| Allosteric regulation is one of the most direct and efficient ways to fine-tune protein function.In biological networks,various allosteric effects of proteins can simultaneously and dynamically regulate cellular functions by activating,inhibiting or transforming the signal propagation of specific pathways,which trigger a variety of normal or abnormal cellular processes.The researches on clarifying the dynamic regulation mechanism of allostery on biological network and revealing the allosterome hiding in proteome,are of great significance for explaining cell function and exploring disease targets.At present,allosterome and allosteric networks are still in the initial stage of concept and direction exploration.Therefore,a series of bioinformatic studies has been carried out in this thesis,focusing on the expansion of allosterome and the construction of allosteric networks.The first part of this thesis,for the first time,has constructed multiple allosterome datasets and develops analysis methods: Chapter 2 describes the construction of the allosteric core dataset and the implement of ASD 2019,including 1,949 allosteric proteins,82,070 allosteric modulators and 89,554 allosteric interactions,which has achieved a data scale for system biological analysis.In Chapter 3,a novel Allo Site Pro method for allosteric site identification was developed and applied to the human proteome to predict the allosteric sites of each human protein,and a high-quality dataset offering potential allosteric sites of human proteins was constructed.In Chapter 4,allosterome maps were established for 9 human protein families,and the allosteric data and knowledge accumulated during the last decade were also annotated in each map,the tool is of great use for the phylogenetic analysis among homologous allosteric sites.The second part completes the construction of allosteric regulatory network and related data mining: in Chapter 5,261 allosteric regulatory networks containing allosteric proteins are firstly built and realized as Allo Network online academic resources.Secondly,the dataset of endogenous allosteric modulators was established,and its modulator attributes and the distribution of allosteric regulations were deeply explored,then the allosteric networks centered on endogenous ligands was realized.Finally,the identification method of potential endogenous allosteric ligands was preliminarily tested,and it was found that the molecular docking method had a better identification effect for the endogenous ligands with a high heteroatom-carbon ratio,especially for the ones containing phosphorus atoms.In the third part,based on above work and according to different research directions in allostery,ASD 2019 is built as a comprehensive analysis platform for allosterome.In Chapter 6,novel features were curated in ASD 2019 as follows:(1)Allo SitePotential: the dataset of potential allosteric sites of human proteins;(2)Allosterome:the online version of allosteric evolutionary maps;(3)Allo Mutation: the dataset of somatic mutations in allosteric sites extracted from a large number of clinical cancer samples;(4)Allo Drug: the dataset of allosteric drugs and targets;(5)Allo Pharm: a new allosteric interaction evaluation tool based on pharmacophore model.(6)Allo Pathway:a web tool for allosteric communication pathway prediction.In summary,this thesis has carried out a series of exploratory studies on allostery,allosterome and allosteric networks,and provided a variety of effective solutions and analytical processes for allosteric target identification,allosteric regulatory molecular screening,allosteric mechanism research and allosterome evolutionary analysis.These work will not only provide strong support for researchers to discover new allosteric targets and design highly selective allosteric modulators,but also offer clues to expand allosterome and uncover the allosteric regulatory networks. |
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