Dataset Information

Dataset of potential Rhizoma Polygonati compound-druggable targets and partial pharmacokinetics for treatment of COVID-19.

ABSTRACT: Rhizoma Polygonati (Chinese name as , pinyin as huangjing), as medicine and food homology of Traditional Chinese Medicine, has been recently applied for the complex prescriptions of alternative medicine for treatment of COVID-19 but the mechanisms are largely unclear. Here using public database search and filtering the potential chemical compound based drug targets with COVID-19 targets mapped, the list of data were provided and suggested pharmacokinetic tolerating dose of selected natural compounds were further collected from database. The data provided is the supplementary as a reference showing the intersections of Rhizoma Polygonati druggable targets of lists from current database and potentially related ones targeting COVID-19.

SUBMITTER: Mu C

PROVIDER: S-EPMC7683227 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Dataset of potential Rhizoma Polygonati compound-druggable targets and partial pharmacokinetics for treatment of COVID-19.

Mu Chenglin C Sheng Yifan Y Wang Qian Q Amin Amr A Li Xugang X Xie Yingqiu Y

Data in brief 20201030

Rhizoma Polygonati (Chinese name as , pinyin as huangjing), as medicine and food homology of Traditional Chinese Medicine, has been recently applied for the complex prescriptions of alternative medicine for treatment of COVID-19 but the mechanisms are largely unclear. Here using public database search and filtering the potential chemical compound based drug targets with COVID-19 targets mapped, the list of data were provided and suggested pharmacokinetic tolerating dose of selected natural compo ...[more]

PMID: 33251300

Similar Datasets

Project description:Multiple sclerosis is a complex autoimmune disease caused by a combination of genetic and environmental factors. Translation of Genome-Wide Association Study findings into therapeutics and effective preventive strategies has been limited to date. We used summary-data-based Mendelian randomization to synthesize findings from public expression quantitative trait locus, methylation quantitative trait locus and Multiple Sclerosis Genome-Wide Association Study datasets. By correlating the effects of methylation on multiple sclerosis, methylation on expression and expression on multiple sclerosis susceptibility, we prioritize genetic loci with evidence of influencing multiple sclerosis susceptibility. We overlay these findings onto a list of 'druggable' genes, i.e. genes which are currently, or could theoretically, be targeted by therapeutic compounds. We use GeNets and search tool for the retrieval of interacting genes/proteins to identify protein-protein interactions and druggable pathways enriched in our results. We extend these findings to a model of Epstein-Barr virus-infected B cells, lymphoblastoid cell lines. We conducted a systematic review of prioritized genes using the Open Targets platform to identify completed and planned trials targeting prioritized genes in multiple sclerosis and related disease areas. Expression of 45 genes in peripheral blood was strongly associated with multiple sclerosis susceptibility (False discovery rate 0.05). Of these 45 genes, 20 encode a protein which is currently targeted by an existing therapeutic compound. These genes were enriched for Gene Ontology terms pertaining to immune system function and leucocyte signalling. We refined this prioritized gene list by restricting to loci where CpG site methylation was associated with multiple sclerosis susceptibility, with gene expression and where expression was associated with multiple sclerosis susceptibility. This approach yielded a list of 15 prioritized druggable target genes for which there was evidence of a pathway linking methylation, expression and multiple sclerosis. Five of these 15 genes are targeted by existing drugs and three were replicated in a smaller expression Quantitative Trait Loci dataset (CD40, MERTK and PARP1). In lymphoblastoid cell lines, this approach prioritized 7 druggable gene targets, of which only one was prioritized by the multi-omic approach in peripheral blood (FCRL3). Systematic review of Open Targets revealed multiple early-phase trials targeting 13/20 prioritized genes in disorders related to multiple sclerosis. We use public datasets and summary-data-based Mendelian randomization to identify a list of prioritized druggable genetic targets in multiple sclerosis. We hope our findings could be translated into a platform for developing targeted preventive therapies.

Dataset Information

Dataset of potential Rhizoma Polygonati compound-druggable targets and partial pharmacokinetics for treatment of COVID-19.

Publications

Dataset of potential Rhizoma Polygonati compound-druggable targets and partial pharmacokinetics for treatment of COVID-19.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets