Expanding potential targets of herbal chemicals by node2vec based on herb-drug interactions.

BACKGROUND: The identification of chemical-target interaction is key to pharmaceutical research and development, but the unclear materials basis and complex mechanisms of traditional medicine (TM) make it difficult, especially for low-content chemicals which are hard to test in experiments. In this research, we aim to apply the node2vec algorithm in the context of drug-herb interactions for expanding potential targets and taking advantage of molecular docking and experiments for verification. METHODS: Regarding the widely reported risks between cardiovascular drugs and herbs, Salvia miltiorrhiza (Danshen, DS) and Ligusticum chuanxiong (Chuanxiong, CX), which are widely used in the treatment of cardiovascular disease (CVD), and approved drugs for CVD form the new dataset as an example. Three data groups DS-drug, CX-drug, and DS-CX-drug were applied to serve as the context of drug-herb interactions for link prediction. Three types of datasets were set under three groups, containing information from chemical-target connection (CTC), chemical-chemical connection (CCC) and protein-protein interaction (PPI) in increasing steps. Five algorithms, including node2vec, were applied as comparisons. Molecular docking and pharmacological experiments were used for verification. RESULTS: Node2vec represented the best performance with average AUROC and AP values of 0.91 on the datasets "CTC, CCC, PPI". Targets of 32 herbal chemicals were identified within 43 predicted edges of herbal chemicals and drug targets. Among them, 11 potential chemical-drug target interactions showed better binding affinity by molecular docking. Further pharmacological experiments indicated caffeic acid increased the thermal stability of the protein GGT1 and ligustilide and low-content chemical neocryptotanshinone induced mRNA change of FGF2 and MTNR1A, respectively. CONCLUSIONS: The analytical framework and methods established in the study provide an important reference for researchers in discovering herb-drug interactions, alerting clinical risks, and understanding complex mechanisms of TM.

Leocarpinolide B Attenuates Collagen Type II-Induced Arthritis by Inhibiting DNA Binding Activity of NF-κB.

Rheumatoid arthritis (RA) is a chronic autoimmune disease triggered by a cascading inflammatory response. Sigesbeckia Herba (SH) has long been utilized as a traditional remedy to alleviate symptoms associated with rheumatism. Our previous study found that leocarpinolide B (LB), a sesquiterpene lactone isolated from the whole plant of SH, possesses potent a anti-inflammatory effect on macrophages. This study was designed to evaluate the therapeutic effects of LB on RA, and further investigate the underlying mechanisms. In collagen type II-induced arthritic mice, LB was demonstrated to decrease the production of autoimmune antibodies in serum and inflammatory cytokines in the joint muscles and recover the decreased regulatory T lymphocytes in spleen. Moreover, LB significantly suppressed the inflammatory infiltration, formation of pannus and bone erosion in the paw joints. In vitro testing showed that LB inhibited the proliferation, migration, invasion, and secretion of inflammatory cytokines in IL-1ß-induced human synovial SW982 cells. Network pharmacology and molecular docking suggested NF-κB p65 could be the potential target of LB on RA treatment, subsequent experimental investigation confirmed that LB directly interacted with NF-κB p65 and reduced the DNA binding activity of NF-κB in synovial cells. In conclusion, LB significantly attenuated the collagen type II-induced arthritis, which was at least involved in the inhibition of DNA binding activity of NF-κB through a direct binding to NF-κB p65. These findings suggest that LB could be a valuable lead compound for developing anti-RA drugs.

[The analysis of human immunodeficiency virus-1 subtypes in Yunnan province].

OBJECTIVE: To analyze the geographical distribution and risk factors of HIV-1 subtypes in Yunnan province. METHODS: Blood samples from 1319 HIV positives were collected in Yunnan Province from 2001 to 2006. The nested polymerase chain reaction was used to amplify the gag (p24)-protease fragments from RNA extracted from plasma or sera. The sequences were used for subtype determination by phylogenetic tree analysis. RESULTS: Among 1319 samples studied, the subtypes has been successfully obtained from 644 samples that were constituted of seven subtypes: CRF08_BC, CRF07_BC, CRF07/08_BC, CRF01_AE, C, B' and URFB/C. C/CRF07_BC/CRF08_BC were distributed in the whole province, but CRF01_AE were mainly distributed in the boarding areas with Myanmar such as Dehong, Baoshan, Xishuangbanna and Puer. Moreover, injecting drugs users accounted for 61.6% (270/438) among C/CRF07_BC/CRF08_BC infections, while only 8.5% (15/177) among CRF01_AE infections. CONCLUSION: Our data indicated that at least seven subtypes were identified in Yunnan province, the relationship between subtypes and transmission routes were analyzed, and the geographic difference of subtypes was also observed.