From nature to industry: Harnessing enzymes for biocatalysis

Science, Journal Year: 2023, Volume and Issue: 382(6673)

Published: Nov. 23, 2023

Biocatalysis harnesses enzymes to make valuable products. This green technology is used in countless applications from bench scale industrial production and allows practitioners access complex organic molecules, often with fewer synthetic steps reduced waste. The last decade has seen an explosion the development of experimental computational tools tailor enzymatic properties, equipping enzyme engineers ability create biocatalysts that perform reactions not present nature. By using (chemo)-enzymatic synthesis routes or orchestrating intricate cascades, scientists can synthesize elaborate targets ranging DNA pharmaceuticals starch made vitro CO2-derived methanol. In addition, new chemistries have emerged through combination biocatalysis transition metal catalysis, photocatalysis, electrocatalysis. review highlights recent key developments, identifies current limitations, provides a future prospect for this rapidly developing technology.

Language: Английский

---

Advances in microbial exoenzymes bioengineering for improvement of bioplastics degradation

Chemosphere, Journal Year: 2024, Volume and Issue: 355, P. 141749 - 141749

Published: March 21, 2024

Plastic pollution has become a major global concern, posing numerous challenges for the environment and wildlife. Most conventional ways of plastics degradation are inefficient cause great damage to ecosystems. The development biodegradable offers promising solution waste management. These designed break down under various conditions, opening up new possibilities mitigate negative impact traditional plastics. Microbes, including bacteria fungi, play crucial role in bioplastics by producing secreting extracellular enzymes, such as cutinase, lipases, proteases. However, these microbial enzymes sensitive extreme environmental temperature acidity, affecting their functions stability. To address challenges, scientists have employed protein engineering immobilization techniques enhance enzyme stability predict structures. Strategies improving substrate interaction, increasing thermostability, reinforcing bonding between active site substrate, refining activity being utilized boost functionality. Recently, bioengineering through gene cloning expression potential microorganisms, revolutionized biodegradation bioplastics. This review aimed discuss most recent strategies modifying bioplastic-degrading terms functionality, thermostability enhancement, binding site, with other improvement surface action. Additionally, discovered exoenzymes metagenomics were emphasized.

Language: Английский

---

Engineering Enzymes for Environmental Sustainability

Angewandte Chemie International Edition, Journal Year: 2023, Volume and Issue: 62(52)

Published: Aug. 31, 2023

Abstract The development and implementation of sustainable catalytic technologies is key to delivering our net‐zero targets. Here we review how engineered enzymes, with a focus on those developed using directed evolution, can be deployed improve the sustainability numerous processes help conserve environment. Efficient robust biocatalysts have been capture carbon dioxide (CO 2 ) embedded into new efficient metabolic CO fixation pathways. Enzymes refined for bioremediation, enhancing their ability degrade toxic harmful pollutants. Biocatalytic recycling gaining momentum, cutinases PETases depolymerization abundant plastic, polyethylene terephthalate (PET). Finally, biocatalytic approaches accessing petroleum‐based feedstocks chemicals are expanding, optimized enzymes convert plant biomass biofuels or other high value products. Through these examples, hope illustrate enzyme engineering biocatalysis contribute cleaner more chemical industry.

Language: Английский

---

A versatile microbial platform as a tunable whole-cell chemical sensor

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Sept. 27, 2024

Language: Английский

---

Imine Reductases and Reductive Aminases in Organic Synthesis

ACS Catalysis, Journal Year: 2024, Volume and Issue: unknown, P. 14308 - 14329

Published: Sept. 12, 2024

Language: Английский

---

Data‐Driven Protein Engineering for Improving Catalytic Activity and Selectivity

ChemBioChem, Journal Year: 2023, Volume and Issue: 25(3)

Published: Nov. 29, 2023

Abstract Protein engineering is essential for altering the substrate scope, catalytic activity and selectivity of enzymes applications in biocatalysis. However, traditional approaches, such as directed evolution rational design, encounter challenge dealing with experimental screening process a large protein mutation space. Machine learning methods allow approximation fitness landscapes identification patterns using limited data, thus providing new avenue to guide campaigns. In this concept article, we review machine models that have been developed assess enzyme‐substrate‐catalysis performance relationships aiming improve through data‐driven engineering. Furthermore, prospect future development field provide additional strategies tools achieving desired activities selectivities.

Language: Английский

---

Selection of a promiscuous minimalist cAMP phosphodiesterase from a library of de novo designed proteins

Nature Chemistry, Journal Year: 2024, Volume and Issue: 16(7), P. 1200 - 1208

Published: May 3, 2024

Abstract The ability of unevolved amino acid sequences to become biological catalysts was key the emergence life on Earth. However, billions years evolution separate complex modern enzymes from their simpler early ancestors. To probe how can develop new functions, we use ultrahigh-throughput droplet microfluidics screen for phosphoesterase activity amidst a library more than one million based de novo designed 4-helix bundle. Characterization hits revealed that acquisition function involved large jump in sequence space enriching truncations removed >40% protein chain. Biophysical characterization catalytically active truncated it dimerizes into an α-helical structure, with gain accompanied by increased structural dynamics. identified phosphodiesterase is manganese-dependent metalloenzyme hydrolyses range phosphodiesters. It most towards cyclic AMP, rate acceleration ~10 9 and catalytic proficiency >10 14 M −1 , comparable larger shaped evolution.

Language: Английский

---

On synergy between ultrahigh throughput screening and machine learning in biocatalyst engineering

Faraday Discussions, Journal Year: 2024, Volume and Issue: 252, P. 89 - 114

Published: Jan. 1, 2024

Protein design and directed evolution have separately contributed enormously to protein engineering. Without being mutually exclusive, the former relies on computation from first principles, while latter is a combinatorial approach based chance. Advances in ultrahigh throughput (uHT) screening, next generation sequencing machine learning may create alternative routes engineered proteins, where functional information linked specific sequences interpreted extrapolated

Language: Английский

---

Addressing epistasis in the design of protein function

Proceedings of the National Academy of Sciences, Journal Year: 2024, Volume and Issue: 121(34)

Published: Aug. 12, 2024

Mutations in protein active sites can dramatically improve function. The site, however, is densely packed and extremely sensitive to mutations. Therefore, some mutations may only be tolerated combination with others a phenomenon known as epistasis. Epistasis reduces the likelihood of obtaining improved functional variants slows natural lab evolutionary processes. Research has shed light on molecular origins epistasis its role shaping trajectories outcomes. In addition, sequence- AI-based strategies that infer epistatic relationships from mutational patterns or experimental evolution data have been used design variants. recent years, combinations such approaches atomistic calculations successfully predicted highly combinatorial sites. These were thousands active-site variants, demonstrating that, while our understanding remains incomplete, determinants are critical for accurate now sufficiently understood. We conclude space explored by expanded enhance activities discover new ones. Furthermore, opens way systematically exploring sequence structure impacts function, deepening control over activity.

Language: Английский

---

Revolutionizing Molecular Design for Innovative Therapeutic Applications through Artificial Intelligence

Molecules, Journal Year: 2024, Volume and Issue: 29(19), P. 4626 - 4626

Published: Sept. 29, 2024

The field of computational protein engineering has been transformed by recent advancements in machine learning, artificial intelligence, and molecular modeling, enabling the design proteins with unprecedented precision functionality. Computational methods now play a crucial role enhancing stability, activity, specificity for diverse applications biotechnology medicine. Techniques such as deep reinforcement transfer learning have dramatically improved structure prediction, optimization binding affinities, enzyme design. These innovations streamlined process allowing rapid generation targeted libraries, reducing experimental sampling, rational tailored properties. Furthermore, integration approaches high-throughput techniques facilitated development multifunctional novel therapeutics. However, challenges remain bridging gap between predictions validation addressing ethical concerns related to AI-driven This review provides comprehensive overview current state future directions engineering, emphasizing their transformative potential creating next-generation biologics advancing synthetic biology.

Language: Английский

---