Biology subjects

Gao, Y.-D.

Publications and source records attributed to Gao, Y.-D..

3 recordsLinked to original sources

bioRxiv2021

Cypripedium wardii (Orchidaceae) employs pseudopollen with both reward and deception to attract both flis and bees as pollinators

O_LIFlowering plants always attract animals providing rewards or deceptive signals to gain reproductive success. However, there is no well-documented reporting about a pollination mechanism with both rewards and deceptive signals by a same object. We found Cypripedium wardii flowers seem to attract visitors by the white pseudopollenlike trichomes on labella in our preliminary field observation. C_LIO_LITo explore the pollination mechanism of Cypripedium wardii, especially, the ecological function of the pseudopollen-like trichomes, we conducted field observations, analyses of the traits of visitors and flowers, and breeding system experiments. C_LIO_LIThe white trichomes composed by multicellular moniliform hairs on the floral labella played a crucial role to attract pollinators, causing a high natural fruit set ratio in C. wardii. We established the direct connection of the white trichomes and real pollen. C_LIO_LIWe propose that flowers of C. wardii provide pseudopollen to attract suitable bees and hoverflies as pollinators. And our evidence indicate that the pseudopollen owns both deceptive and rewarding ecological functions. Our study provide a clear pollination mechanism with both rewards and deceptive signals by a same object in angiosperm for the first time. However, an inbreeding depression seem to be caused by this strategy. And we speculated that the pollen mimicry strategy with both rewarding and deceptive functions in C. wardii may be an adaptation to the habitat fragmentation of this species to gain a reproductive assurance. C_LI

plant biology↗

bioRxiv2017

Anti-HIV activity prediction and enrichment identify novel human targets for Anti-HIV therapy

Human immunodeficiency virus (HIV) relies heavily on the host proteins to facilitate its entry and replication. Currently, more than 4000 human proteins are recorded to be involved in the HIV-1 life cycle. Identifying appropriate anti-HIV targets from so many host proteins is crucial to anti-HIV drug development, but a challenging work. Here we combined anti-HIV activity prediction and enrichment analysis to identify novel human targets for anti-HIV therapy. We firstly developed an accurate prediction tool named Anti-HIV-Predictor (AUC>0.96) to predict the anti-HIV activity of given compounds. Using this tool, we predicted 10488 anti-HIV compounds from ChEMBLdb. Then, based on this result and relationships of targets and compounds, we inferred 73 anti-HIV targets that enriched with anti-HIV compounds. The functional annotation and network analysis revealed that they directly or indirectly interact with 20 HIV proteins through neuropeptide signaling, GPCR signaling, cell surface signaling pathway, and so on. Nearly half of these targets overlap with the NCBI HIV dataset. However, the percentage of known therapeutic targets in these targets is significantly higher than that in the NCBI HIV dataset. After a series of feature analysis, we identified 13 novel human targets with high potential as anti-HIV targets, the inhibitors of which have experimentally confirmed anti-HIV activity. It is noteworthy that the inhibitors of REN and CALCA have better anti-HIV activity than CCR5 inhibitors. Taken together, our findings provide novel human targets for the host-oriented anti-HIV drug development and should significantly advance current anti-HIV research.

bioinformatics↗

bioRxiv2016

Efficient repositioning of approved drugs as anti-HIV agents using Anti-HIV-Predictor

Development of new, effective and affordable drugs against HIV is urgently needed. In this study, we developed a worlds first web server called Anti-HIV-Predictor (http://bsb.kiz.ac.cn:70/hivpre) for predicting anti-HIV activity of given compounds. This server is rapid and accurate (accuracy >93% and AUC > 0.958). We applied the server to screen 1835 approved drugs for anti-HIV therapy. Totally 67 drugs were predicted to have anti-HIV activity, 25 of which are anti-HIV drugs. Then we experimentally evaluated 35 predicted new anti-HIV compounds by assays of syncytia formation, p24 quantification, cytotoxicity. Finally, we repurposed 7 approved drugs (cetrorelix, dalbavancin, daunorubicin, doxorubicin, epirubicin, idarubicin and valrubicin) as new anti-HIV agents. The original indication of these drugs is involved in a variety of diseases such as female infertility and cancer. Anti-HIV-Predictor and the 7 repurposed anti-HIV agents provided here demonstrate the efficacy of this strategy for discovery of new anti-HIV agents.

bioinformatics↗