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生物催化剂设计的组合与计算挑战

Combinatorial and computational challenges for biocatalyst design.

作者信息

Arnold F H

机构信息

Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena 91125, USA.

出版信息

Nature. 2001 Jan 11;409(6817):253-7. doi: 10.1038/35051731.

Abstract

Nature provides a fantastic array of catalysts extremely well suited to supporting life, but usually not so well suited for technology. Whether biocatalysis will have a significant technological impact depends on our finding robust routes for tailoring nature's catalysts or redesigning them anew. Laboratory evolution methods are now used widely to fine-tune the selectivity and activity of enzymes. The current rapid development of these combinatorial methods promises solutions to more complex problems, including the creation of new biosynthetic pathways. Computational methods are also developing quickly. The marriage of these approaches will allow us to generate the efficient, effective catalysts needed by the pharmaceutical, food and chemicals industries and should open up new opportunities for producing energy and chemicals from renewable resources.

摘要

大自然提供了一系列极为出色的催化剂,它们非常适合维持生命,但通常不太适合技术应用。生物催化是否会对技术产生重大影响,取决于我们能否找到完善的途径来定制大自然的催化剂或重新设计它们。实验室进化方法如今被广泛用于微调酶的选择性和活性。这些组合方法当前的快速发展有望解决更复杂的问题,包括创建新的生物合成途径。计算方法也在迅速发展。这些方法的结合将使我们能够生成制药、食品和化工行业所需的高效、有效的催化剂,并应为从可再生资源生产能源和化学品开辟新机遇。

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