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).