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Enzyme kinetics studies the rates of biochemical reactions. Scientists monitor the reaction rates for a particular enzymatic reaction at various substrate concentrations. Additional trials with inhibitors or other molecules that affect the reaction rate may also be performed.
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For many years, scientists thought that enzyme-substrate binding took place in a simple "lock-and-key" fashion. This model stated that the enzyme and substrate fit together perfectly in one instantaneous step. However, current research supports a more refined view scientists call induced fit. The induced-fit model expands upon the lock-and-key model by describing a more dynamic interaction between enzyme and substrate. As the enzyme and substrate come together, their interaction causes...
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Unraveling Entropic Rate Acceleration Induced by Solvent Dynamics in Membrane Enzymes
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Challenges for an enzymatic reaction kinetics database.

Ulrike Wittig1, Maja Rey, Renate Kania

  • 1Scientific Databases and Visualization Group, Heidelberg Institute for Theoretical Studies (HITS), Germany.

The FEBS Journal
|October 30, 2013
PubMed
Summary
This summary is machine-generated.

Extracting biochemical reaction kinetics data from scientific literature is challenging due to unstructured information. The SABIO-RK database and improved data standards aim to streamline this process for computational modeling and biological understanding.

Keywords:
biocurationdatabaseontologyreaction kineticsstandardization

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Area of Science:

  • Biochemistry
  • Computational Biology
  • Bioinformatics

Background:

  • Scientific literature contains vast amounts of kinetic data crucial for understanding cellular processes via computational modeling.
  • Extracting this data is time-consuming for biocurators and modelers due to information being unstructured and lacking standardized terminology.
  • Existing biological databases offer unified structures and searchability, aiding data analysis for modeling.

Purpose of the Study:

  • To review the challenges in curating and integrating biochemical reaction kinetics data from publications.
  • To highlight the development and utility of the SABIO-RK database for reaction kinetics.
  • To inform experimentalists about data integration issues and suggest improvements for data accessibility.

Main Methods:

  • Analysis of publications for kinetic data extraction challenges.
  • Description of the development process for the SABIO-RK database.
  • Review of initiatives and tools for structured data publishing and ontology annotation.

Main Results:

  • Identification of significant challenges in extracting and standardizing kinetic data from literature.
  • Development of the SABIO-RK database to consolidate biochemical reaction kinetics information.
  • Highlighting the need for standardized data formats and community efforts to improve data accessibility.

Conclusions:

  • Incompletely and imprecisely written publications pose significant data integration challenges.
  • The SABIO-RK database offers a structured approach to managing biochemical reaction kinetics data.
  • Community initiatives and tools are essential for simplifying structured data publishing and enhancing data usability for modeling.