Exploration of QSAR modelling techniques and their combination to rationalize the physicochemical characters of nitrophenyl derivatives towards aldose reductase inhibition

Reference and notes

• Kador PF, Kinoshita JH, Sharpless NE. Aldose reductase inhibitors: a potential new class of agents for the pharmacological control of certain diabetic complications. J Med Chem 1985; 28: 841–849.
   PubMed Web of Science ®Google Scholar
• Kador PF. The role for aldose reductase in the development of diabetic complications. Med Res Rev. 198; 88: 325–352.
   Google Scholar
• Yabe-Nishimura C. Aldose reductase in glucose toxicity: a potential target for the prevention of diabetic complications. Pharmacol Rev, 1998; 20: 21–33.
   Google Scholar
• Costantino L, Rastelli G, Cignarella G, Vianello P, Barlocco D. New aldose reductase inhibitors as potential agents for the prevention of long-term diabetic complications. Exp Opin Ther Patents 1997; 7: 843–858.
   Web of Science ®Google Scholar
• Wolffenbuttel, BHR, Van Haeften TW. Pharmacological prevention of diabetic complications. Drugs 1995; 50: 263–288.
   PubMed Web of Science ®Google Scholar
• Porte D Jr, Schwartz MW. Diabetes complications: why is glucose potentially toxic? Science 1996; 272: 699–700.
   PubMed Web of Science ®Google Scholar
• Suzen S, Buyukbingol E. Recent studies of aldose reductase enzyme inhibition for diabetic complications. Curr Med Chem 2003; 10:1329–1352.
   PubMed Web of Science ®Google Scholar
• Larson ER, Lipinski CA, Sarges, R. Medicinal chemistry of aldose reductase inhibitors. Med Res Rev 1988;8: 159–186.
   PubMed Web of Science ®Google Scholar
• Sarges R. Advances in drug research. Testa, B: London: Academic; Vol 18. 1989; p 139–175.
   Google Scholar
• Costantino L, Rastelli G, Vianello P, Cignarella G, Barlocco D. Diabetes complications and their potential prevention: aldose reductase inhibition and other approaches. Med Res Rev 1999; 19: 3–23.
   PubMed Web of Science ®Google Scholar
• Costantino L, Rastelli G, Gamberoni MC, Barlocco D. Pharmacological approaches to the treatment of diabetic complications. Exp Opin Ther Patents 2000; 10:1245–1262.
   Web of Science ®Google Scholar
• Soni LK, Kaskhedikar SG. Exploring structural requirements for aldose-reductase inhibition by 2,4-dioxo- 5- (naphthyl methylene) -3- thiazolidine acetic acids and 2-thioxo analogues: Fujita-Ban and Hansch approach. Arch Pharm Chem Life Sci 2006; 339: 327–331.
   PubMed Web of Science ®Google Scholar
• Soni LK, Kaskhedikar SG. Exploring structural feature of aldose-reductase inhibition by 5-[[2-(ω-carboxyalkoxy)aryl]methylene]- 4-oxo-2-thioxothiazolidine derivatives employing Fujita-Ban and Hansch approach. Chem Pharm Bull 2007; 55: 72–75.
   PubMed Web of Science ®Google Scholar
• Soni LK, Gupta AK, Kaskhedikar SG. QSAR Study of 5-Arylidene-2,4-Thiazolidinediones as Aldose Reductase Inhibitors. Med Chem Res (In Press)
   Web of Science ®Google Scholar
• Amic D, Davidovic-Amic D, Beslo D, Lucic B, Trinajstic N. The use of the ordered orthogonalized multivariate linear regression in a structure-activity study of coumarin and flavonoid derivatives as inhibitors of aldose reductase. J Chem Inf Comput Sci 1997; 37: 581–586.
   Google Scholar
• Stefanic-Petek A, Krbavcic A, Solmajer T. QSAR of flavonoids: 4. differential inhibition of aldose reductase and p56lck protein tyrosine kinase. Croat Chem Acta 2002; 75: 517–529.
   Web of Science ®Google Scholar
• Prabhakar YS, Gupta MK, Roy N, Venkateswarlu Y. A high dimensional QSAR study on the aldose reductase inhibitory activity of some flavones: topological descriptors in modeling the activity. J Chem Inf Modeling 2006; 46: 86–92.
   PubMed Web of Science ®Google Scholar
• Costantino L, Ferrari AM, Gamberini MC, Rastelli G. Nitrophenyl derivatives as aldose reductase inhibitors. Bioorg Med Chem 2002; 10: 3923–3931.
   PubMed Web of Science ®Google Scholar
• Hansch C, Leo A. Substituent Constants for Correlation Analysis in Chemistry and Biology. New York: John Wiley; 1979.
   Google Scholar
• CS Chem Office, Version 80, Cambridge soft corporation, Software publishers Association, 1730 M Street, suite 700, Washington D C 20036 (202)452–1600, USA.
   Google Scholar
• Todeschini R, Consonni V DRAGON-software for the calculation of molecular descriptors rel 112 for Windows; 2001.
   Google Scholar
• Gupta AK, Arockia Babu M, Kaskhedikar SGVALSTAT: A program for quantitative structure activity relationship studies and their validations Indian J Pharm Sci 2004; 66: 396–402.
   Google Scholar
• Chatterjee S, Hadi A, Price B. Regression analysis by examples 3rd ed New York: Wiley-VCH;2000.
   Google Scholar
• Shapiro S, Guggenheim B. Inhibition of oral bacteria by phenolic compounds part 1 QSAR analysis using molecular connectivity Quant Struct Act Relat 1998; 17: 327–337.
   Google Scholar
• Cho DH, Lee SK, Kim BT, No KT. Quantitative structure-activity relationship (QSAR) study of new fluorovinyloxyacetamides Bull Korean Chem Soc 2001; 22: 388–394.
   Web of Science ®Google Scholar
• Golbraikh A, Tropsha ABeware of q2! J Mol Grap Mod 2002; 20: 269–276
   PubMed Web of Science ®Google Scholar
• Gasteiger J, Sadowski J, Schuur J, Selzer P, Steinhauer L, Steinhauer Vchemical information in 3D space J Chem Inf Comput Sci 1996; 365: 1030–1037.
   Google Scholar
• Schuur JH, Selzer P, Gasteiger J. The coding of the three-dimensional structure of molecules by molecular transforms and its application to structure-spectra correlations and studies of biological activity J Chem Inf Comput Sci, 1996; 362: 334–344.
   Google Scholar
• Schuur J, Gasteiger J. Infrared spectra simulation of substituted benzene derivatives on the basis of a novel 3D structure representation J Anal Chem 1997; 69: 2398–2405.
   Web of Science ®Google Scholar
• Todeschini R, Consonni V. Handbook of molecular descriptors Weinheim: Wiley-VCH; 2000.
   Google Scholar