• Zvetanka Zhivkova Faculty of Pharmacy, Medical University, Sofia, Bulgaria




QSPkR, Clearance, Unbound clearance, In silico modelling, Prediction of ADME


Objective: Prediction of pharmacokinetic behaviour of new candidate drugs is an important step in drug design. Clearance is a key pharmacokinetic parameter, controlling drug exposure in the body. It depends on numerous factors and is frequently restricted by plasma protein binding. The study is focused on the development of quantitative structure-pharmacokinetic relationship (QSPkR) for the unbound clearance (CLu) of neutral drugs.

Methods: The dataset consisted of 117 neutral drugs, divided into training set (n = 94) and external test set (n = 23). Chemical structures were encoded by 113 theoretical descriptors. Genetic algorithm and step-wise multiple linear regression were applied for model development. The model was evaluated by cross-validation in the training set and external test set.

Results: Significant, predictive and interpretable QSPkR model was developed with explained variance r2 = 0.617, cross-validated correlation coefficient q2LOO-CV = 0.554, external test set predictive coefficient r2pred = 0.656, and root mean square error in prediction RMSEP = 1.89. The model was able to predict CLu for 56% of the drugs in the external test set within the 2-fold error of experimental values.

Conclusion: The model reveals the main molecular features governing CLu of neutral drugs. CLu is favoured by lipophilicity, the presence of fused aromatic rings, ester groups, dihydropyridine moieties and nine-member ring systems, while polarity, molecular size and strong electron withdrawing atoms and groups as substituents in aromatic rings affect negatively CL


Download data is not yet available.


Rowland M, Tozer TN. Elimination. In: Clinical Pharmaco-kinetics: concepts and application. 3rd ed. Baltimore, Philadelphia, USA: Williams and Wilkins; 1995. p. 156-84.

Zhivkova Z. Application of QSPkR for prediction of key pharmacokinetic parameters. Lambert Academic Publishing; 2017.

Turner JV, Maddalena DJ, Cutler DJ. Pharmacokinetic parameter prediction from drug structure using artificial neural networks. Int J Pharm 2004;270:209-19.

Ng C, Xiao Y, Putnam W, Lum B, Tropsha A. Quantitative structure-pharmacokinetic parameters relationships (QSPkR) analysis of antimicrobial agents in human using simulated annealing k-nearest neighbor and partial least square analysis methods. J Pharm Sci 2004;93:2535-44.

Yap CW, Li ZR, Chen YZ. Quantitative structure-pharmacokinetic relationships for drug clearance by using statistical learning methods. J Mol Graph Model 2006;24:383-95.

Yu MJ. Predicting total clearance in humans from chemical structure. J Chem Inf Model 2010;50:1284-95.

Berellini G, Waters NJ, Lombardo F. In silico prediction of total human plasma clearance. J Chem Inf Model 2012;52:2069-78.

Gombar VK, Hall SD. Quantitative structure-activity relationship models of clinical pharmacokinetics: clearance and volume of distribution. J Chem Inf Model 2013;53:948-57.

Paine WS, Barton P, Bird J, Denton R, Menochet K, Smith A, et al. A rapid computational filter for predicting the rate of human renal clearance. J Mol Graph Model 2010;29:529-37.

Lombardo F, Obach RS, Varma MV, Stringer R, Berellini G. Clearance mechanism assignment and total clearance prediction in human based upon in silico models. J Med Chem 2014;57:4392-405.

Manga NDJ, Duffy JC, Rowe PH, Cronin MTD. A hierarchical QSAR model for urinary excretion of drugs in humans as a predictive tool for biotransformation. QSAR Comb Sci 2003;22:263-73.

Doddareddy MR, Cho YS, Koh HY, Kim DH, Pae AN. In silico renal clearance model using classical volsurf approach. J Chem Inf Model 2006;46:1312-20.

Kusama M, Toshimoto K, Maeda K, Hirai Y, Imai S, Chiba K, et al. In silico classification of major clearance pathways of drugs with their physicochemical parameters. Drug Metab Dispos 2010;38:1362-70.

Pelis RM, Wright SH. Renal transport of organic anions and cations. Compr Physiol 2011;1:1795-835.

Smith DA, Allerton C, Kalgutkar A, Van de Waterbeemd H, Walker DK. Renal clearance. In: Pharmacokinetics and metabolism in drug design. 3rded. Weinheim, Germany: Wiley–VCH Verlag GmbH and Co. KGaA; 2012. p. 103-10.

Wu CY, Benet LZ. Predicting drug disposition via application of BCS: transport/absorption/elimination interplay and development of a biopharmaceutics drug disposition classification system. Pharm Res 2005;22:11-23.

Zhivkova Z, Doytchinova I. Quantitative structure–clearance relationships of acidic drugs. Mol Pharmacol 2013;10:3758-68.

Zhivkova Z, Doytchinova I. Quantitative structure-pharmacokinetic relationships for plasma clearance of basic drugs with consideration of the major elimination pathway. J Pharm Pharm Sci 2017;20:135-47.

Obach RS, Lombardo F, Waters NJ. Trend analysis of a database of intravenous pharmacokinetic parameters in humans for 670 drug compounds. Drug Metab Dispos 2008;36:1385-405.

http://www.drugbank.ca. [Last accessed on 20 Nov 2017]

http://chemicalbook.com. [Last accessed on 20 Nov 2017]

http://www.ebi.ac.uk. [Last accessed on 20 Nov 2017]

Roy K, Kar S, Das RN. Statistical methods in QSAR/QSPR. In: Roy K, Kar S, Das RN, editors. A primer on QSAR/QSPR modelling. Fundamental concepts. Heidelberg, New York, Dordrechs, London: Springer Cham; 2015. p. 37-59.

Alexander DLJ, Tropsha A, Winkler DA. Beware of R2: Simple, unambiguous assessment of the prediction accuracy of QSAR and QSPR models. J Chem Inf Model 2015;55:1316-22.

Zhivkova Z. Quantitative structure–pharmacokinetics relationships for plasma protein binding of basic drugs. J Pharm Pharm Sci 2017;20:349-59.

Zhivkova Z. Quantitative structure–pharmacokinetics relationship for plasma protein binding of neutral drugs, submitted for publication. J Pharm Pharm Sci 2017;20:349-59.

Hein KL, Kragh Hansen U, Morth JP, Jeppesen MD, Otzen D, Moeller JV, et al. Crystallographic analysis reveals a unique lidocaine binding site on human serum albumin. J Struct Biol 2010;171:353-60.

Nishi K, Ono T, Nakamura T, Fukunaga N, Izumi M, Watanabe H, et al. Structural insights into differences in drug-binding selectivity between two forms of human alpha1-acid glycoprotein genetic variants, the A and F1*S forms. J Biol Chem 2011;286:14427-34.

Al-Omarm MA. Nimodipine: drug metabolism and pharmacokinetic profile. Profiles of drug substances. Excipients Related Methodol 2005;31:371-5.

Smith DA, Allerton C, Kalgutkar A, Van de Waterbeemd H, Walker DK. Predicting human pharmacokinetics. In: Pharmacokinetics and metabolism in drug design. 3rd ed. Weinheim, Germany: Wiley–VCH Verlag GmbH and Co. KGaA; 2012. p. 209-27.

Kerns EH, Di L. Drug-like properties: concepts, structure design and methods. 2nd Ed. Elsevier: Amsterdam, Boston, Heidelberg, etc; 2016. p. 161-97.

Boehm HJ, Banner D, Bendels S, Kansy M, Kuhn B, Mueller K, et al. Fluorine in medicinal chemistry. Chem Bio Chem 2004;5:637-43.

Nassar AEF, Kamel AM, Clarimont C. Improving the decision-making process in the structural modification of drug candidates: enhancing metabolic stability. DDT 2004;9:1020-8.

www.drugs.com/monograph/clevidipine-butyrate.html. [Last accessed on 20 Nov 2017]

Zhang D, Krishna R, Wang L, Zeng J, Mitroka J, Dai R, et al. Metabolism, pharmacokinetics, and protein covalent binding of radiolabeled MaxiPost (BMS-204352) in humans. Drug Metab Dispos 2005;33:83-93.

Hiraoka H, Yamamoto K, Miyoshi S, Morita T, Nakamura K, Kadoi Y, et al. Kidneys contribute to the extrahepatic clearance of propofol in humans, but not lungs and brain. Br J Clin Pharmacol 2005;60:176–82.

Favetta P, Degoute CS, Perdrix JP, Dufresne C, Boulieu R, Guitton J. Propofol metabolites in man following propofol induction and maintenance. Br J Anaesth 2002;88:653-8.

Tsuchiya Y, Nakajima M, Yokoi T. Cytochrome P450-mediated metabolism of estrogens and its regulation in human. Cancer Lett 2005;227:115-24.

Derissen EJB, Beijnen JH, Schellens JHM. Concise drug review: azacitadineand decitabine. Oncologist 2013;18:619-24.

American Society of Health-System Pharmacists; AHFS Drug Information. Bethesda MD; 2009.



How to Cite

Zhivkova, Z. “QUANTITATIVE STRUCTURE–PHARMACOKINETICS MODELING OF THE UNBOUND CLEARANCE FOR NEUTRAL DRUGS”. International Journal of Current Pharmaceutical Research, vol. 10, no. 2, Mar. 2018, pp. 56-59, doi:10.22159/ijcpr.2018v10i2.25849.



Original Article(s)