Computer-aided, resistance gene-guided genome mining for proteasome and HMG-CoA reductase inhibitors.
Computer-aided, resistance gene-guided genome mining for proteasome and HMG-CoA reductase inhibitors.
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DOI：
10.1093/jimb/kuad045
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发表时间：
2023-02-17
影响因子：
3.4
通讯作者：
中科院分区：
文献类型：
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作者：
次级代谢物（SM）是具有生物活性的小分子，其中许多具有医学价值。真菌基因组中含有大量的SM生物合成基因簇（BGC），其产物未知，这表明大量有价值的SM仍有待发现。然而，在真菌中存在的数百万种产生有用化合物的SM BGC中鉴定SM BGC具有挑战性。一种解决方案是抗性基因引导的基因组挖掘，它利用了这样一个事实，即一些BGC含有编码BGC产生的化合物所靶向的蛋白质的抗性版本的基因。这种BGC的生物信息学特征是它们含有不具有SM生物合成功能的必需基因的等位基因，并且在基因组中的其他地方存在第二等位基因。我们已经开发了一种计算机辅助的耐药基因引导的基因组挖掘方法，允许用户查询大型数据库中的BGC，这些BGC可以产生具有治疗目的的化合物。我们使用MycoCosm基因组数据库，应用这种方法寻找靶向蛋白酶体β6亚基（蛋白酶体抑制剂费卢命B的靶点）或HMG-CoA还原酶（降胆固醇治疗药物（如洛伐他汀）的靶点）的SM BGC。我们的方法被证明是有效的，发现已知的非鲁他汀和洛伐他汀BGC以及非鲁他汀和洛伐他汀相关的BGC与SM基因的变异，表明它们可能产生非鲁他胺和洛伐他汀的结构变体。令人欣慰的是，我们还发现了与洛伐他汀BGC不密切相关的BGC，但它们可以产生新的HMG-CoA还原酶抑制剂。一种新的计算机辅助的方法，抗性基因导向的基因组挖掘报告沿着其使用，以确定真菌的生物合成基因簇，产生蛋白酶体和HMG-CoA还原酶抑制剂。
Secondary metabolites (SMs) are biologically active small molecules, many of which are medically valuable. Fungal genomes contain vast numbers of SM biosynthetic gene clusters (BGCs) with unknown products, suggesting that huge numbers of valuable SMs remain to be discovered. It is challenging, however, to identify SM BGCs, among the millions present in fungi, that produce useful compounds. One solution is resistance gene-guided genome mining, which takes advantage of the fact that some BGCs contain a gene encoding a resistant version of the protein targeted by the compound produced by the BGC. The bioinformatic signature of such BGCs is that they contain an allele of an essential gene with no SM biosynthetic function, and there is a second allele elsewhere in the genome. We have developed a computer-assisted approach to resistance gene-guided genome mining that allows users to query large databases for BGCs that putatively make compounds that have targets of therapeutic interest. Working with the MycoCosm genome database, we have applied this approach to look for SM BGCs that target the proteasome β6 subunit, the target of the proteasome inhibitor fellutamide B, or HMG-CoA reductase, the target of cholesterol reducing therapeutics such as lovastatin. Our approach proved effective, finding known fellutamide and lovastatin BGCs as well as fellutamide- and lovastatin-related BGCs with variations in the SM genes that suggest they may produce structural variants of fellutamides and lovastatin. Gratifyingly, we also found BGCs that are not closely related to lovastatin BGCs but putatively produce novel HMG-CoA reductase inhibitors. A new computer-assisted approach to resistance gene-directed genome mining is reported along with its use to identify fungal biosynthetic gene clusters that putatively produce proteasome and HMG-CoA reductase inhibitors.
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影响因子：
16.5
作者：
Chen, A. J.;Frisvad, J. C.;Sun, B. D.;Varga, J.;Kocsube, S.;Dijksterhuis, J.;Kim, D. H.;Hong, S. -B.;Houbraken, J.;Samson, R. A.
通讯作者：
Samson, R. A.
DOI：
10.1073/pnas.1205532110
发表时间：
2013-01-02
影响因子：
11.1
作者：
Andersen, Mikael R.;Nielsen, Jakob B.;Mortensen, Uffe H.
通讯作者：
Mortensen, Uffe H.
影响因子：
4.8
作者：
Drott, M. T.;Bastos, R. W.;Greco, C.
通讯作者：
Greco, C.
影响因子：
5.2
作者：
Anyaogu DC;Mortensen UH
通讯作者：
Mortensen UH
DOI：
10.1083/jcb.201210077
发表时间：
2012-11-12
期刊：
The Journal of cell biology
影响因子：
--
作者：
Goldberg AL
通讯作者：
Goldberg AL