2.8. Data acquisition and statistical analysis
The data and statistical analysis in this study comply with the recommendations on experimental design and analysis in pharmacology (Curtis et al., 2018). Data from biochemical analyses were normalized with 100% defined as the mean of the technical replicates in the control group. During behavioural analysis, researchers were not aware of the drug that each animal had received. Competition curves were plotted and fitted by nonlinear regression. Data were best fitted to a sigmoidal dose-response curve and an IC50 or EC50value was obtained. Transporter ratios were calculated as (1/DAT IC50 : 1/SERT IC50), with higher values indicating greater selectivity for DAT. Ki(affinity) values were calculated using the Cheng-Prusoff equation:Ki = IC50/(1+[radioligand concentration/Kd]). One-way ANOVA, and subsequent post hoc test (Tukey-Kramer) which was conducted only if F was significant, was used to determine overall α-aminovalerophenone derivatives effects on HLA, CPP as well as DA and 5-HT uptake in both rat synaptosomes and HEK cells. The α error probability was set at 0.05 (p<0.05). The exact group size for the individual experiments is shown in the corresponding figure legends. Pearson correlation analyses were also performed when needed. All analysis were carried out using GraphPad Prism (GraphPad software, San Diego, CA, USA). Molecular and physicochemical descriptors were calculated for the different amino-terminal group using ChemBioOffice Ultra and Data Warrior software. Lipophilicity descriptors included calculated partition coefficient (CLogP). Molecular surface and steric bulk were also investigated using Total Surface Area (TSA) and calculated molar refractivity (CMR), respectively (Hevener et al., 2008).