qsar modeling, molecular docking and admet/pharmacokinetic studies: a chemometrics approach to search for novel inhibitors of norepinephrine transporter as potent antipsychotic drugs

Chemometrics study that relates biological activity to physicochemical descriptors of a molecule and the prediction of absorption, distribution, metabolism, excretion and toxicity (admet) properties in advance are important steps in drugs discovery. in this study, a chemometrics approach was employed on some molecules (inhibitors) of norepinephrine transporter to assess their inhibitory potencies, interactions with the receptor and predict their admet/pharmacokinetic properties for identification of novel antipsychotic drugs. the molecules were optimized by using density functional theory at the basis set of b3lyp/6-31g*. the genetic function algorithm technique was used to generate a statistically significant model with a good correlation coefficient r2train = 0.952 cross-validated coefficient q2cv = 0.870, and adjusted squared correlation coefficient r2adj = 0.898. the molecular docking simulation using a neurotransmitter transporter receptor (pdb code 2a65) revealed that three inhibitors (molecule no 38, 44 and 12) exhibited the highest binding affinity of − 10.3, − 9.9 and − 9.3 kcal/mol, respectively, were observed to inhibit the target by forming strong hydrogen bonds with hydrophobic interactions. the physicochemical and admet/pharmacokinetic properties result showed that these three molecules are orally bioavailable, high gastrointestinal absorption, good permeability and non-inhibitors of cyp3a4 and cyp2d6 except for molecule no 38. also, molecules no 38 and 44 proved to be non-substrate of p-glycoprotein and nontoxicity to a human ether-a-go-go-related gene with predicted herg toxicity endpoints (pic50 < 6) and low admet_risk (< 7.0). the results of this study would provide physicochemical and pharmacokinetics properties needed to identify potent antipsychotic drugs and other relevant information in drug discovery.