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Cluster Analysis of Medicinal Plants and Targets Based on Multipartite Network.

ABSTRACT: Network-based methods for the analysis of drug-target interactions have gained attention and rely on the paradigm that a single drug can act on multiple targets rather than a single target. In this study, we have presented a novel approach to analyze the interactions between the chemicals in the medicinal plants and multiple targets based on the complex multipartite network of the medicinal plants, multi-chemicals, and multiple targets. The multipartite network was constructed via the conjunction of two relationships: chemicals in plants and the biological actions of those chemicals on the targets. In doing so, we introduced an index of the efficacy of chemicals in a plant on a protein target of interest, called target potency score (TPS). We showed that the analysis can identify specific chemical profiles from each group of plants, which can then be employed for discovering new alternative therapeutic agents. Furthermore, specific clusters of plants and chemicals acting on specific targets were retrieved using TPS that suggested potential drug candidates with high probability of clinical success. We expect that this approach may open a way to predict the biological functions of multi-chemicals and multi-plants on the targets of interest and enable repositioning of the plants and chemicals.

SUBMITTER: Lee N

PROVIDER: S-EPMC8068312 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundScutellaria baicalensis Georgi has been extensively used as a medicinal herb in China for over 2000 years. They may be intentionally or inadvertently substituted or blended with comparable species in the local market, threatening clinical medication safety. Molecular markers are effective tools to prevent misidentification and eliminate doping and falsification among Scutellaria plants. This study screened four highly variable regions to identify Scutellaria and its adulterants. In addition, a phylogenetic analysis was performed using the complete cp genome combined with published Scutellaria species samples. Moreover, a comparative analysis of the cp genomes was conducted to investigate the cp genome evolution of S. baicalensis.ResultsThe complete cp genome of five species of Scutellaria was sequenced for the first time, and four previously published Scutellaria species were re-sequenced. They all exhibited a conserved quadripartite structure in their cp genomes, including two distinct regions, namely a small and large single copy region, respectively, and two inverted repeats encompassing the majority of ribosomal RNA genes. Furthermore, the nine species exhibited high conservation from aspects of the genome structure, codon usage, repeat sequences, and gene content. Four highly variable regions (matK-rps16, ndhC-trnV-UAC, psbE-petL, and rps16-trnQ-UUG) may function as potential molecular markers for differentiating S. baicalensis from its adulterants. Additionally, the monophyly of Scutellaria was ascertained and could be reclassified into two subgenera, subgenus Anaspis and subgenus Scutellaria, as evidenced by the phylogenetic analyses on sequences of cp genome and shared protein-coding sequences. According to the molecular clock analysis, it has been inferred that the divergence of Scutellaria occurred at approximately 4.0 Mya during the Pliocene Epoch.ConclusionOur study provides an invaluable theoretical basis for further Scutellaria species identification, phylogenetics, and evolution analysis.

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Cluster Analysis of Medicinal Plants and Targets Based on Multipartite Network.

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