Please use this identifier to cite or link to this item: https://doi.org/10.1039/b303745b
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dc.titleCan an in silico drug-target search method be used to probe potential mechanisms of medicinal plant ingredients?
dc.contributor.authorChen, X.
dc.contributor.authorUng, C.Y.
dc.contributor.authorChen, Y.
dc.date.accessioned2014-05-19T02:57:18Z
dc.date.available2014-05-19T02:57:18Z
dc.date.issued2003-08
dc.identifier.citationChen, X., Ung, C.Y., Chen, Y. (2003-08). Can an in silico drug-target search method be used to probe potential mechanisms of medicinal plant ingredients?. Natural Product Reports 20 (4) : 432-444. ScholarBank@NUS Repository. https://doi.org/10.1039/b303745b
dc.identifier.issn02650568
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/53340
dc.description.abstractMedicinal plants have been explored therapeutically in traditional medicines and are a valuable source for drug discovery. Insufficient knowledge about the molecular mechanism of these medicinal plants limits the scope of their application and hinders the effort to design new drugs using the therapeutic principles of herbal medicines. This problem can be partially alleviated if efficient methods for rapid identification of protein targets of herbal ingredients can be introduced. Efforts have been directed at developing efficient computer methods for facilitating target identification. Various methods being explored or under investigation are reviewed here. So far, one computer method, INVDOCK, has been specifically used for automated drug target identification. Its usefulness in the identification of therapeutic targets of medicinal herbal ingredients as well as synthetic chemicals is reviewed. The majority of INVDOCK identified therapeutic targets of several well-known medicinal herbal ingredients have been found to be confirmed or implicated by experiments, which suggests the potential of in silico methods in facilitating the study of molecular mechanism of medicinal plants.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1039/b303745b
dc.sourceScopus
dc.typeReview
dc.contributor.departmentBIOLOGICAL SCIENCES
dc.contributor.departmentCOMPUTATIONAL SCIENCE
dc.description.doi10.1039/b303745b
dc.description.sourcetitleNatural Product Reports
dc.description.volume20
dc.description.issue4
dc.description.page432-444
dc.description.codenNPRRD
dc.identifier.isiut000184872000006
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