Dutta Kunal, Shityakov Sergey, Khalifa Ibrahim
Department of Human Physiology, Vidyasagar University, Medinipur, India.
Department of Chemoinformatics, Infochemistry Scientific Center, Saint Petersburg National Research University of Information Technologies, Mechanics and Optics (ITMO University), Saint-Petersburg, Russia.
Front Bioeng Biotechnol. 2021 Aug 2;9:666858. doi: 10.3389/fbioe.2021.666858. eCollection 2021.
Today's environmental balance has been compromised by the unreasonable and sometimes dangerous actions committed by humans to maintain their dominance over the Earth's natural resources. As a result, oceans are contaminated by the different types of plastic trash, crude oil coming from mismanagement of transporting ships spilling it in the water, and air pollution due to increasing production of greenhouse gases, such as CO and CH ., into the atmosphere. The lands, agricultural fields, and groundwater are also contaminated by the infamous chemicals , polycyclic aromatic hydrocarbons, pyrethroids pesticides, bisphenol-A, and dioxanes. Therefore, bioremediation might function as a convenient alternative to restore a clean environment. However, at present, the majority of bioremediation reports are limited to the natural capabilities of microbial enzymes. Synthetic biology with uncompromised supervision of ethical standards could help to outsmart nature's engineering, such as the CETCH cycle for improved CO fixation. Additionally, a blend of synthetic biology with machine learning algorithms could expand the possibilities of bioengineering. This review summarized current state-of-the-art knowledge of the data-assisted enzyme redesigning to actively promote new research on important enzymes to ameliorate the environment.
如今，人类为维持对地球自然资源的主导地位而采取的不合理甚至危险的行为，已经破坏了环境平衡。结果，海洋受到了不同类型塑料垃圾、运输船只管理不善导致原油泄漏以及温室气体（如一氧化碳和甲烷）排放增加造成的空气污染的污染。陆地、农田和地下水也受到了臭名昭著的化学物质、多环芳烃、拟除虫菊酯类农药、双酚A和二恶烷的污染。因此，生物修复可能是恢复清洁环境的一种便捷替代方法。然而，目前大多数生物修复报告仅限于微生物酶的天然能力。在严格的道德标准监督下，合成生物学有助于超越自然工程，比如用于改善二氧化碳固定的CETCH循环。此外，合成生物学与机器学习算法的结合可以扩大生物工程的可能性。本综述总结了数据辅助酶重新设计的当前最新知识，以积极推动对重要酶的新研究，从而改善环境。
