CFP last date
22 April 2024
Reseach Article

Computational Prediction of Molecular Targets responsible for Antioxidant Activity of D-pinitol in Caenorhabditis elegans

Published on February 2013 by Shailendra K Gupta, Rakesh Pandey, Madhumita Karmakar, Suchi Smita, Aakanksha Pant, Virendra Shukla, A. K. Yadav, Hema Negi, M. M. Gupta
National Seminar on Application of Artificial Intelligence in Life Sciences 2013
Foundation of Computer Science USA
NSAAILS - Number 1
February 2013
Authors: Shailendra K Gupta, Rakesh Pandey, Madhumita Karmakar, Suchi Smita, Aakanksha Pant, Virendra Shukla, A. K. Yadav, Hema Negi, M. M. Gupta
dd64d6c4-0e6d-4be2-b347-75a11b7cb7ec

Shailendra K Gupta, Rakesh Pandey, Madhumita Karmakar, Suchi Smita, Aakanksha Pant, Virendra Shukla, A. K. Yadav, Hema Negi, M. M. Gupta . Computational Prediction of Molecular Targets responsible for Antioxidant Activity of D-pinitol in Caenorhabditis elegans. National Seminar on Application of Artificial Intelligence in Life Sciences 2013. NSAAILS, 1 (February 2013), 19-23.

@article{
author = { Shailendra K Gupta, Rakesh Pandey, Madhumita Karmakar, Suchi Smita, Aakanksha Pant, Virendra Shukla, A. K. Yadav, Hema Negi, M. M. Gupta },
title = { Computational Prediction of Molecular Targets responsible for Antioxidant Activity of D-pinitol in Caenorhabditis elegans },
journal = { National Seminar on Application of Artificial Intelligence in Life Sciences 2013 },
issue_date = { February 2013 },
volume = { NSAAILS },
number = { 1 },
month = { February },
year = { 2013 },
issn = 0975-8887,
pages = { 19-23 },
numpages = 5,
url = { /proceedings/nsaails/number1/10380-1004/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Seminar on Application of Artificial Intelligence in Life Sciences 2013
%A Shailendra K Gupta
%A Rakesh Pandey
%A Madhumita Karmakar
%A Suchi Smita
%A Aakanksha Pant
%A Virendra Shukla
%A A. K. Yadav
%A Hema Negi
%A M. M. Gupta
%T Computational Prediction of Molecular Targets responsible for Antioxidant Activity of D-pinitol in Caenorhabditis elegans
%J National Seminar on Application of Artificial Intelligence in Life Sciences 2013
%@ 0975-8887
%V NSAAILS
%N 1
%P 19-23
%D 2013
%I International Journal of Computer Applications
Abstract

D-pinitol (3-O-methyl-D-inositol), a form of vitamin B inositol is a sugar-like molecule used for natural healing purposes for various diabetic-associated conditions. It is found in various plants like legumes, leafy vegetables, and citrus fruits, but is not found in animals and humans. In the present investigation, we have predicted possible biological molecular targets for D-pinitol using reverse docking approaches. In the process, we have identified that D-pinitol have affinity for most of the enzymes directly/indirectly associated with the free radical scavenging processes, indicating that D-pinitol might use as a potential antioxidant. The prediction was further in vivo validated on C. elegans, a multicellular model system using chemotaxis, thermo-tolerance and ROS scavenging activities assay. A strong correlation was observed in the computational prediction and in vivo antioxidant activities assays of D-pinitol in a dose-dependent manner. The findings broaden our current perspectives in understanding the antioxidative properties of D-pinitol.

References
  1. A. Davis, M. Christiansen, J. F. Horowitz, S. Klein, M. K. Hellerstein and R. E. Ostlund Jr. , Effect of pinitol treatment on insulin action in subjects with insulin resistance, Diabetes Care (2000), pp. 1000–1005.
  2. Govindarajan R, Rastogi S, Vijayakumar M, Shirwaikar A, Rawat AK, Mehrotra S, Pushpangadan P. Studies on the antioxidant activities of Desmodium gangeticum. Biol Pharm Bull. 2003; 26(10): 1424-7.
  3. Govindarajan R, Asare-Anane H, Persaud S, Jones P, Houghton PJ. Effect of Desmodium gangeticum extract on blood glucose in rats and on insulin secretion in vitro. Planta Med. 2007;73(5):427-32.
  4. Rathi A, Rao ChV, Ravishankar B, De S, Mehrotra S. Anti-inflammatory and anti-nociceptive activity of the water decoction Desmodium gangeticum. J Ethnopharmacol. 2004;95(2-3):259-63.
  5. Dharmani P, Mishra PK, Maurya R, Chauhan VS, Palit G. Desmodium gangeticum: a potent anti-ulcer agent. Indian J Exp Biol. 2005;43(6):517-21.
  6. Lai SC, Peng WH, Huang SC, Ho YL, Huang TH, Lai ZR, Chang YS. Analgesic and anti-inflammatory activities of methanol extract from Desmodium triflorum DC in mice. Am J Chin Med. 2009;37(3):573-88.
  7. Singh RK, Pandey BL, Tripathi M, Pandey VB. Anti-inflammatory effect of (+)-pinitol. Fitoterapia. 2001;72(2):168-70.
  8. Kim JI, Kim JC, Kang MJ, Lee MS, Kim JJ, Cha IJ. Effects of pinitol isolated from soybeans on glycaemic control and cardiovascular risk factors in Korean patients with type II diabetes mellitus: a randomized controlled study. Eur J Clin Nutr. 2005;59(3):456-8.
  9. Guo C, Oosterhuis DM. Effect of water-deficit stress and genotypes on pinitol occurrence in soybean plants. Environ. Exp. Bot. 1997;37(2-3), 147-152.
  10. Gao Z, Li H, Zhang H, Liu X, Kang L, Luo X, Zhu W, Chen K, Wang X, Jiang H. PDTD: a web-accessible protein database for drug target identification. BMC Bioinformatics 2008;9:104
  11. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE. The Protein Data Bank. Nucleic Acids Res. 2000;28(1):235-42.
  12. Li H, Gao Z, Kang L, Zhang H, Yang K, Yu K, Luo X, Zhu W, Chen K, Shen J, Wang X, Jiang H. TarFisDock: a web server for identifying drug targets with docking approach. Nucl. Acids Res. 2006;34:W219-224.
  13. Gupta SK, Dhawan A, Shanker R. In silico approaches: prediction of biological targets for fullerene derivatives. J Biomed Nanotechnol. 2011;7(1):91-2.
  14. Chen YZ, Zhi DG. Ligand-Protein Inverse Docking and its Potential Use in the Computer Search of Protein Targets of a Small Molecule. Proteins 2001;43:217–226.
  15. Paul N, Kellenberger E, Bret G, Muller P, Rognan D. Recovering the True Targets of Specific Ligands by Virtual Screening of the Protein Data Bank. Proteins 2004;54:671–680.
  16. Muller P, Lena G, Boilard E, Bezzine S, Lambeau G, Guichard G, Rognan D. In Silico-Guided Target Identification of a Scaffold-Focused Library: 1,3,5-Triazepan-2,6-Diones as Novel Phospholipase A2 Inhibitors. J. Med. Chem. 2006;49:6768–6778.
  17. Schneidman-Duhovny D, Inbar Y, Polak V, Shatsky M, Halperin I, Benyamini H, Barzilai A, Dror O, Haspel N, Nussinov R et al. Taking Geometry to its Edge: Fast Unbound Rigid (and Hinge-Bent) Docking. Proteins 2003;52:107–112.
  18. Brenner S. The genetics of Caenorhabditis elegans. Genetics. 1974;77(1):71-94.
  19. Kampkotter A, Nkwonkam CG, Zurawski RF, Timpel C, Chovolou Y, Wätjen W, Kahl R. Effects of the Xavonoids kaempferol and Wsetin on thermotolerance, oxidative stress and FoxO transcription factor DAF-16 in the model organism Caenorhabditis elegans. Arch Toxicol. 2007; 81:849–858.
  20. Tawe WN, Eschbach ML, Walter RD, Henkle-Dührsen K. Identification of stress-responsive genes in Caenorhabditis elegans using RT-PCR differential display. Nucleic Acids Res. 1998;26(7):1621-7.
  21. Leiers B, Kampkötter A, Grevelding CG, Link CD, Johnson TE, Henkle-Dührsen K. A stress-responsive glutathione S-transferase confers resistance to oxidative stress in Caenorhabditis elegans. Free Radic Biol Med. 2003;34(11):1405-15.
  22. Oh SW, Mukhopadhyay A, Svrzikapa N, Jiang F, Davis RJ, Tissenbaum HA. JNK regulates lifespan in Caenorhabditis elegans by modulating nuclear translocation of forkhead transcription factor/DAF-16. Proc Natl Acad Sci U S A. 2005;102(12):4494-9
  23. Gami MS, Wolkow CA. Studies of Caenorhabditis elegans DAF-2/insulin signaling reveal targets for pharmacological manipulation of lifespan. Aging Cell. 2006;5(1):31-7.
  24. Osuka K, Watanabe Y, Usuda N, Atsuzawa K, Wakabayashi T, Takayasu M. Oxidative stress activates STAT1 in basilar arteries after subarachnoid hemorrhage. Brain Res. 2010;1332:12-9.
Index Terms

Computer Science
Information Sciences

Keywords

Caenorhabditis Elegans D-pinitol Anti-oxidative Activity Reverse Docking Approach