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3 Publications visible to you, out of a total of 3
Toward Reproducible Enzyme Modeling with Isothermal Titration Calorimetry

Abstract (Expand)

To apply enzymes in technical processes, a detailed understanding of the molecular mechanisms is required. Kinetic and thermodynamic parameters of enzyme catalysis are crucial to plan, model, and … implement biocatalytic processes more efficiently. While the kinetic parameters, Km and kcat, are often accessible by optical methods, the determination of thermodynamic parameters requires more sophisticated methods. Isothermal titration calorimetry (ITC) allows the label-free and highly sensitive analysis of kinetic and thermodynamic parameters of individual steps in the catalytic cycle of an enzyme reaction. However, since ITC is susceptible to interferences due to denaturation or agglomeration of the enzymes, the homogeneity of the enzyme sample must always be considered, and this can be accomplished by means of dynamic light scattering (DLS) analysis. We here report on the use of an ITC-dependent work flow to determine both the kinetic and the thermodynamic data for a cofactor-dependent enzyme. Using a standardized approach with the implementation of sample quality control by DLS, we obtain high-quality data suitable for the advanced modeling of the enzyme reaction mechanism. Specifically, we investigated stereoselective reactions catalyzed by the NADPH-dependent ketoreductase Gre2p under different reaction conditions. The results revealed that this enzyme operates with an ordered sequential mechanism and is affected by substrate or product inhibition depending on the reaction buffer. Data reproducibility is ensured by specifying standard operating procedures, using programmed workflows for data analysis, and storing all data in a F.A.I.R. (findable, accessible, interoperable, and reusable) repository (https://doi.org/10.15490/fairdomhub.1.investigation.464.1). Our work highlights the utility for combined binding and kinetic studies for such complex multisubstrate reactions.

Authors: Felix Ott, Kersten S. Rabe, Christof M. Niemeyer, Gudrun Gygli

Date Published: 3rd Sep 2021

Publication Type: Journal

Simulation Foundry: Automated and F.A.I.R. Molecular Modeling

Abstract (Expand)

The Simulation Foundry (SF) is a modular workflow for the automated creation of molecular modeling (MM) data. MM allows for the reliable prediction of the microscopic and macroscopic properties of … multicomponent systems from first principles. The SF makes MM repeatable, replicable, and findable, accessible, interoperable, and reusable (F.A.I.R.). The SF uses a standardized data structure and file naming convention, allowing for replication on different supercomputers and re-entrancy. We focus on keeping the SF simple by basing it on scripting languages that are widely used by the MM community (bash, Python) and making it reusable and re-editable. The SF was developed to assist expert users in performing parameter studies of multicomponent systems by high throughput molecular dynamics simulations. The usability of the SF is demonstrated by simulations of thermophysical properties of binary mixtures. A standardized data exchange format enables the integration of simulated data with data from experiments. The SF also provides a complete documentation of how the results were obtained, thus assigning provenance. Increasing computational power facilitates the intensification of the simulation process and requires automation and modularity. The SF provides a community platform on which to integrate new methods and create data that is reproducible and transparent (https://fairdomhub.org/studies/639/snapshots/1, https://fairdomhub.org/studies/639/snapshots/2).

Authors: Gudrun Gygli, Juergen Pleiss

Date Published: 27th Apr 2020

Publication Type: Journal

Analysis of Thermophysical Properties of Deep Eutectic Solvents by Data Integration

Abstract

Not specified

Authors: Xinmeng Xu, Jan Range, Gudrun Gygli, Jürgen Pleiss

Date Published: 12th Mar 2020

Publication Type: Journal

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