DNA barcoding is impending towards the generation of universal standards for species discrimination with a standard gene region that can be sequenced accurately and within short span of time. In this study, we were successful in developing efficient barcode locus in the Nepenthes genus. A total of 317 accessions were retrieved from GenBank of NCBI which represent 140 different species Nepenthes and evaluated the efficacy of ITS, rbcl and matK barcode candidates using barcode gap, applied distance similarity, and tree-based methods. Our result indicates that single-locus ITS or combined with plastid regions (matK) showed the best species discrimination with distinctive barcoding gaps. Therefore, we tentatively proposed the combination of ITS+matK as a core barcode for Nepenthes genus. This study provides a report on DNA barcoding for unique insectivores’ Nepenthes genus. As the different species of Nepenthes are higly endemic and endangered, it would be a useful study to understand the evolutionary relationship, sketched in emigration, mislabeling and can be a probable assessment for its biodiversity.

Background. Cancer is a second leading cause of death in the world, killing approximately 3500 per million people each year. Therefore, the drugs with multitarget pharmacology based on biological networks are crucial to investigate the molecular mechanisms of cancer drugs and repurpose the existing drugs to reduce adverse effects. Clerodendrum is a diversified genus with a wide range of economic and pharmacological properties. Limited studies were conducted on the genuss putative anticancer properties and the mechanisms of action based on biological networks remains unknown. This study was aimed to construct the possible compound/target/pathway biological networks for anticancer effect of Clerodendrum sp. using docking weighted network pharmacological approach and to investigate its potential mechanism of action. Methods. A total of 194 natural Clerodendrum sp. Compounds were retrieved from public databases and screened using eight molecular descriptors. The cancer-associated gene targets were retrieved from databases and the function of the target genes with related pathways were examined. Cytoscape v3.7.2 was used to build three major networks: compound-target network, target-target pathway network, and compound-target-pathway network. Results. Our finding indicates that the anticancer activity of Clerodendrum sp. involves 6 compounds, 9 targets, and 63 signaling pathways, resulting in multicompounds, multitargets, and multipathways networks. Additionally, molecular dynamics (MD) simulations were used to estimate the binding affinity of the best hit protein-ligand complexes. Conclusion. This study suggests the potential anticancer activity of Clerodendrum sp. which could further contribute to scavenger novel compounds for the development of new alternative anticancer drugs.