In-silico tools in phytochemical research

dc.contributor.authorSingh, Ajeet
dc.contributor.authorZahra, Shafaque
dc.contributor.authorKumar, Shailesh
dc.date.accessioned2019-08-05T11:58:08Z
dc.date.available2019-08-05T11:58:08Z
dc.date.issued2019
dc.descriptionAccepted date: 26 June 2019en_US
dc.description.abstractThe enormous and highly diversified plant kingdom bears a potpourri of phytochemicals, which offers a lot of chance in the pharmaceutical field for researchers to scout new drugs for treating a large number of diseases. The surplus amount of biomedical knowledge accumulated so far has led to the use of bioinformatics approaches for the analysis of genomics, proteomics, and metabolomics datasets. With the help of available data and computational analysis techniques, it has become possible to explore and analyze the multifarious molecular targets of individual phytochemical compounds. Web-based cheminformatics databases have assisted in extensive data mining, modeling of biochemical pathways and protein-protein interactions, and they are gainful for phytochemical research surpassing the narrow spectrum of their old and conventional uses. Genome-wide functional screening for probable pharmacological targets, pharmacophore generation, Quantitative or qualitative structure-activity relationship (QSAR) modeling, molecular docking, and systems biology approaches in this current post-genomic era have now become an indispensable part of the drug discovery process. Although, currently known phytoconstituents and their structures represent only an infinitesimal portion of the total diversity of plant phytocomponents, with the emergence in ‘in silico’ based approaches, many new phytoconstituents, and their respective targets will be discovered in the future. This chapter sheds light on the key elements of drug designing and available user-oriented ‘in silico’ tools helpful in phytochemical research.en_US
dc.identifier.citationIn: Kumar S, Egbuna C (eds), Phytochemistry: An in-silico and in-vitro Update. Springer, Singapore, pp 351-372en_US
dc.identifier.doihttps://doi.org/10.1007/978-981-13-6920-9_19en_US
dc.identifier.isbn978-981-13-6920-9
dc.identifier.officialurlhttps://link.springer.com/chapter/10.1007%2F978-981-13-6920-9_19en_US
dc.identifier.urihttps://ndkr-library.nipgr.ac.in/handle/123456789/968
dc.language.isoen_USen_US
dc.publisherSpringer Nature Publishing AGen_US
dc.subjectCheminformaticsen_US
dc.subjectDockingen_US
dc.subjectDrug designingen_US
dc.subjectPhytochemicalsen_US
dc.subjectQSAR modelingen_US
dc.titleIn-silico tools in phytochemical researchen_US
dc.typeBook chapteren_US

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