The Unexplored Importance of Fleeting Chiral Intermediates in Enzyme-Catalyzed Reactions

A kinetic analysis of coupled sequential enzyme reactions

10.26434/chemrxiv.5746065.v2 ◽

2018 ◽

Author(s):

Justin Eilertsen ◽

Santiago Schnell

Keyword(s):

Enzyme Assay ◽

Sequential Reaction ◽

Enzyme Reactions ◽

Indicator Reaction ◽

Single Substrate ◽

Complex Sequences ◽

Catalyzed Reactions ◽

Enzyme Catalyzed Reactions ◽

Single Enzyme

<div>As a case study, we consider a coupled enzyme assay of sequential enzyme reactions obeying the Michaelis--Menten reaction mechanism. The sequential reaction consists of a single-substrate, single-enzyme non-observable reaction followed by another single-substrate, single-enzyme observable reaction (indicator reaction). In this assay, the product of the non-observable reaction becomes the substrate of the indicator reaction. A mathematical analysis of the reaction kinetics is performed, and it is found that after an initial fast transient, the sequential reaction is described by a pair of interacting Michaelis--Menten equations. Timescales that approximate the respective lengths of the indicator and non-observable reactions, as well as conditions for the validity of the Michaelis--Menten equations are derived. The theory can be extended to deal with more complex sequences of enzyme catalyzed reactions.</div>

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A kinetic analysis of coupled sequential enzyme reactions

10.26434/chemrxiv.5746065.v1 ◽

2018 ◽

Author(s):

Justin Eilertsen ◽

Santiago Schnell

Keyword(s):

Enzyme Assay ◽

Sequential Reaction ◽

Enzyme Reactions ◽

Indicator Reaction ◽

Single Substrate ◽

Complex Sequences ◽

Catalyzed Reactions ◽

Enzyme Catalyzed Reactions ◽

Single Enzyme

<div>As a case study, we consider a coupled enzyme assay of sequential enzyme reactions obeying the Michaelis-Menten reaction mechanism. The sequential reaction consists of a single-substrate, single enzyme non-observable reaction followed by another single-substrate, single enzyme observable reaction (indicator reaction). In this assay, the product of the non-observable reaction becomes the substrate of the indicator reaction. A mathematical analysis of the reaction kinetics is performed, and it is found that after an initial fast transient, the sequential reaction is described by a pair of interacting Michaelis-Menten equations. Timescales that approximate the respective lengths of the indicator and non-observable reactions, as well as conditions for the validity of the Michaelis-Menten equations are derived. The theory can be extended to deal with more complex sequences of enzyme catalyzed reactions.</div>

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Computationally Augmented Retrosynthesis: Total Synthesis of Paspaline A and Emindole PB

10.26434/chemrxiv.7322330.v1 ◽

2018 ◽

Author(s):

Timothy Newhouse ◽

Daria E. Kim ◽

Joshua E. Zweig

Keyword(s):

Chemical Synthesis ◽

Total Synthesis ◽

Small Molecules ◽

First Principles ◽

Quantum Chemical ◽

Computational Analysis ◽

Empirical Evaluation ◽

Synthetic Strategy ◽

Catalyzed Reactions ◽

Enzyme Catalyzed Reactions

The diverse molecular architectures of terpene natural products are assembled by exquisite enzyme-catalyzed reactions. Successful recapitulation of these transformations using chemical synthesis is hard to predict from first principles and therefore challenging to execute. A means of evaluating the feasibility of such chemical reactions would greatly enable the development of concise syntheses of complex small molecules. Herein, we report the computational analysis of the energetic favorability of a key bio-inspired transformation, which we use to inform our synthetic strategy. This approach was applied to synthesize two constituents of the historically challenging indole diterpenoid class, resulting in a concise route to (–)-paspaline A in 9 steps from commercially available materials and the first pathway to and structural confirmation of emindole PB in 13 steps. This work highlights how traditional retrosynthetic design can be augmented with quantum chemical calculations to reveal energetically feasible synthetic disconnections, minimizing time-consuming and expensive empirical evaluation.

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Diverse Taxonomies for Diverse Chemistries: Enhanced Representation of Natural Product Metabolism in UniProtKB

Metabolites ◽

10.3390/metabo11010048 ◽

2021 ◽

Vol 11 (1) ◽

pp. 48

Author(s):

Marc Feuermann ◽

Emmanuel Boutet ◽

Anne Morgat ◽

Kristian Axelsen ◽

Parit Bansal ◽

...

Keyword(s):

Natural Products ◽

Natural Product ◽

Semantic Web Technologies ◽

Knowledge Resources ◽

Web Technologies ◽

Chemical Structures ◽

Biological Interest ◽

Catalyzed Reactions ◽

Enzyme Catalyzed Reactions ◽

Practical Demonstration

The UniProt Knowledgebase UniProtKB is a comprehensive, high-quality, and freely accessible resource of protein sequences and functional annotation that covers genomes and proteomes from tens of thousands of taxa, including a broad range of plants and microorganisms producing natural products of medical, nutritional, and agronomical interest. Here we describe work that enhances the utility of UniProtKB as a support for both the study of natural products and for their discovery. The foundation of this work is an improved representation of natural product metabolism in UniProtKB using Rhea, an expert-curated knowledgebase of biochemical reactions, that is built on the ChEBI (Chemical Entities of Biological Interest) ontology of small molecules. Knowledge of natural products and precursors is captured in ChEBI, enzyme-catalyzed reactions in Rhea, and enzymes in UniProtKB/Swiss-Prot, thereby linking chemical structure data directly to protein knowledge. We provide a practical demonstration of how users can search UniProtKB for protein knowledge relevant to natural products through interactive or programmatic queries using metabolite names and synonyms, chemical identifiers, chemical classes, and chemical structures and show how to federate UniProtKB with other data and knowledge resources and tools using semantic web technologies such as RDF and SPARQL. All UniProtKB data are freely available for download in a broad range of formats for users to further mine or exploit as an annotation source, to enrich other natural product datasets and databases.

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