Discussion with Barbara M. Bakker (University Medical Center Groningen), Carsten Kettner, Thomas S. Leyh (Albert Einstein College of Medicine), Johann M. Rohwer (University of Stellenbosch) and Reinhard Sterner (University of Regensburg) recorded at BEILSTEIN ENZYMOLOGY SYMPOSIUM – Enzymes in Transformation and Signalling Rüdesheim, Germany, 19 – 21 September 2017 At the end of the Beilstein Enzymology Symposium, Carsten Kettner discusses with Barbara Bakker, Thomas Leyh, Johann Rohwer and Reinhard Sterner about the pitfalls when reusing enzyme function data from the literature and databases. Listen to the views on the following themes: Which information is required to reproduce experiments and reuse experimental data in simulation and modelling? What are the reasons for missing information in papers and what is the role of the journals with regards to quality control? Are reporting guidelines and software tools beneficial for the science community? How burdensome is data input in STRENDA DB considered in comparison to other data acquisition systems? The panel, each an expert from a different area in enzymology, gave some interesting insights into their experiences with published experimental data and provided a number of ideas on how to increase reproducibility, comparability and reliability of these data. The Beilstein Enzymology Symposia embrace structural, computational and biological disciplines, and bring researchers (established and younger workers) together to discuss the many and diverse roles of enzymes in biology, and to explore the limits and challenges of holistic studies that attempt to integrate microscopic views of protein function into complex biological behaviour. This symposium addresses enzymes and other signal‑cascade proteins which capture and transduce these diverse signals into discrete chemical entities that inform and direct cellular behaviour. Molecular-information processing networks require the coordinated interplay of numerous components, and are the focus of systems-biological investigations aimed at understanding, for example, the spread of disease, or identifying targets that can control signal-transduction.