KOFFI and Anabel 2.0-a new binding kinetics database and its integration in an open-source binding analysis software.

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.

Comparison of different label-free imaging high-throughput biosensing systems for aptamer binding measurements using thrombin aptamers.

To enable the analysis of several hundreds to thousands of interactions in parallel, high-throughput systems were developed. We used established thrombin aptamer assays to compare three such high-throughput imaging systems as well as analysis software and user influence. In addition to our own iRIf-system, we applied bscreen and IBIS-MX96. As non-imaging reference systems we used Octet-RED96, Biacore3000, and Monolith-NT.115. In this study we measured 1378 data points. Our results show that all systems are suitable for analyzing binding kinetics, but the kinetic constants as well as the ranking of the selected aptamers depend significantly on the applied system and user. We provide an insight into the signal generation principles, the systems and the results generated for thrombin aptamers. It should contribute to the awareness that binding constants cannot be determined as easily as other constants. Since many parameters like surface chemistry, biosensor type and buffer composition may change binding behavior, the experimenter should be aware that a system and assay dependent KD is determined. Frequently, certain conditions that are best suited for a given biosensing system cannot be transferred to other systems. Therefore, we strongly recommend using at least two different systems in parallel to achieve meaningful results.

Boosting AthaMap Database Content with Data from Protein Binding Microarrays.

The AthaMap database generates a map of predicted transcription factor binding sites (TFBS) and small RNA target sites for the whole Arabidopsis thaliana genome. With the advent of protein binding microarrays (PBM), the number of known TFBS for A. thaliana transcription factors (TFs) has increased dramatically. Using 113 positional weight matrices (PWMs) generated from a single PBM study and representing a total number of 68 different TFs, the number of predicted TFBS in AthaMap was now increased by about 3.8 × 10(7) to 4.9 × 10(7). The number of TFs with PWM-predicted TFBS annotated in AthaMap has increased to 126, representing a total of 29 TF families and newly including ARF, AT-Hook, YABBY, LOB/AS2 and SRS. Furthermore, links from all Arabidopsis TFs and genes to the newly established Arabidopsis Information Portal (AIP) have been implemented. With this qualitative and quantitative update, the improved AthaMap increases its value as a resource for the analysis of A. thaliana gene expression regulation at www.athamap.de.