Home   >   CSC-OpenAccess Library   >    Manuscript Information
Full Text Available

(78.86KB)
This is an Open Access publication published under CSC-OpenAccess Policy.
Optimization of Herbal Drugs using Soft Computing Approach
S. K. Nayak , P. K. Patra, P. Padhi, A. Panda
Pages - 34 - 39     |    Revised - 30-08-2010     |    Published - 30-10-2010
Volume - 1   Issue - 1    |    Publication Date - December 2010  Table of Contents
MORE INFORMATION
KEYWORDS
Herbal drugs, GA. ANN, QCAR
ABSTRACT
The study presents the results of our investigation into the use of Genetic Algorithms (GA) and ANN for identifying near optimal design parameters of compositions of drug systems that are based on soft computing ( i.e.) for herbal drug design. Herbal medicine has been applied successfully in much clinical therapeutics since long throughout in world. The present study proposes the concept of Quantitative Composition–Activity Relationship (QCAR) and computational technique to predict bioactivity of herbal drug and designing of new herbal drug for a particular disease. Genetic algorithm investigated the relationship between chemical composition of a widely used herbal medicine in India, and its bioactivity effect. The predicted results indicate that the proposed computing method is an efficient tool to herbal drug design.
CITED BY (1)  
1 Sharma, V., & Sarkar, I. N. (2013). Bioinformatics opportunities for identification and study of medicinal plants. Briefings in bioinformatics, 14(2), 238-250.
1 Google Scholar
2 CiteSeerX
3 refSeek
4 Scribd
5 SlideShare
6 PDFCAST
7 PdfSR
1 S. Arumugama, S. Kavimanib, B. Kadalmanic, A.B.A. Ahmedd, M.A. Akbarshac, M.V. Rao. “Antidiabetic activity of leaf and callus extracts of Aegle marmelos in rabbit”. Science Asia, 34: 317-321, 2008
2 E. Chan, M. Tan, J. Xin, S. Sudarsanam, D.E. “Johnson. Interactions between traditional Chinese medicines and Western therapeutics”, 13(1): 50-65, 2010
3 V.P. Dixit, R. Sinha, R. Tank. “Effect of Neem seed oil on the blood glucose Concentration of normal and alloxan 4diabetic rats”. Journal of Ethnopharmacology, 17: 95-98, 1986
4 J. K. Grover, S. Yadav, V. Vats. “Medicinal plants of India with antidiabetic potential”. J. Ethnopharmacology, 81: 81–100, 2002
5 P. Heacht. “High-throughput screening to odds with informatics-driven chemistry”. In current drug discovery, 21-24, 2002
6 J. Holland. “Adaptation in Natural and Artificial Systems”. University of Michigan Press (1975)
7 M.D. Ivorra, M. Paya, A. Villar. “A Review of natural products and plants as potential antidiabetic drugs”. Journal of Ethnopharmacology, 27: 243–275, 1989
8 Y. Wang, X. Wang, Y. Cheng. “A Computational Approach to Botanical Drug Design by Modeling Quantitative Composition–activity Relationship”. Chem Biol Drug Des, 68: 166–172, 2006
9 E.E. Jarald, E. Sheeja, S. Motwani, K.R. Dutt, R.K Goel. “Comparative Evaluation of Antihyperglycemic and hyperglycemic Activity of various Parts of Catharanthus roseus Linn”. Research Journal of Medicinal Plant, 2(1): 10-15, 2008
10 S. Rajasekaran, D. Aathishsekar. “Therapeutic Evaluation of Aloe vera leaf Gel Extract on Glycoprotein Components in Rats with Streptozotocin Diabetes”. Journal of Pharmacology and Toxicology, 2(4): 380-385, 2007
11 A.Q. Shamim, W. Asad, V. Sultana. “The Effect of Phyllanthus emblica Linn on Type – II Diabetes, Triglycerides and Liver - Specific Enzyme”. Pakistan Journal of Nutrition, 8(2): 125- 128, 2009
12 P. Scartezzini, E. Sproni. “Review on some plants of Indian traditional medicine with antioxidant activity”. J. Ethnopharmacol, 71: 23–43, 2000
13 S.D. Seth, B. Sharma B. “Medicinal plants of India”. Indian J. Med. Res, 120: 9–11, 2004
14 H. Sumida, A.I. Houston, J. M. Mcnamara, D.W.D. Hamilton. “Genetic Algorithms and Evolution”. J. Theor. Biol, 147: 59-84, 1990
15 V. Venkatasubramanian, A. Sundaram. “Genetic algorithms: introduction and applications”. Encyclopedia of Computational Chemistry, John Wiley &Sons, pp. 1115–1127 (1998)
16 T. Vetrichelvan, M. Jegadeesan. “Anti-diabetic activity of alcoholic extract of Aerva lanata (L.) Juss. ex Schultes in rats”. Journal of Ethnopharmacology, 80: 103–107, 2002
17 U. C. S. Yadav, K. Moorthy, N. Z. Baquer. “Combined treatment of sodium orthovanadate and Momordica charantia fruit extract prevents alterations in lipid profile and lipogenic enzymes in alloxan diabetic rats”. Molecular and Cellular Biochemistry, 268:111–120, 2005
18 J. Zupan, J.Gasteiger. “Neural Networks in Chemistry and Drug Design (2nd edn)”. John Wiley & Sons (1999)
Associate Professor S. K. Nayak
- India
simanta.nayak@eastodissa.ac.in
Dr. P. K. Patra
- India
Dr. P. Padhi
- India
Mr. A. Panda
- India