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Journal Abstract Search
322 related items for PubMed ID: 18630262
1. Construction of the pharmacophore model of acetylcholinesterase inhibitor. Zhu Y, Tong XY, Zhao Y, Chen H, Jiang FC. Yao Xue Xue Bao; 2008 Mar; 43(3):267-76. PubMed ID: 18630262 [Abstract] [Full Text] [Related]
2. [Construction and application of pharmacophore model of benzoylurea derivatives as beta-tubulin inhibitors]. Gao LM, Zhang SH, Yi H, Jiang JD, Song DQ. Yao Xue Xue Bao; 2010 Apr; 45(4):462-6. PubMed ID: 21355210 [Abstract] [Full Text] [Related]
3. Discovery of dual binding site acetylcholinesterase inhibitors identified by pharmacophore modeling and sequential virtual screening techniques. Gupta S, Fallarero A, Järvinen P, Karlsson D, Johnson MS, Vuorela PM, Mohan CG. Bioorg Med Chem Lett; 2011 Feb 15; 21(4):1105-12. PubMed ID: 21273074 [Abstract] [Full Text] [Related]
4. Molecular modeling, docking and ADMET studies applied to the design of a novel hybrid for treatment of Alzheimer's disease. da Silva CH, Campo VL, Carvalho I, Taft CA. J Mol Graph Model; 2006 Oct 15; 25(2):169-75. PubMed ID: 16413803 [Abstract] [Full Text] [Related]
5. Inhibition of acetylcholinesterase, beta-amyloid aggregation, and NMDA receptors in Alzheimer's disease: a promising direction for the multi-target-directed ligands gold rush. Rosini M, Simoni E, Bartolini M, Cavalli A, Ceccarini L, Pascu N, McClymont DW, Tarozzi A, Bolognesi ML, Minarini A, Tumiatti V, Andrisano V, Mellor IR, Melchiorre C. J Med Chem; 2008 Aug 14; 51(15):4381-4. PubMed ID: 18605718 [Abstract] [Full Text] [Related]
6. In silico design and search for acetylcholinesterase inhibitors in Alzheimer's disease with a suitable pharmacokinetic profile and low toxicity. da Silva VB, de Andrade P, Kawano DF, Morais PA, de Almeida JR, Carvalho I, Taft CA, da Silva CH. Future Med Chem; 2011 Jun 14; 3(8):947-60. PubMed ID: 21707398 [Abstract] [Full Text] [Related]
7. Pharmacophore mapping-based virtual screening followed by molecular docking studies in search of potential acetylcholinesterase inhibitors as anti-Alzheimer's agents. Ambure P, Kar S, Roy K. Biosystems; 2014 Feb 14; 116():10-20. PubMed ID: 24325852 [Abstract] [Full Text] [Related]
8. A combinatorial feature selection approach to describe the QSAR of dual site inhibitors of acetylcholinesterase. Asadabadi EB, Abdolmaleki P, Barkooie SM, Jahandideh S, Rezaei MA. Comput Biol Med; 2009 Dec 14; 39(12):1089-95. PubMed ID: 19854437 [Abstract] [Full Text] [Related]
9. Discovery of a novel acetylcholinesterase inhibitor by structure-based virtual screening techniques. Chen Y, Fang L, Peng S, Liao H, Lehmann J, Zhang Y. Bioorg Med Chem Lett; 2012 May 01; 22(9):3181-7. PubMed ID: 22472693 [Abstract] [Full Text] [Related]
10. Receptor-dependent (RD) 3D-QSAR approach of a series of benzylpiperidine inhibitors of human acetylcholinesterase (HuAChE). Araújo JQ, de Brito MA, Hoelz LV, de Alencastro RB, Castro HC, Rodrigues CR, Albuquerque MG. Eur J Med Chem; 2011 Jan 01; 46(1):39-51. PubMed ID: 21074294 [Abstract] [Full Text] [Related]
11. An investigation of structurally diverse carbamates for acetylcholinesterase (AChE) inhibition using 3D-QSAR analysis. Roy KK, Dixit A, Saxena AK. J Mol Graph Model; 2008 Sep 01; 27(2):197-208. PubMed ID: 18515163 [Abstract] [Full Text] [Related]
12. Novel carbamates as orally active acetylcholinesterase inhibitors found to improve scopolamine-induced cognition impairment: pharmacophore-based virtual screening, synthesis, and pharmacology. Chaudhaery SS, Roy KK, Shakya N, Saxena G, Sammi SR, Nazir A, Nath C, Saxena AK. J Med Chem; 2010 Sep 09; 53(17):6490-505. PubMed ID: 20684567 [Abstract] [Full Text] [Related]
14. Virtual screening discovery of new acetylcholinesterase inhibitors issued from CERMN chemical library. Sopkova-de Oliveira Santos J, Lesnard A, Agondanou JH, Dupont N, Godard AM, Stiebing S, Rochais C, Fabis F, Dallemagne P, Bureau R, Rault S. J Chem Inf Model; 2010 Mar 22; 50(3):422-8. PubMed ID: 20196555 [Abstract] [Full Text] [Related]
15. Prediction of acetylcholinesterase inhibitors and characterization of correlative molecular descriptors by machine learning methods. Lv W, Xue Y. Eur J Med Chem; 2010 Mar 22; 45(3):1167-72. PubMed ID: 20053484 [Abstract] [Full Text] [Related]
16. Lessons from functional analysis of AChE covalent and noncovalent inhibitors for design of AD therapeutic agents. Barak D, Ordentlich A, Kaplan D, Kronman C, Velan B, Shafferman A. Chem Biol Interact; 2005 Dec 15; 157-158():219-26. PubMed ID: 16289124 [Abstract] [Full Text] [Related]
17. Heterocyclic inhibitors of AChE acylation and peripheral sites. Bolognesi ML, Andrisano V, Bartolini M, Cavalli A, Minarini A, Recanatini M, Rosini M, Tumiatti V, Melchiorre C. Farmaco; 2005 Dec 15; 60(6-7):465-73. PubMed ID: 15878569 [Abstract] [Full Text] [Related]
18. Lead identification of acetylcholinesterase inhibitors-histamine H3 receptor antagonists from molecular modeling. Bembenek SD, Keith JM, Letavic MA, Apodaca R, Barbier AJ, Dvorak L, Aluisio L, Miller KL, Lovenberg TW, Carruthers NI. Bioorg Med Chem; 2008 Mar 15; 16(6):2968-73. PubMed ID: 18249544 [Abstract] [Full Text] [Related]
19. Knowledge based identification of MAO-B selective inhibitors using pharmacophore and structure based virtual screening models. Boppana K, Dubey PK, Jagarlapudi SA, Vadivelan S, Rambabu G. Eur J Med Chem; 2009 Sep 15; 44(9):3584-90. PubMed ID: 19321235 [Abstract] [Full Text] [Related]
20. Pharmacophore Modeling, virtual and in vitro screening for acetylcholinesterase inhibitors and their effects on amyloid-β self- assembly. Bag S, Tulsan R, Sood A, Datta S, Török M. Curr Comput Aided Drug Des; 2013 Mar 15; 9(1):2-14. PubMed ID: 22734711 [Abstract] [Full Text] [Related] Page: [Next] [New Search]