Comparative Network Pharmacology Based on Tanimoto Coefficient with Forbes-2 Coefficient

Authors

  • Basirun  Department of Statistics, Bogor Agricultural University, Bogor, Indonesia
  • Farit Mochammad Afendi  Department of Computer Science, Bogor Agricultural University, Bogor, Indonesia
  • Wisnu Ananta Kusuma  Tropical Biopharmaca Research Center Bogor Agriculture University, Bogor, Indonesia

Keywords:

DM Type 2, Jamu, Forbes-2 Coefficient, Tanimoto Coefficient, MAD

Abstract

Research on active compound contained in medicinal plant as ingredient for creating jamu has been widely practiced, but a detailed explanation of the mechanism of work in molecular and pharmacological still needs to be developed. In research of in silico, one of the common approaches done to look at the work mechanism of a compound was considering the similarity aspects of chemical structures between compounds. Measurement of similarity between compounds in general using Tanimoto coefficient. Based on the research result toward clustering 79 coefficient similarity to measure closseness of compounds, in addition Tanimoto, there was Forbes-2 coefficient found better similarity. Based on the statement the researcher was interested to do research with the aim of evaluating the Network Pharmacology medicinal plants that play the role of DM Type 2 by replacing Tanimoto coefficient with Forbes-2 coefficient. The evaluation method in this research used Mean Absolute Deviation (MAD). The result of the pharmacology network analysis using the Tanimoto coefficient was better compared to the Forbes-2 coefficient

References

  1. Zhang Gui-Biao, Li Qing-Ya, Qi-long Chen, Shi-bing Su. 2013. Jejaring Pharmacology: a new approach for chinese Jamu research. Hindawi. Article ID 621423, 1-9.
  2. Nurishmaya MR. 2014. Pendekatan Bioinformatika Formulasi Jamu Baru Berkhasiat Antidiabetes dengan Ikan Zebra (danio rerio) sebagai Hewan Model [Skripsi]. Bogor(ID): Institut Pertanian Bogor.
  3. Qomariasih N, Susetyo B, Afendi FM. 2016. Analisis gerombol simultan dan jejaring farmakologi antara senyawa dengan protein target pada penentuan senyawa aktif jamu anti Diabetes Tipe 2. Jurnal Jamu Indonesia. 1(2) : 30-40.
  4. Bakri R, Wijayanto H, Afendi FM. 2016. Prediksi senyawa aktif pada tanaman obat berdasarkan kemiripan struktur kemiripan kimiawi untuk penyakit Diabetes Tipe 2. Jurnal Jamu Indonesia. 1(3) : 1-5.
  5. Klekota J, Roth FP. 2008. Chemical Substructures that Enrich for Biological Activity. Bioinformatics, 24:2518-2525.
  6. Zhao S, Li S. 2010. Network-based relating pharmacological and genomic spaces for drug target identification. PLoS ONE. 5(7): e11764. doi:10.1371/journal.pone.0011764.
  7. Johnson AM, Maggiora GM. 1990. Concepts and Applications of Molecular Similarity. New York: John Willey&Sons.ISBN 0-471-62175-7.

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Published

2018-07-30

Issue

Section

Research Articles

How to Cite

[1]
Basirun, Farit Mochammad Afendi, Wisnu Ananta Kusuma, " Comparative Network Pharmacology Based on Tanimoto Coefficient with Forbes-2 Coefficient, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 9, pp.348-355, July-August-2018.