The collection, description and molecular analysis of naturally occurring (pathogenic) mutations are important for understanding the functional mechanisms and malfunctions of biological units such as proteins. Numerous databases collate a huge amount of functional data or descriptions of mutations, but tools to analyse the molecular effects of genetic variations are as yet poorly provided. The goal of this work was therefore to develop a translational web-application that facilitates the interactive linkage of functional and structural data and which helps improve our understanding of the molecular basis of naturally occurring gain- or loss- of function mutations. Here we focus on the human glycoprotein hormone receptors (GPHRs), for which a huge number of mutations are known to cause diseases. We describe new options for interactive data analyses within three-dimensional structures, which enable the assignment of molecular relationships between structure and function. Strikingly, as the functional data are converted into relational percentage values, the system allows the comparison and classification of data from different GPHR subtypes and different experimental approaches. Our new application has been incorporated into a freely available database and website for the GPHRs (http://www.ssfa-gphr.de), but the principle development would also be applicable to other macromolecules.