An computational-biostatistical approach, supported by ab initio optimizations of auxin-like molecules, was used to find biologically meaningful relationships between quantum chemical variables and fresh bioassay's data. It is proven that the auxin-like recognition requires different molecular assembling states. We suggest that the carboxyl group is not the determining factor in explaining the biological auxin-like conduct. The biological effects depends essentially on the chemical condition of the ring system. The aim to find active molecules (quantum objects) via statistical grouping-analysis of molecular quantum similarity measures was verified by bioactivity assays. Next, this approach led to the discovery of a non-carboxylated active auxin-like molecule (2,6-dibromo-phenol). This is the first publication on structure activity relationship of auxin-like molecules, which relies on highly standardized bioassays of different auxins screened in parallel as well as analysed by multi-dimensional scaling.