheimer's disease. FEBS Lett., 2005, 79, 5260-5264.
99. Buehler, L.K. Advancing drug discovery-beyond design. PharmaGenomics, 2004, 4, 24-26.
100. Keith, C.T., Borisy, A. A., Stockwell, B. R. Multicomponent therapeutics for networked systems. Nat. Rev. Drug Discov., 2005, 4, 71-78.
101. Barnham, K.J., Masters, C. L., Bush, A. I. Neurodegenerative diseases and oxidative stress. Nat. Rev. Drug Discov., 2004, 3, 205-214.
102. Cummings, J.L. Alzheimer's Disease. N. Engl. J. Med., 2004, 351, 56-67.
103. Mattson, M.P. Pathways towards and away from Alzheimer's disease. Nature, 2004, 430, 631-639.
104. Brown, D.R., Kozlowski, H. Biological inorganic and bioinorganic chemistry of neurodegeneration based on prion and Alzheimer diseases. Dalton Trans., 2004, 13, 1907-1917.
105. Youdim, M.B., Buccafusco, J. J. Multi-functional drugs for various CNS targets in the treatment of neurodegenerative disorders. Trends Pharmacol. Sci., 2005, 26, 27-35.
106. Katayama, T., Imaizumi, K., Manabe, T., Hitomi, J., Kudo, T., Tohyama, M. Induction of neuronal death by ER stress in Alzheimer's disease. J. Chem. Neuroanat., 2004, 28, 67-78.