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Enzymes have evolved to catalyse challenging chemical transformations with high efficiency and selectivity. Although a number of artificial systems have been developed to recapitulate the catalytic activity of natural enzymes, they are mostly limited to catalysing relatively simple reactions owing to their ability to mimic only the active metal centres of natural enzymes, without incorporating the proximal amino acids or cofactors. Here we report a metal–organic framework-based artificial enzyme (metal–organic–zyme, MOZ) by integrating active metal centres, proximal amino acids and other cofactors into a tunable metal–organic framework monolayer. We design two libraries of MOZs to perform photocatalytic CO2 reduction and water oxidation reactions. Through tuning the incorporated amino acids in the MOZs, we systematically optimize the activity and selectivity of these libraries. Combining these optimized MOZs into a single system realizes complete artificial photosynthesis in the reaction of (1 + n) CO2 + 2H2O → CH4 + nCO + (2 + n/2)O2.
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Comprehensive phylogenetic analysis of the ribonucleotide reductase family reveals an ancestral clade
Billions of years ago, the Earth’s atmosphere had very little oxygen. It was only after some bacteria and early plants evolved to harness energy from sunlight that oxygen began to fill the Earth’s environment. Oxygen is highly reactive and can interfere with enzymes and other molecules that are essential to life. Organisms living at this point in history therefore had to adapt to survive in this new oxygen-rich world. An ancient family of enzymes known as ribonucleotide reductases are used by all free-living organisms and many viruses to repair and replicate their DNA. Because of their essential role in managing DNA, these enzymes have been around on Earth for billions of years. Understanding how they evolved could therefore shed light on how nature adapted to increasing oxygen levels and other environmental changes at the molecular level. One approach to study how proteins evolved is to use computational analysis to construct a phylogenetic tree. This reveals how existing members of a family are related to one another based on the chain of molecules (known as amino acids) that make up each protein. Despite having similar structures and all having the same function, ribonucleotide reductases have remarkably diverse sequences of amino acids. This makes it computationally very demanding to build a phylogenetic tree. To overcome this, Burnim, Spence, Xu et al. created a phylogenetic tree using structural information from a part of the enzyme that is relatively similar in many modern-day ribonucleotide reductases. The final result took seven continuous months on a supercomputer to generate, and includes over 6,000 members of the enzyme family. The phylogenetic tree revealed a new distinct group of ribonucleotide reductases that may explain how one adaptation to increasing levels of oxygen emerged in some family members, while another adaptation emerged in others. The approach used in this work also opens up a new way to study how other highly diverse enzymes and other protein families evolved, potentially revealing new insights about our planet’s past.
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- Award ID(s):
- 1942668
- PAR ID:
- 10387891
- Date Published:
- Journal Name:
- eLife
- Volume:
- 11
- ISSN:
- 2050-084X
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.7554/eLife.79790
