Browsing by Author "Zhang, Xi"

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    Bacterial and fungal inhibitor interacted impacting growth of invasive Triadica sebifera and soil N2O emissions
    (Frontiers Media S.A., 2023) Lai, Xiaoqin; Luo, Laicong; Fang, Haifu; Zhang, Ling; Shad, Nasir; Bai, Jian; Li, Aixin; Zhang, Xi; Yu, Yadi; Wang, Hao; Siemann, Evan
    Plant invasions affect biodiversity and seriously endanger the stability of ecosystems. Invasive plants show strong adaptability and growth advantages but are influenced by various factors. Soil bacteria and fungi are critical to plant growth and are important factors affecting plant invasions. Plant invasions also affect soil N2O emissions, but the effects of invasive plants from different population origins on N2O emissions and their microbial mechanisms are not clear. In this experiment, we grew Triadica sebifera from native (China) and invasive (USA) populations with or without bacterial (streptomycin) and/or fungal (iprodione) inhibitors in a factorial experiment in which we measured plant growth and soil N2O emissions of T. sebifera. Plants from invasive populations had higher leaf masses than those from native populations when soil bacteria were not inhibited (with or without fungal inhibition) which might reflect that they are more dependent on soil bacteria. Cumulative N2O emissions were higher for soils with invasive T. sebifera than those with a plant from a native population. Bacterial inhibitor application reduced cumulative N2O emissions but reductions were larger with application of the fungal inhibitor either alone or in combination with the bacterial inhibitor. This suggests that fungi play a strong role in plant performance and soil N2O emissions. Therefore, it is important to further understand the effects of soil microorganisms on the growth of T. sebifera and soil N2O emissions to provide a more comprehensive scientific basis for understanding the causes and consequences of plant invasions.
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    Specificity in the druggable kinome: Molecular basis and its applications
    (2009) Zhang, Xi; Fernandez, Ariel
    Rational design of kinase inhibitors remains a challenge partly because there is no clear delineation of the molecular features that direct the pharmacological impact towards clinically relevant targets. In this thesis, we focus on a structural marker and construct a kinase classifier that enables the accurate prediction of pharmacological differences. Our indicator is a microenvironmental descriptor that quantifies the propensity for water exclusion around preformed polar pairs. The results suggest that targeting polar dehydration patterns heralds a new generation of drugs that enable a tighter control of specificity than designs aimed at promoting ligand-kinase pairwise interactions. As an application of the structural marker, we introduce a computational screening approach which provides a tool for extensive screening that uses experimentally obtained small-scale profiles as input data and makes predictions for a larger kinase set. These predictions result from a propagation of the reduced profile, exploiting a structural comparison of kinases based on a feature-similarity matrix. The comparison focuses on a molecular marker for specificity and promiscuity of kinase inhibitors. Our approach enables the computational high-throughput screening of entire libraries of compounds to search for suitable leads, mapping their inhibitory impact on a sizable sample of the human kinome. Yet another application of the structural marker is advocated by illustrating its cleaning efficacy. In this regard, we reassess the possibility to turn multi-target drugs into real clinical opportunities through judicious redesign. A general cleaning strategy, which adopts the structural marker as redesigning instruction, is proposed and exemplified by a workable approach.