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

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Perspectives on Computational Enzyme Modeling: From Mechanisms to Design and Drug Development

ACS Omega, Journal Year: 2024, Volume and Issue: unknown

Published: Feb. 8, 2024

Understanding enzyme mechanisms is essential for unraveling the complex molecular machinery of life. In this review, we survey field computational enzymology, highlighting key principles governing and discussing ongoing challenges promising advances. Over years, computer simulations have become indispensable in study mechanisms, with integration experimental exploration now established as a holistic approach to gain deep insights into enzymatic catalysis. Numerous studies demonstrated power characterizing reaction pathways, transition states, substrate selectivity, product distribution, dynamic conformational changes various enzymes. Nevertheless, significant remain investigating multistep reactions, large-scale changes, allosteric regulation. Beyond mechanistic studies, modeling has emerged an tool computer-aided design rational discovery covalent drugs targeted therapies. Overall, design/engineering drug development can greatly benefit from our understanding detailed enzymes, such protein dynamics, entropy contributions, allostery, revealed by studies. Such convergence different research approaches expected continue, creating synergies research. This outlining ever-expanding research, aims provide guidance future directions facilitate new developments important evolving field.

Language: Английский

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AlphaFold two years on: Validation and impact

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

Published: Aug. 12, 2024

Two years on from the initial release of AlphaFold, we have seen its widespread adoption as a structure prediction tool. Here, discuss some latest work based with particular focus use within structural biology community. This encompasses cases like speeding up determination itself, enabling new computational studies, and building tools workflows. We also look at ongoing validation predictions continue to be compared against large numbers experimental structures further delineate model’s capabilities limitations.

Language: Английский

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Harnessing conformational dynamics in enzyme catalysis to achieve nature-like catalytic efficiencies: the shortest path map tool for computational enzyme redesign

Faraday Discussions, Journal Year: 2024, Volume and Issue: 252, P. 306 - 322

Published: Jan. 1, 2024

It is challenging to identify enzyme mutations that enhance specific conformational changes.We develop the shortest path map method address this challenge.

Language: Английский

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Directed Evolution of Protoglobin Optimizes the Enzyme Electric Field

Journal of the American Chemical Society, Journal Year: 2024, Volume and Issue: 146(24), P. 16670 - 16680

Published: June 7, 2024

To unravel why computational design fails in creating viable enzymes, while directed evolution (DE) succeeds, our research delves into the laboratory of protoglobin. DE has adapted this protein to efficiently catalyze carbene transfer reactions. We show that previously proposed enhanced substrate access and binding alone cannot account for increased yields during DE. The 3D electric field entire active site is tracked through dynamics, clustered using affinity propagation algorithm, subjected principal component analysis. This analysis reveals notable changes with DE, where distinct topologies influence transition state energetics mechanism. A chemically meaningful emerges takes lead facilitates crossing barrier transfer. Our findings underscore intrinsic dynamic's on enzyme function, ability switch mechanisms within same protein, crucial role design.

Language: Английский

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Integration of a Randomized Sequence Scanning Approach in AlphaFold2 and Local Frustration Profiling of Conformational States Enable Interpretable Atomistic Characterization of Conformational Ensembles and Detection of Hidden Allosteric States in the ABL1 Protein Kinase

Journal of Chemical Theory and Computation, Journal Year: 2024, Volume and Issue: 20(12), P. 5317 - 5336

Published: June 12, 2024

Despite the success of AlphaFold methods in predicting single protein structures, these showed intrinsic limitations characterization multiple functional conformations allosteric proteins. The recent NMR-based structural determination unbound ABL kinase active state and discovery inactive low-populated that are unique for present an ideal challenge AlphaFold2 approaches. In current study, we employ several adaptations methodology to predict conformational ensembles states including randomized alanine sequence scanning combined with alignment subsampling proposed this study. We show new adaptation local frustration profiling enables accurate prediction structures ensembles, also offering a robust approach interpretable predictions detection hidden states. found large high residue clusters uniquely characteristic low-populated, fully form can define energetically frustrated cracking sites transitions, presenting difficult targets AlphaFold2. results study uncovered previously unappreciated fundamental connections between profiles ability This integration landscape-based analysis allows atomistic providing physical basis successes detecting play significant role regulation.

Language: Английский

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A novel shark VNAR antibody-based immunotoxin targeting TROP-2 for cancer therapy

Acta Pharmaceutica Sinica B, Journal Year: 2024, Volume and Issue: 14(11), P. 4806 - 4818

Published: Aug. 27, 2024

TROP-2, a tumor-associated antigen, has been implicated in the progression of various epithelial tumors. Due to its favorable expression profile, TROP-2 emerged as promising target for antibody–drug conjugates (ADCs) based anti-tumor therapies. Although ADCs have shown efficacy cancer treatment, their application solid tumors is hindered by high molecular weight, poor tumor penetration, and release cytotoxic molecules. Therefore, recombinant immunotoxin was developed on shark-derived variable domain immunoglobulin new antigen receptor (VNAR) antibody. VNARs are only one-tenth size IgG antibodies possess remarkable tissue penetration capabilities stability. In this study, shark VNAR phage display library created, leading identification VNAR-5G8 that targets TROP-2. exhibited affinity cellular internalization ability towards cells expressing levels Epitope analysis revealed recognizes hidden epitope consisting CRD TY-1 Subsequently, fused with truncated form Pseudomonas exotoxin (PE38) create (5G8-PE38), which significant activity vitro vivo. Overall, study highlights promise 5G8-PE38 valuable candidate therapy.

Language: Английский

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Perspectives on flow biocatalysis: the engine propelling enzymatic reactions

Journal of Flow Chemistry, Journal Year: 2023, Volume and Issue: 14(1), P. 211 - 218

Published: Oct. 23, 2023

Abstract Flow biocatalysis has emerged as an empowering tool to boost the potential of enzymatic reactions towards more automatized, sustainable, and generally efficient synthetic processes. In last fifteen years, increasing number biocatalytic transformations carried out in continuous flow exemplified benefits that this technology can bring incorporate into industrial operations. This perspective aims capture a nutshell available methodologies for well discuss current limitations future directions field. Graphical abstract

Language: Английский

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Unlocking novel therapies: cyclic peptide design for amyloidogenic targets through synergies of experiments, simulations, and machine learning

Chemical Communications, Journal Year: 2023, Volume and Issue: 60(6), P. 632 - 645

Published: Dec. 7, 2023

Proposed de novo peptide design strategy against amyloidogenic targets. After initial computational preparation of the binder and target, experimental validation are incorporated in iterative machine learning powered cycles to generate better improved peptide-based

Language: Английский

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Advancing microbial production through artificial intelligence-aided biology

Biotechnology Advances, Journal Year: 2024, Volume and Issue: 74, P. 108399 - 108399

Published: June 24, 2024

Language: Английский

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