Current and Emerging Tools of Computational Biology To Improve the Detoxification of Mycotoxins
Current and Emerging Tools of Computational Biology To Improve the Detoxification of Mycotoxins
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DOI：
10.1128/aem.02102-21
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发表时间：
2022-02-01
影响因子：
4.4
通讯作者：
Momeni，Babak
中科院分区：
文献类型：
--
作者：
Sandlin，Natalie;Kish，Darius Russell;Momeni，Babak
生物有机体具有清除环境中毒素的丰富潜力，但识别合适的候选者并对其进行改进仍然具有挑战性。我们探索使用计算工具来发现解毒有害化合物的菌株和酶。我们特别关注霉菌毒素（真菌产生的毒素，会污染食品和饲料）以及能够降低其危害的生物酶。我们讨论使用已建立的和新颖的计算工具来补充三个方向上的现有经验数据：发现未充分探索的生物体解毒的前景，发现有助于解毒的重要细胞过程，以及提高解毒酶的性能。我们希望在计算生物学和生物修复领域的研究人员之间建立协同对话。我们展示了开放的生物修复问题，计算研究人员可以在其中做出贡献，并强调可以使生物修复研究人员受益的相关现有和新兴计算工具。
Biological organisms carry a rich potential for removing toxins from our environment, but identifying suitable candidates and improving them remain challenging. We explore the use of computational tools to discover strains and enzymes that detoxify harmful compounds. In particular, we focus on mycotoxins—fungus-produced toxins that contaminate food and feed—and biological enzymes that are capable of rendering them less harmful. We discuss the use of established and novel computational tools to complement existing empirical data in three directions: discovering the prospect of detoxification among underexplored organisms, finding important cellular processes that contribute to detoxification, and improving the performance of detoxifying enzymes. We hope to create a synergistic conversation between researchers in computational biology and those in the bioremediation field. We showcase open bioremediation questions where computational researchers can contribute and highlight relevant existing and emerging computational tools that could benefit bioremediation researchers.