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Journal Abstract Search
148 related items for PubMed ID: 20964806
21. Non-stochastic quadratic fingerprints and LDA-based QSAR models in hit and lead generation through virtual screening: theoretical and experimental assessment of a promising method for the discovery of new antimalarial compounds. Montero-Torres A, García-Sánchez RN, Marrero-Ponce Y, Machado-Tugores Y, Nogal-Ruiz JJ, Martínez-Fernández AR, Arán VJ, Ochoa C, Meneses-Marcel A, Torrens F. Eur J Med Chem; 2006 Apr; 41(4):483-93. PubMed ID: 16545891 [Abstract] [Full Text] [Related]
22. Tyrosinase inhibitory effect of benzoic acid derivatives and their structure-activity relationships. Khan SB, Hassan Khan MT, Jang ES, Akhtar K, Seo J, Han H. J Enzyme Inhib Med Chem; 2010 Dec; 25(6):812-7. PubMed ID: 20476840 [Abstract] [Full Text] [Related]
23. Classification of inhibitors of protein tyrosine phosphatase 1B using molecular structure based descriptors. Patankar SJ, Jurs PC. J Chem Inf Comput Sci; 2003 Dec; 43(3):885-99. PubMed ID: 12767147 [Abstract] [Full Text] [Related]
24. Novel inhibitors of human histone deacetylase (HDAC) identified by QSAR modeling of known inhibitors, virtual screening, and experimental validation. Tang H, Wang XS, Huang XP, Roth BL, Butler KV, Kozikowski AP, Jung M, Tropsha A. J Chem Inf Model; 2009 Feb; 49(2):461-76. PubMed ID: 19182860 [Abstract] [Full Text] [Related]
25. Novel coumarin-based tyrosinase inhibitors discovered by OECD principles-validated QSAR approach from an enlarged, balanced database. Le-Thi-Thu H, Casañola-Martín GM, Marrero-Ponce Y, Rescigno A, Saso L, Parmar VS, Torrens F, Abad C. Mol Divers; 2011 May; 15(2):507-20. PubMed ID: 20814821 [Abstract] [Full Text] [Related]
26. A novel non-stochastic quadratic fingerprints-based approach for the 'in silico' discovery of new antitrypanosomal compounds. Montero-Torres A, Vega MC, Marrero-Ponce Y, Rolón M, Gómez-Barrio A, Escario JA, Arán VJ, Martínez-Fernández AR, Meneses-Marcel A. Bioorg Med Chem; 2005 Nov 15; 13(22):6264-75. PubMed ID: 16115770 [Abstract] [Full Text] [Related]
27. Unified QSAR approach to antimicrobials. Part 3: first multi-tasking QSAR model for input-coded prediction, structural back-projection, and complex networks clustering of antiprotozoal compounds. Prado-Prado FJ, González-Díaz H, de la Vega OM, Ubeira FM, Chou KC. Bioorg Med Chem; 2008 Jun 01; 16(11):5871-80. PubMed ID: 18485714 [Abstract] [Full Text] [Related]
28. Antiprotozoan lead discovery by aligning dry and wet screening: prediction, synthesis, and biological assay of novel quinoxalinones. Martins Alho MA, Marrero-Ponce Y, Barigye SJ, Meneses-Marcel A, Machado Tugores Y, Montero-Torres A, Gómez-Barrio A, Nogal JJ, García-Sánchez RN, Vega MC, Rolón M, Martínez-Fernández AR, Escario JA, Pérez-Giménez F, Garcia-Domenech R, Rivera N, Mondragón R, Mondragón M, Ibarra-Velarde F, Lopez-Arencibia A, Martín-Navarro C, Lorenzo-Morales J, Cabrera-Serra MG, Piñero J, Tytgat J, Chicharro R, Arán VJ. Bioorg Med Chem; 2014 Mar 01; 22(5):1568-85. PubMed ID: 24513185 [Abstract] [Full Text] [Related]
29. Kojic acid-amino acid conjugates as tyrosinase inhibitors. Noh JM, Kwak SY, Seo HS, Seo JH, Kim BG, Lee YS. Bioorg Med Chem Lett; 2009 Oct 01; 19(19):5586-9. PubMed ID: 19700313 [Abstract] [Full Text] [Related]
30. Synthesis and structure-activity relationships of phenylpropanoid amides of serotonin on tyrosinase inhibition. Takahashi T, Miyazawa M. Bioorg Med Chem Lett; 2011 Apr 01; 21(7):1983-6. PubMed ID: 21377874 [Abstract] [Full Text] [Related]
31. Predictive models for tyrosinase inhibitors: Challenges from heterogeneous activity data determined by different experimental protocols. Tang H, Cui F, Liu L, Li Y. Comput Biol Chem; 2018 Apr 01; 73():79-84. PubMed ID: 29471263 [Abstract] [Full Text] [Related]
32. Two- and three-dimensional quantitative structure-activity relationships for a series of purine nucleoside phosphorylase inhibitors. Castilho MS, Postigo MP, de Paula CB, Montanari CA, Oliva G, Andricopulo AD. Bioorg Med Chem; 2006 Jan 15; 14(2):516-27. PubMed ID: 16203153 [Abstract] [Full Text] [Related]
34. Discovery of small-molecule inhibitors of tyrosinase. Germanas JP, Wang S, Miner A, Hao W, Ready JM. Bioorg Med Chem Lett; 2007 Dec 15; 17(24):6871-5. PubMed ID: 17964155 [Abstract] [Full Text] [Related]
35. Unified QSAR approach to antimicrobials. 4. Multi-target QSAR modeling and comparative multi-distance study of the giant components of antiviral drug-drug complex networks. Prado-Prado FJ, Martinez de la Vega O, Uriarte E, Ubeira FM, Chou KC, González-Díaz H. Bioorg Med Chem; 2009 Jan 15; 17(2):569-75. PubMed ID: 19112024 [Abstract] [Full Text] [Related]
36. Combining ligand-based pharmacophore modeling, quantitative structure-activity relationship analysis and in silico screening for the discovery of new potent hormone sensitive lipase inhibitors. Taha MO, Dahabiyeh LA, Bustanji Y, Zalloum H, Saleh S. J Med Chem; 2008 Oct 23; 51(20):6478-94. PubMed ID: 18808096 [Abstract] [Full Text] [Related]
37. Oxazolones: new tyrosinase inhibitors; synthesis and their structure-activity relationships. Khan KM, Mughal UR, Khan MT, Zia-Ullah, Perveen S, Choudhary MI. Bioorg Med Chem; 2006 Sep 01; 14(17):6027-33. PubMed ID: 16750372 [Abstract] [Full Text] [Related]
38. Quantitative structure-activity relationship studies of mushroom tyrosinase inhibitors. Xue CB, Luo WC, Ding Q, Liu SZ, Gao XX. J Comput Aided Mol Des; 2008 May 01; 22(5):299-309. PubMed ID: 18256890 [Abstract] [Full Text] [Related]
39. Synthesis and evaluation of 2(3H)-thiazole thiones as tyrosinase inhibitors. Emami S, Hosseinimehr SJ, Shahrbandi K, Enayati AA, Esmaeeli Z. Arch Pharm (Weinheim); 2012 Aug 01; 345(8):629-37. PubMed ID: 22532401 [Abstract] [Full Text] [Related]
40. 4D-QSAR analysis of a series of antifungal p450 inhibitors and 3D-pharmacophore comparisons as a function of alignment. Liu J, Pan D, Tseng Y, Hopfinger AJ. J Chem Inf Comput Sci; 2003 Aug 01; 43(6):2170-9. PubMed ID: 14632469 [Abstract] [Full Text] [Related] Page: [Previous] [Next] [New Search]