Abstract
The kinetics of featured interactions (KOFFI) database is a novel tool and resource for binding kinetics data from biomolecular interactions. While binding kinetics data are abundant in literature, finding valuable information is a laborious task. We used text extraction methods to store binding rates (association, dissociation) as well as corresponding meta-information (e.g. methods, devices) in a novel database. To date, over 270 articles were manually curated and binding data on over 1705 interactions was collected and stored in the (KOFFI) database. Moreover, the KOFFI database application programming interface was implemented in Anabel (open-source software for the analysis of binding interactions), enabling users to directly compare their own binding data analyses with related experiments described in the database.
Highlights
A key step in the understanding of all biological processes lies in describing the underlying interactions between biomolecules
In drug discovery, characterizing binding properties of antibody–antigen, enzyme–inhibitor or receptor–ligand interactions plays a crucial role in identifying suitable drug candidates
This coincides with the notion that it is not the affinity of a drug itself which determines its efficacy, but the association and dissociation rate, the latter being inversely related to the ‘residence-time’ or ‘dissociative half-life’ of the complex, as has been proposed periodically throughout the past decade [2,3,4,5,6]
Summary
A key step in the understanding of all biological processes lies in describing the underlying interactions between biomolecules. Studies have shown that not all detection methods and devices yield similar binding rates for the same interaction, especially in the case of methods using labeling techniques, as they utilize either non-native proteins and/or ligands with potentially different binding properties [7,8] With this change in the awareness and understanding of underlying processes comes an increase in demand for high-quality binding kinetics data. Some databases annotating KD or IC50 values exist (Table 1), a more general resource containing association and dissociation rates combined with crucial information on the experimental set-up is missing to our knowledge The intent of this project was to fill this gap by creating a database to collect and store binding kinetics data mainly for label-free detection methods extracted from literature with related information about the performed experiments for kon and koff determination, providing reference data for future experiments and highquality data for data mining projects. It is hoped that this database will lay a foundation which can be used for further development in the future
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