S. B. Olasupo, A. Uzairu, G. S. Adamu, and S. Uba, “Computational Modeling and Pharmacokinetics/ADMET Study of Some Arylpiperazine Derivatives as Novel Antipsychotic Agents Targeting Depression,” Chem. Africa., 3 (2020) 1–10.
 N. Dessalew, “QSAR study on dual SET and NET reuptake inhibitors: an insight into the structural requirement for antidepressant activity,” J. Enzyme Inhib. Med. Chem.., 24 (2009) 262–271.
 S. B. Olasupo, A. Uzairu, G. A. Shallangwa, and S. Uba, “Profiling the antidepressant properties of Phenyl piperidine derivatives as inhibitors of serotonin transporter (SERT) via Cheminformatics Modeling, Molecular docking and ADMET predictions.,” Sci. African., 9 (2020) p. e00517.
 M. Gabrielsen, A. W. Ravna, K. Kristiansen, and I. Sylte, “Substrate binding and translocation of the serotonin transporter studied by docking and molecular dynamics simulations,” J. Mol. Model., 18 (2012) 1073–1085.
 I. C. Muszynski, L. Scapozza, K. Kovar, and G. Folkers, “Quantitative structure‐activity relationships of phenyltropanes as inhibitors of three monoamine transporters: Classical and CoMFA studies,” Quant. Struct. Relationships., 18 (1999) 342–353.
 S. Bhat, A. H. Newman, and M. Freissmuth, “How to rescue misfolded SERT, DAT and NET: targeting conformational intermediates with atypical inhibitors and partial releasers,” Biochem. Soc. Trans., 47 (2019) 861–874.
 Y. Yang et al., “Computational analysis of structure-based interactions for novel H1-antihistamines,” Int. J. Mol. Sci., 17 (2016) 129.
 J. Wang et al., “Profiling the interaction mechanism of indole-based derivatives targeting the HIV-1 gp120 receptor,” RSC Adv., 5 (2015) 78278–78298.
 S. B. Olasupo, A. Uzairu, G. Shallangwa, and S. Uba, “QSAR analysis and molecular docking simulation of norepinephrine transporter (NET) inhibitors as anti-psychotic therapeutic agents,” Heliyon., 5 (2019) e02640.
 A. Penmatsa, K. H. Wang, and E. Gouaux, “X-ray structure of dopamine transporter elucidates antidepressant mechanism,” Nature., 503 (2013) 85.
 P. T. Mpiana et al., “Identification of potential inhibitors of SARS-CoV-2 main protease from Aloe vera compounds: a molecular docking study,” Chem. Phys. Lett., 754 (2020) 137751
 S. S. ul Hassan, W.-D. Zhang, H. Jin, S. H. Basha, and S. V. S. S. Priya, “In-silico anti-inflammatory potential of guaiane dimers from Xylopia vielana targeting COX-2,” J. Biomol. Struct. Dyn., 1 (2020) 1–15.
 A. Daina, O. Michielin, and V. Zoete, “SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules,” Sci. Rep., 7 (2017) 42717.
 D. E. V Pires, T. L. Blundell, and D. B. Ascher, “pkCSM: predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures,” J. Med. Chem., 58 (2015) 4066–4072.
 M. Cheminformatics, “Calculation of molecular properties and bioactivity score,” Comput. software]. Retrieved from http//www. molinspiration. com/cgi-bin/properties, (2018).
 F. Cheng et al., “Correction to ‘admetSAR: A Comprehensive Source and Free Tool for Assessment of Chemical ADMET Properties,’” J. Chem. Inf. Model., 59 (2019) 4959.
 C. A. Lipinski, “Rule of five in 2015 and beyond: Target and ligand structural limitations, ligand chemistry structure and drug discovery project decisions,” Adv. Drug Deliv. Rev., 101 (2016) 34–41.
 S. B. Olasupo, A. Uzairu, G. A. Shallangwa, and S. Uba, “Chemoinformatic studies on some inhibitors of dopamine transporter and the receptor targeting schizophrenia for developing novel antipsychotic agents,” Heliyon, 6 (2020) e04464.
 N. Brooijmans, “Docking methods, ligand design, and validating data sets in the structural genomic era,” Struct. Bioinformatics. JGaPE Bourne, Ed. John Wiley Sons, ( 2009)
 S. Roy, L. R. Samant, and A. Chowdhary, “In silico pharmacokinetics analysis and ADMET of phytochemicals of Datura metel Linn. and Cynodon dactylon Linn,” J. Chem. Pharm. Res., 7 (2015) 385–388.
 A. Daina and V. Zoete, “A boiled‐egg to predict gastrointestinal absorption and brain penetration of small molecules,” ChemMedChem., 11 (2016) 1117–1121.
 S. Babatunde, O. Adamu, U. Gideon, and S. Sani, “QSAR modeling , molecular docking and ADMET / pharmacokinetic studies : a chemometrics approach to search for novel inhibitors of norepinephrine transporter as potent antipsychotic drugs,” J. Iran. Chem. Soc., 17 (2020) 1953–1966.
 S. E. Adeniji, D. E. Arthur, M. Abdullahi, and A. Haruna, “Quantitative structure–activity relationship model, molecular docking simulation and computational design of some novel compounds against DNA gyrase receptor,” Chem. Africa, 3 (2020) 391–408.