Bioinformatics and Medicinal Plant Research: Current Scenario
Bioinformatics being a multidisciplinary data-driven field has revolutionized several aspects of life sciences research, and area of drug development through medicinal plants is no exception. Medicinal plants have been known to play a major role in the primary healthcare system of several communities across the globe since ancient times. They continue to provide a multitude of pharmacologically active compounds. Now, to increase the utility of medicinal plants for drug discovery, bioinformatics plays a major role in replacing the conventional expensive, time-consuming and sluggish methods of drug development through high-throughput computational approaches. In this chapter, we attempt to present the comprehensive and updated summary on the role of bioinformatics in the area of medicinal plant research through the development of plant-based drugs. We need to understand the role of different bioinformatics approaches in medicinal plant research as it could serve as harbinger for the discovery of new therapeutic potential leads against various pharmacological targets. Owing to the increasing demand of herbal drugs in the market due to a wide continuum of beneficial effects they can offer to humankind over their non-plant counterparts, it becomes mandatory to pay attention to the medicinal plant-based research area in which there has been limited application of bioinformatics approaches. The chapter therefore aims to provide an overview on the current scenario of bioinformatics in analysing the data pertaining to medicinal plants, which ultimately could lead to quicker and economical drug designing with improved pharmacokinetics.
KeywordsApplications Bioinformatics Drug development Medicinal plants Virtual screening
We are highly indebted to the Bioinformatics Centre, University of Kashmir, for providing their services while drafting this chapter.
Conflict of Interest
The authors declare that they have no conflicts of interest with respect to research, authorship and publication of this book chapter.
Copyright and Permission Statement
We confirm that the materials included in this chapter do not violate copyright laws. Where relevant, appropriate permissions have been obtained from the original copyright holder(s). All original sources have been appropriately acknowledged and/or referenced.
- Afendi FM, Okada T, Yamazaki M, Hirai-Morita A, Nakamura Y, Nakamura K, Ikeda S, Takahashi H, Altaf-Ul-Amin M, Darusman LK, Saito K, Kanaya S (2012) KNApSAcK family databases: integrated metabolite-plant species databases for multifaceted plant research. Plant Cell Physiol 53(2):e1CrossRefPubMedGoogle Scholar
- Caspi R, Foerster H, Fulcher CA, Kaipa P, Krummenacker M, Latendresse M, Paley S, Rhee SY, Shearer AG, Tissier C (2008) The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/genome databases. Nucleic Acids Res 36(suppl 1):D623–D631PubMedPubMedCentralGoogle Scholar
- Chanda S (2014) Importance of pharmacognostic study of medicinal plants: an overview. J Pharmacogn Phytochem 2(5):69–73Google Scholar
- Childs KL (2014) Methods for plant genome annotation. In: Bell E (ed) Molecular life sciences: an encyclopedia reference. Springer, New York, pp 1–7Google Scholar
- Drezen E, Lavenier D (2014) Quality metrics for benchmarking sequences comparison tools. In: Brazilian symposium on bioinformatics. Springer International Publishing, Cham, pp 144–153Google Scholar
- Harishchander A (2017) A review on application of bioinformatics in medicinal plant research. Bioinforma Proteomics Open Access J 1(1):000104Google Scholar
- Lagunin AA, Goel RK, Gawande DY, Pahwa P, Gloriozova TA, Dmitriev AV, Ivanov SM, Rudik AV, Konova VI, Pogodin PV, Druzhilovsky DS, Poroikov VV (2014) Chemo- and bioinformatics resources for in silico drug discovery from medicinal plants beyond their traditional use: a critical review. Nat Prod Rep 31(11):1585–1611CrossRefPubMedGoogle Scholar
- Magrane M, Consortium U (2011) UniProt knowledgebase: a hub of integrated protein data. Database J Biol Databases Curation 2011:bar009Google Scholar
- Nantasenamat C, Isarankura-Na-Ayudhya C, Naenna T, Prachayasittikul V (2009) A practical overview of quantitative structure-activity relationship. EXCLI J 8:74–88Google Scholar
- Nayak SK, Patra PK, Padhi P, Panda A (2010) Optimization of herbal drugs using soft computing approach. Int J Log Comput 1:34–39Google Scholar
- Ohyanagi H, Takano T, Terashima S, Kobayashi M, Kanno M, Morimoto K, Kanegae H, Sasaki Y, Saito M, Asano S (2014) Plant omics data center: an integrated web repository for interspecies gene expression networks with NLP-based curation. Plant Cell Physiol 56(1):e9. (1–8)CrossRefPubMedPubMedCentralGoogle Scholar
- Pathania S, Ramakrishnan SM, Bagler G (2015) Phytochemica: a platform to explore phytochemicals of medicinal plants. Database (Oxford) 2015Google Scholar
- Rocca-Serra P, Brazma A, Parkinson H, Sarkans U, Shojatalab M, Contrino S, Vilo J, Abeygunawardena N, Mukherjee G, Holloway E, Kapushesky M, Kemmeren P, Lara GG, Oezcimen A, Sansone SA (2003) ArrayExpress: a public database of gene expression data at EBI. C R Biol 326(10–11):1075–1078CrossRefGoogle Scholar
- Sarkar IN (2000) Biodiversity informatics: the emergence of a field. BMC Bioinforma 10(Suppl 14):S1Google Scholar
- Saxena M, Saxena J, Nema R, Singh D, Gupta A (2013) Phytochemistry of medicinal plants. J Pharmacogn Phytochem 1(6):168–182Google Scholar
- Sayers EW, Barrett T, Benson DA, Bolton E, Bryant SH, Canese K, Chetvernin V, Church DM, Dicuccio M, Federhen S, Feolo M, Geer LY, Helmberg W, Kapustin Y, Landsman D, Lipman DJ, Lu Z, Madden TL, Madej T, Maglott DR, Marchler-Bauer A, Miller V, Mizrachi I, Ostell J, Panchenko A, Pruitt KD, Schuler GD, Sequeira E, Sherry ST, Shumway M, Sirotkin K, Slotta D, Souvorov A, Starchenko G, Tatusova TA, Wagner L, Wang Y, John Wilbur W, Yaschenko E, Ye J (2010) Database resources of the national center for biotechnology information. Nucleic Acids Res 38(D1):D5–D16CrossRefGoogle Scholar
- Singh A, Kumar N (2013) A review on DNA microarray technology. Int J Curr Res Rev 5(22):1Google Scholar
- Ueno S, Moriguchi Y, Uchiyama K, Ujino-Ihara T, Futamura N, Sakurai T, Shinohara K, Tsumura Y (2012) A second generation framework for the analysis of microsatellites in expressed sequence tags and the development of EST-SSR markers for a conifer, Cryptomeria japonica. BMC Genomics 13(1):1CrossRefGoogle Scholar
- Wu KM, Farrelly J, Birnkrant D, Chen S, Dou J, Atrakchi A, Bigger A, Chen C, Chen Z, Freed L, Ghantous H, Goheer A, Hausner E, Osterberg R, Rhee H, Zhang K (2004) Regulatory toxicology perspectives on the development of botanical drug products in the United States. Am J Ther 11(3):213–217CrossRefPubMedGoogle Scholar
- Yang C, Hasselgren CH, Boyer S, Arvidson K, Aveston S, Dierkes P, Benigni R, Benz RD, Contrera J, Kruhlak NL, Matthews EJ, Han X, Jaworska J, Kemper RA, Rathman JF, Richard AM (2008) Understanding genetic toxicity through data mining: the process of building knowledge by integrating multiple genetic toxicity databases. Toxicol Mech Methods 18(2–3):277–295CrossRefPubMedGoogle Scholar
- Zeng X, Zhang P, He W, Qin C, Chen S, Tao L, Wang Y, Tan Y, Gao D, Wang B, Chen Z, Chen W, Jiang YY, Chen YZ (2018) NPASS: natural product activity and species source database for natural product research, discovery and tool development. Nucleic Acids Res 46(D1):D1217–D1222CrossRefPubMedGoogle Scholar