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

Author:

Olasupo Sabitu Babatunde,Uzairu Adamu,Shallangwa Gideon,Uba Sani

Abstract

AbstractChemometrics 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.

Publisher

Springer Science and Business Media LLC

Subject

General Chemistry

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