minChemBio:利用最小的过渡扩展化学合成与化学酶途径。

IF 3.9 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
ACS Synthetic Biology Pub Date : 2025-03-21 Epub Date: 2025-02-14 DOI:10.1021/acssynbio.4c00692
Mohit Anand, Vikas Upadhyay, Costas D Maranas
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引用次数: 0

摘要

化学-酶途径设计旨在结合酶与化学合成的优势,更有效地穿越生物分子设计空间。当化学反应经常与区域选择性和立体选择性作斗争时,酶转化经常遇到低酶活性或可用性的限制。最佳地整合这两种方法提供了一个机会,以确定超越任何一种模式的能力的有效途径。最近,研究表明利用酶的步骤进入工业规模的化学过程的优势,例如血糖调节剂西格列汀(默克)和HIV蛋白酶抑制剂Darunavir (Prozomix)。设计最佳的化学-酶途径是一项复杂的任务。它需要导航一个高维的潜在反应搜索空间,这些反应结合了单个化学和生物化学步骤,同时最小化化学催化和生物反应之间的过渡。在这里,我们介绍了一种算法方法minChemBio,它依赖于通过分别从美国专利局(USPTO)和MetaNetX数据库中提取的已知化学和酶的步骤进行优化搜索来解决混合整数线性规划(MILP)问题。minChemBio允许最小化途径中化学和生物反应之间的过渡,从而减少了对昂贵的分离和纯化步骤的需求。minChemBio以3个案例研究为基准,涉及2-5-呋喃二甲酸、对苯二甲酸酯和3-羟基丁酸酯的合成。确定的设计既包括已建立的文献途径,也包括未探索的途径,这些途径与现有的反合成工具确定的途径进行了比较。minChemBio通过控制和最小化化学催化和生物催化步骤之间的转换,填补了目前途径反合成工具的空白。用户可以通过开源代码(https://github.com/maranasgroup/chemo-enz)访问它。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
minChemBio: Expanding Chemical Synthesis with Chemo-Enzymatic Pathways Using Minimal Transitions.

Chemo-enzymatic pathway design aims to combine the strengths of enzymatic with chemical synthesis to traverse biomolecular design space more efficiently. While chemical reactions often struggle with regioselectivity and stereoselectivity, enzymatic conversions often encounter limitations of low enzyme activity or availability. Optimally integrating both approaches provides an opportunity to identify efficient pathways beyond the capabilities of either modality. Recently, studies have shown the advantage of leveraging enzymatic steps into industrial-scale chemical processes, such as for the blood sugar regulator Sitagliptin (Merck) and the HIV protease inhibitor Darunavir (Prozomix). Designing optimal chemo-enzymatic pathways is a complex task. It requires navigating a high-dimensional search space of potential reactions that combine individual chemical and biochemical steps while at the same time minimizing transitions between chemical catalysis and bioreactions. Here, we introduce an algorithmic approach, minChemBio, that relies on solving a mixed-integer linear programming (MILP) problem by optimally searching through known chemical and enzymatic steps extracted from the United States Patent Office (USPTO) and MetaNetX databases, respectively. minChemBio allows for the minimization of transitions between chemical and biological reactions in the pathway, thus reducing the need for costly separation and purification steps required. minChemBio was benchmarked on three case studies involving the synthesis of 2-5-furandicarboxylic acid, terephthalate, and 3-hydroxybutyrate. Identified designs included both established literature pathways as well as unexplored ones which were compared against pathways identified by existing retrosynthetic tools. minChemBio fills a current gap in the space of pathway retrosynthesis tools by controlling and minimizing the transitions between chemical catalysis and biocatalytic steps. It is accessible to users through open-source code (https://github.com/maranasgroup/chemo-enz).

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来源期刊
CiteScore
8.00
自引率
10.60%
发文量
380
审稿时长
6-12 weeks
期刊介绍: The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism. Topics may include, but are not limited to: Design and optimization of genetic systems Genetic circuit design and their principles for their organization into programs Computational methods to aid the design of genetic systems Experimental methods to quantify genetic parts, circuits, and metabolic fluxes Genetic parts libraries: their creation, analysis, and ontological representation Protein engineering including computational design Metabolic engineering and cellular manufacturing, including biomass conversion Natural product access, engineering, and production Creative and innovative applications of cellular programming Medical applications, tissue engineering, and the programming of therapeutic cells Minimal cell design and construction Genomics and genome replacement strategies Viral engineering Automated and robotic assembly platforms for synthetic biology DNA synthesis methodologies Metagenomics and synthetic metagenomic analysis Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction Gene optimization Methods for genome-scale measurements of transcription and metabolomics Systems biology and methods to integrate multiple data sources in vitro and cell-free synthetic biology and molecular programming Nucleic acid engineering.
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