Understanding the sequence-structure-function relationship of the large arylsulfate sulfotransferase (ASST) enzyme family for engineering novel sulfation biocatalysts

了解大型芳基硫酸酯磺基转移酶 (ASST) 酶家族的序列-结构-功能关系,用于工程新型硫酸化生物催化剂

基本信息

项目摘要

Sulfated biomolecules are widespread in nature and play important roles in biological functions. Among the enzymes responsible for sulfation, ArylSulfate SulfoTransferases (ASSTs) are interesting biocatalysts as they use simple aromatic sulfates such as para-nitrophenyl sulfate as donors in comparison to PAPS-dependent sulfotransferases that use the complex and less stable PAPS as donor. However, very few is known about ASSTs (only one 3D-structure and its molecular mechanism described, tentative assignment into different classes according to their biochemistry or genomic context, only one natural donor and one acceptor substrate identified). According to our preliminary phylogenetic analysis on 2244 sequences of ASSTs genes, we identified 19 clades displaying reasonable boots-trap values. In analogy to CAZY or Sulfatlas databases, each of the actual 19 clades could correspond to a varying substrate specificity or/and mechanism. However, since biochemical and structural data are scarce, this hypothesis cannot be challenged by experimental data today. Moreover many of the branches (clades) coincide with taxonomy, which raises the obvious question that substrate specificity might be a trait which is linked to taxonomy.In the SulfASST project, we uses a combination of complementary approaches in bioinformatics, biochemistry, enzymology, structural biology, molecular modeling and protein engineering to obtain substantial information on the ASST enzymes. Based on the preliminary phylogenetic analysis, one representative of each of the 19 subfamilies (clades) will be expressed and screened for donor and acceptor substrates. Enzyme crystallography of 6-8 soundly selected representatives of ASSTs should provide precious details on molecular aspects of catalysis and selectivity (substrate, regiochemistry). Directed enzyme evolution (KnowVolution) and modeling will allow to obtain tailor-made biocatalysts for biotechnological purposes. Finally, this in-depth characterization of the ASSTs and rationalization of the obtained results will enable to: determine if substrate specificity is correlated to phylogeny; know if the genomic context of ASSTs genes is indicative of substrate or biological activity; decipher the structural determinants of substrate specificity/promiscuity and regioselectivity; define if enzyme mechanism is conserved throughout the different subfamilies (clades); predict substrate selectivity and regioselectivity by molecular modeling.
硫酸盐生物分子广泛存在于自然界,在生物功能中发挥着重要的作用。在负责硫酸盐化的酶中,芳基硫酸盐硫酸盐转移酶(ASST)是一种有趣的生物催化剂,因为它们使用简单的芳香族硫酸盐(如对硝基苯硫酸盐)作为供体,而依赖于PAPS的硫酸盐转移酶使用复杂且不稳定的PAPS作为供体。然而,关于Asst的研究很少(只有一种三维结构及其分子机制被描述,根据其生物化学或基因组背景暂定归类,只有一种天然供体和一种受体底物被鉴定)。根据我们对2244个Asst基因序列的初步系统发育分析,我们鉴定出19个分支具有合理的Boot-Trap值。与CAZY或Sulaflas数据库类似,实际的19个分支中的每一个都可能对应于不同的底物专一性或/和机制。然而,由于生化和结构数据稀缺,这一假设不能被今天的实验数据挑战。此外,许多分支(分支)与分类一致,这提出了一个明显的问题,即底物特异性可能是一个与分类相关的性状。在SulfASST项目中,我们使用了生物信息学、生物化学、酶学、结构生物学、分子建模和蛋白质工程的互补方法来获得关于Asst酶的大量信息。根据初步的系统发育分析,将表达19个亚科(支系)中的每一个代表,并对供体和受体底物进行筛选。6-8个经过合理选择的ASST代表的酶结晶学应该提供关于催化和选择性(底物、区域化学)的分子方面的宝贵细节。定向酶进化(KnowVolution)和建模将允许为生物技术目的获得量身定制的生物催化剂。最后,对ASSTS的深入描述和所获得结果的合理化将能够:确定底物专一性是否与系统发育相关;了解ASSTS基因的基因组背景是否指示底物或生物活性;破译底物专一性/混杂和区域选择性的结构决定因素;确定酶机制是否在不同的亚家族(分支)中保守;通过分子建模预测底物的选择性和区域选择性。

项目成果

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Dr. Mehdi Davari Dolatabadi, Ph.D.其他文献

Dr. Mehdi Davari Dolatabadi, Ph.D.的其他文献

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{{ truncateString('Dr. Mehdi Davari Dolatabadi, Ph.D.', 18)}}的其他基金

Machine learning approaches for faster discovery and adaptation of enzymes for difficult chemical reactions (MacBioSyn). Part I: providing solutions for regioselective oxygenations by 2OGD oxidases
机器学习方法可更快地发现和适应困难化学反应的酶 (MacBioSyn)。
  • 批准号:
    497207454
  • 财政年份:
  • 资助金额:
    --
  • 项目类别:
    Priority Programmes

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