Andrographolide derivatives were shown to inhibit α-glucosidase. To investigate the relationship between activities and structures of andrographolide derivatives, a training set was chosen from 25 andrographolide derivatives by the principal component analysis (PCA) method, and a quantitative structure-activity relationship (QSAR) was established by 2D and 3D QSAR methods. The cross-validation r 2 (0.731) and standard error (0.225) illustrated that the 2D-QSAR model was able to identify the important molecular fragments and the cross-validation r 2 (0.794) and standard error (0.127) demonstrated that the 3D-QSAR model was capable of exploring the spatial distribution of important fragments. The obtained results suggested that proposed combination of 2D and 3D QSAR models could be useful in predicting the α-glucosidase inhibiting activity of andrographolide derivatives.
References
[1]
Zhang, CY; Tan, BK. Effects of 14-deoxyandrographolide and 14-deoxy-11,12-didehydroandrographolide on nitric oxide production in cultured human endothelial cells. Phytother. Res 1999, 13, 157–159.
[2]
Sabu, KK; Padmesh, P; Seeni, SJ. Intraspecific variation in active principle content and isozymes of Andrographis paniculata (kalmegh): A traditional hepatoprotective medicinal herb of India. Med. Aromat. Plant Sci 2001, 23, 637–647.
[3]
Bernacki, RJ; Niedbala, MJ; Korytnyk, W. Glycosidases in cancer and invasion. Cancer Metastasis Rev 1985, 4, 81–101.
[4]
Pili, R; Chang, J; Partis, RA; Mueller, RA; Chrest, FJ; Passaniti, A. The alpha-glucosidase I inhibitor castanospermine alters endothelial cell glycosylation, prevents angiogenesis, and inhibits tumor growth. Cancer Res 1995, 55, 2920–2926.
[5]
Humphries, MJ; Matsumoto, K; White, SL; Olden, K. Inhibition of experimental metastasis by castanospermine in mice: Blockage of two distinct stages of tumor colonization by oligosaccharide processing inhibitors. Cancer Res 1986, 46, 5215–5222.
[6]
Papandreou, MJ; Barbouche, R; Guieu, R; Kieny, MP; Fenouillet, E. The alpha-glucosidase inhibitor 1-deoxynojirimycin blocks human immunodeficiency virus envelope glycoprotein-mediated membrane fusion at the CXCR4 binding step. Mol. Pharmacol 2002, 61, 186–193.
[7]
Ouzounov, S; Mehta, A; Dwek, RA; Block, TM; Jordan, R. The combination of interferon alpha-2b and n-butyl deoxynojirimycin has a greater than additive antiviral effect upon production of infectious bovine viral diarrhea virus (BVDV) in vitro: Implications for hepatitis C virus (HCV) therapy. Antiviral Res 2002, 55, 425–435.
[8]
Schmidt, DD; Frommer, W; Junge, B; Muller, L; Wingender, W; Truschei, E; Schafer, D. Alpha-Glucosidase inhibitors. New complex oligosaccharides of microbial origin. Naturwissenschaften 1977, 64, 535–536.
[9]
Kameda, Y; Asano, N; Yoshikawa, M; Takeucki, M; Yamaguchi, T; Matsui, K; Horii, S; Fukase, HJ. Valiolamine, a new alpha-glucosidase inhibiting aminocyclitol produced by Streptomyces hygroscopicus. J.Antibiot 1984, 37, 1301–1307.
[10]
Robinson, KM; Begovic, ME; Rhinehart, BL; Heineke, EW; Ducep, JB; Kastner, PR; Marshall, FN; Danzin, C. New potent alpha-glucohydrolase inhibitor MDL 73945 with long duration of action in rats. Diabetes 1991, 40, 825–830.
[11]
Fujisawa, T; Ikegami, H; Inoue, K; Kawabata, Y; Ogihara, T. Effect of two alpha-glucosidase inhibitors, voglibose and acarbose, on postprandial hyperglycemia correlates with subjective abdominal symptoms. Metabolism 2005, 54, 387–390.
[12]
van den Broek, LAGM; Kat-van den Nieuwenhof, MW; Butters, TD; van Boeckel, CA. Synthesis of alpha-glucosidase I inhibitors showing antiviral (HIV-1) and immunosuppressive activity. J. Pharm. Pharmacol 1996, 48, 172–178.
[13]
Dai, GF; Xu, HW; Wang, JF; Liu, FW; Liu, HM. Studies on the novel alpha-glucosidase inhibitory activity and structure-activity relationships for andrographolide analogues. Bioorgan. Med. Chem 2006, 16, 2710–2713.
[14]
Xu, HW; Dai, GF; Liu, GZ; Wang, JF; Liu, HM. Synthesis of andrographolide derivatives: A new family of alpha-glucosidase inhibitors. Bioorgan. Med. Chem 2007, 15, 4247–4255.
[15]
Truscheit, E; Frommer, W; Junge, B; Muller, L; Schmidt, DD; Wingender, W. Chemistry and biochemistry of microbial alpha-glucosidase inhibitors. Angew. Chem 1981, 93, 738–755.
[16]
Madariaga, H; Lee, PC; Heitlinger, LA; Lenenthal, M. Effects of graded alpha-glucosidase inhibition on sugar absorption in vivo. Dig. Dis. Sci 1988, 33, 1020–1024.
[17]
Lee, D-S; Lee, S-H. Genistein, a soy isoflavone, is a potent alpha-glucosidase inhibitor. FEBS Lett 2001, 501, 84–86.
[18]
McCulloch, DK; Kurtz, AB; Tattersall, RB. A new approach to the treatment of nocturnal hypoglycemia using alpha-glucosidase inhibition. Diabetes Care 1983, 6, 483–487.
[19]
Sou, S; Takahashi, H; Yamasaki, R; Kagechika, H; Endo, Y; Hashimoto, Y. Alpha-glucosidase inhibitors with a 4,5,6,7-tetrachlorophthalimide skeleton pendanted with a cycloalkyl or dicarba-closo-dodecaborane group. Chem. Pharm. Bull 2001, 49, 791–793.
[20]
Node, K. Alpha-glucosidase inhibitors: New therapeutic agents for chronic heart failure. Hypertens. Res 2006, 29, 741–42.
[21]
Hansch, C; Mahoney, PP; Fujita, T; Muir, RM. Correlation of biological activity of phenoxyacetic acids with Hammett substituent constants and partition coefficients. Nature 1962, 194, 178–180.
[22]
Itzstein, VM; Wu, WY; Kok, GB. Rational design of potent sialidase-based inhibitors of influenza virus replication. Nature 1993, 363, 418–423.
[23]
Melnick, M; Reich, SH; Lewis, KK. Bis tertiary amide inhibitors of the HIV-1 protease generated via protein structure-based iterative design. J. Med. Chem 1996, 39, 2795–2811.
[24]
Ring, CS; Sun, E; McKerrow, JH. Structure-based inhibitor design by using protein models for the development of antiparasitic agents. Proc.Natl. Acad. Sci. USA 1993, 90, 3583–3587.
[25]
Hibert, MF; Hoffmann, R; Miller, RC. Conformation-activity relationship study of 5-HT3 receptor antagonists and a definition of a model for this receptor site. J. Med. Chem 1990, 33, 1594–1600.
Xiong, B; Gui, CS; Xu, XY. Acta. A 3D model of SARS_CoV 3CL proteinase and its inhibitors design by virtual screening. Pharmacol. Sin 2003, 24, 497–504.
[28]
Pastor, M; Cruciani, G. A novel strategy for improving ligand selectivity in receptor-based drug design. J. Med. Chem 1995, 38, 4637–4647.
[29]
Anand, K; Ziebuhr, J; Wadhwani, P; Mesters, JR; Hilgenfeld, R. Coronavirus main proteinase (3CLpro) Structure: Basis for design of anti-SARS drugs. Science (Sciencexpress) 2003, 300, 1763–1767.
[30]
Carlton, AT; Vinicius, BDS; Carlos, HTD. Current topics in computer-aided drug design. J. Pharm. Sci 2008, 97, 1089–1098.
[31]
Xu, S. . The 3D-QSAR Studies on Andrographolide Derivatives Inhibiting α-Glucosidase. Ph.D. Dissertation. Zhengzhou University: Zhengzhou, China, 2006.
[32]
Wolfgang, H; Léopold, S. Applied Multivariate Statistical Analysis, 2nd ed ed.; Springer Press: Berlin, Heidelberg, Germany, 2007; pp. 233–272.
[33]
Ash, S; Cline, MA; Homer, RW; Hurst, T; Smith, GB. SYBYL line notation (SLN): A versatile language for chemical structure representation. J Chem Inf Comput Sci 1997, 37, 71–79.
[34]
Timothy, EL. VAX Architecture Reference Manual; Digital Press: Newton, MA, USA, 1987; pp. 288–326.
[35]
Frank, IE; Feikama, J; Constantine, N; Kowalski, BR. Prediction of Product Quality from Spectral Data Using the Partial Least-Squares Method. J. Chem. Inf. Comput. Sci 1984, 24, 20–24.
[36]
Golbraikh, A; Tropsha, A. Beware of q2! J. Mol. Graph. Model 2002, 20, 269–276.
[37]
Cramer, RD; Patterson, DE; Bunce, JD. Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. J. Am. Chem. Soc 1988, 110, 5959–5967.
[38]
Klebe, G; Abraham, U. Comparative Molecular Similarity Index Analysis (CoMSIA) to study hydrogen-bonding properties and to score combinatorial libraries. J. Comput. Aided Mol. Design 1999, 13, 1–10.
[39]
van de Waterbeemd, H. Chemometric Methods in Molecular Design (Methods and Principles in Medicinal Chemistry); Wiley-VCH Press: Weinheim, Germany, 1995; pp. 309–318.
[40]
Dixit, A; Kashaw, SK; Gaur, S; Saxena, AK. Development of CoMFA, advance CoMFA and CoMSIA models in pyrroloquinazolines as thrombin receptor antagonist. Bioorgan. Med. Chem 2004, 12, 3591–3598.
[41]
Narayanan, R; Gunturi, SB. In silico ADME modelling: Prediction models for blood-brain barrier permeation using a systematic variable selection method. Bioorgan. Med. Chem 2005, 13, 3017–3028.
[42]
Gunturi, SB; Narayanan, R; Khandelwal, A. In silico ADME modelling: Computational models to predict human serum albumin binding affinity using ant colony systems. Bioorgan. Med. Chem 2006, 14, 4118–4129.
[43]
Gunturi, SB; Narayanan, R. In silico ADME modeling 3: Computational models to predict human intestinal absorption using sphere exclusion and kNN QSAR methods. QSAR Comb. Sci 2007, 26, 653–668.
