Main Article Content
Abstract
Inhibition of Dipeptidyl Peptidase-4 (DPP-4) is an established therapeutic target for type II diabetes control, having potential for potentiating endogenously produced insulin by maintaining stability of incretin hormones. The current study extensively analyzes molecular modeling, pharmacokinetics, toxicity, and insulin secretory efficacy of Quercetin, Celecoxib, Doxycyline, Atorvastatine, Omeprazole, and Furosemide, a set of six different compounds, for DPP-4 inhibition, which is an established therapeutic target for diabetes control by potentiating endogenously secreted insulin by maintaining stability of incretin secretion. Using InstaDock v1.1 for molecular modeling, binding affinity, as well as Ligand Efficiency, of Quercetin, Celecoxib, Doxycyline, Atorvastatine, Omeprazole, and Furosemide have been calculated, of which Quercetin showed maximum binding affinity of -8.2 kcal/mol, respectively. The pharmacokinetics, target binding, as well as toxicity (LD50) of candidate compounds, have also been predicted using SwissADME, Swiss-TargetPrediction, respectively, in combination, ascertaining anti-toxicity (Gusar on Way2Drug). One-way ANOVA, further followed by t-tests, has also been used to check for significant differences between compounds to identify better treatments for augmenting functions of secreted hormones to stimulate pancreatic insulin secretion. The current scientific study is ethically justifiable for computational procedures, providing concrete scientific inputs for future studies in preparing optimized therapeutic agents for repurposed intervention in commonly prevalent metabolic.
Keywords
Article Details
Copyright (c) 2026 Rasha N. Aljabery

This work is licensed under a Creative Commons Attribution 4.0 International License.
References
- Mohammad T, Mathur Y, Hassan MI. InstaDock: A single-click graphical user interface for molecular docking-based virtual high-throughput screening. Brief Bioinform. 2020;22(4):1-8. doi: 10.1093/bib/bbaa279.
- Hassan NM, Alhossary AA, Mu Y, Kwoh CK. Protein-ligand blind docking using QuickVina-W with inter-process spatio-temporal integration. Sci Rep. 2017;7(1):1-13. doi: 10.1038/s41598-017-15571-7.
- Trott O, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2010;31(2):455-61. doi: 10.1002/jcc.21334.
- Shityakov S, Foerster C. In silico structure-based screening of versatile P-glycoprotein inhibitors using polynomial empirical scoring functions. Adv Appl Bioinform Chem. 2014;7:1-9. doi: 10.2147/aabc.s56046.
- Hopkins AL, Groom CR, Alex A. Ligand efficiency: a useful metric for lead selection. Drug Discov Today. 2004;9(10):430-1. doi: 10.1016/s1359-6446(04)03069-7.
- Gallwitz B. Dipeptidyl-peptidase-4 inhibitors in the management of type 2 diabetes: a critical review. Diabetes Care. 2013;36(Suppl 2):S203-9. doi: 10.2337/dc13-s203.
- Mulvihill EE, Drucker DJ. Pharmacology, physiology, and mechanisms of action of dipeptidyl peptidase-4 inhibitors. Endocr Rev. 2014;35(6):992-1019. doi: 10.1210/er.2014-1035.
- Lionta E, Spyrou G, Vassilatis DK, Cournia Z. Structure-based virtual screening for drug discovery: principles, applications and recent advances. Curr Top Med Chem. 2014;14(16):1923-38. doi: 10.2174/1568026614666140929124445.
- Ferreira LG, dos Santos RN, Oliva G, Andricopulo AD. Molecular docking and structure-based drug design strategies. Molecules. 2015;20(7):13384-421. doi: 10.3390/molecules200713384.
- Yuriev E, Ramsland PA. Latest developments in molecular docking: 2010-2011 in review. J Mol Recognit. 2013;26(5):215-39. doi: 10.1002/jmr.2266.
- Eid HM, Haddad PS. The antidiabetic potential of quercetin: underlying mechanisms. Curr Med Chem. 2017;24(4):355-64. doi: 10.2174/0929867323666160909153707.
- Sharma M, Gupta YK. Quercetin: A promising drug candidate for the treatment of type 2 diabetes mellitus. Eur J Pharmacol. 2019;862:172591. doi: 10.1016/j.ejphar.2019.172591.
- Paniagua-Pérez R, Madrigal-Bujaidar E, Reyes-Cadena S, et al. Celecoxib induces antidiabetic, antioxidant and anti-inflammatory effects in a rat model of type 2 diabetes. Life Sci. 2017;183:1-8. doi: 10.1016/j.lfs.2017.06.028.
- Solomon DH, Schneeweiss S, Glynn RJ, et al. Relationship between COX-2 specific inhibitors and diabetes risk. Diabetes Care. 2006;29(2):247-52. doi: 10.2337/dc05-1998.
- Sattar N, Preiss D, Murray HM, Welsh P, Buckley BM, de Craen AJ, et al. Statins and risk of incident diabetes: a collaborative meta-analysis of randomised statin trials. Lancet. 2010;375(9716):735-42. doi: 10.1016/s0140-6736(09)61965-6.
- Preiss D, Seshasai SR, Welsh P, et al. Risk of incident diabetes with statin therapy: meta-analysis of randomised controlled trials. BMJ. 2012;344:e494. doi: 10.1136/bmj.e494.
- Wang J, Chen L, Chen B, et al. Proton pump inhibitors and the risk of diabetes: a systematic review and meta-analysis. Diabetes Res Clin Pract. 2020;166:108297. doi: 10.4239/wjd.v14.i2.120.
- Filippatos TD, Elisaf MS. Effect of furosemide on glucose metabolism: a review. Diabetes Metab Syndr. 2018;12(6):1049-53. doi: 10.1016/j.dsx.2018.05.003.
- Kalra S, Gupta Y. Oral antidiabetic agents: current role in type 2 diabetes mellitus. Indian J Endocrinol Metab. 2017;21(4):546-51. doi: 10.4103/ijem.IJEM_202_17.
- Wu Y, Ding Y, Tanaka Y, Zhang W. Risk factors contributing to type 2 diabetes and recent advances in the treatment and prevention. Int J Med Sci. 2014;11(11):1185-200. doi: 10.7150/ijms.10001.
- Kim S, Chen J, Cheng T, Gindulyte A, He J, He S, et al. PubChem in 2021: new data content and improved web interfaces. Nucleic Acids Res. 2021;49(D1):D1388-95. doi: 10.1093/nar/gkaa971.
- Berman HM, Westbrook J, Feng Z, et al. The Protein Data Bank. Nucleic Acids Res. 2000;28(1):235-42. doi: 10.1093/nar/28.1.235.
- BIOVIA, Dassault Systèmes. Discovery Studio Modeling Environment, Release 2025. San Diego: Dassault Systèmes; 2024.
- Schrödinger LLC. The PyMOL Molecular Graphics System, Version 2.0. New York: Schrödinger; 2015.
- Daina A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep. 2017;7:42717. doi: 10.1038/srep42717.
- Daina A, Michielin O, Zoete V. SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules. Nucleic Acids Res. 2019;47(W1):W357-64. doi: 10.1093/nar/gkz382.
- Lagunin A, Stepanchikova A, Filimonov D, Poroikov V. PASS: prediction of activity spectra for biologically active substances. Bioinformatics. 2000;16(8):747-8. doi: 10.1093/bioinformatics/16.8.747.
- Duffy SJ, et al. The effect of DPP-4 inhibition on endothelial function and postprandial lipids in type 2 diabetes. J Clin Endocrinol Metab. 2013;98(4):1596-603. doi: 10.1210/jc.2012-3314.
- Drucker DJ. The biology of incretin hormones. Cell Metab. 2006;3(3):153-65. doi: 10.1016/j.cmet.2006.01.004.
- Thornberry NA, Gallwitz B. Mechanism of action of incretin-based therapies and DPP-4 inhibitors. Best Pract Res Clin Endocrinol Metab. 2009;23(4):479-86. doi: 10.1016/j.beem.2009.03.004.
- Mentlein R. Mechanisms underlying the rapid degradation and elimination of the incretin hormones GLP-1 and GIP. Best Pract Res Clin Endocrinol Metab. 2009;23(4):443-52. doi: 10.1016/j.beem.2009.03.005.
- Mulvihill EE, Drucker DJ. Dipeptidyl peptidase-4 inhibition and the gut microbiome: current concepts and future directions. Metabolism. 2019;96:23-32. doi: 10.1016/j.metabol.2019.01.013.
- Andres S, Pevny S, Ziegenhagen R, Bakhiya N, Schäfer B, Hirsch-Ernst KI, et al. Safety aspects of the use of quercetin as a dietary supplement. Mol Nutr Food Res. 2018;62(1):1700447. doi: 10.1002/mnfr.201700447.
- Boots AW, Haenen GR, Bast A. Health effects of quercetin: from antioxidant to nutraceutical. Eur J Pharmacol. 2008;585(2-3):325-37. doi: 10.1016/j.ejphar.2008.03.008.
- McTaggart F, Buckett L, Davidson R, et al. Atorvastatin: an overview. J Int Med Res. 1999;27(1):1-19. doi: 10.1177/030006059902700101.
- Corsini A, Bellosta S, Baetta R, Fumagalli R, Paoletti R, Bernini F. New insights into the pharmacodynamic and pharmacokinetic properties of statins. Pharmacol Ther. 1999;84(3):413-28. doi: 10.1016/s0163-7258(99)00045-5.
- Zocor and Lipitor: pharmacokinetic and pharmacodynamic comparison. JAMA. 2001;286(4):442-7. doi: 10.1001/jama.286.4.442.
- Solomon SD, McMurray JJ, Pfeffer MA, Wittes J, Fowler R, Finn P, et al. Cardiovascular risk associated with celecoxib in a clinical trial for colorectal adenoma prevention. N Engl J Med. 2005;352(11):1071-80. doi: 10.1056/nejmoa050405.
- Nissen SE, Yeomans ND, Solomon DH, Lüscher TF, Libby P, Husni ME, et al. Cardiovascular safety of celecoxib, naproxen, or ibuprofen for arthritis. N Engl J Med. 2016;375(26):2519-29. doi: 10.1056/nejmoa1611593.
- Schachter M. Chemical, pharmacokinetic and pharmacodynamic properties of statins: an update. Fundam Clin Pharmacol. 2005;19(1):117-25. doi: 10.1111/j.1472-8206.2004.00299.x
- Agwuh KN, MacGowan A. Pharmacokinetics and pharmacodynamics of the tetracyclines including glycylcyclines. J Antimicrob Chemother. 2006;58(2):256-65. doi: 10.1093/jac/dkl224.
- Andersson T, Weidolf L. Stereoselective disposition of omeprazole in humans. Clin Pharmacokinet. 2001;40(7):455-66. doi: 10.2165/00003088-200140060-00003.
- Brater DC. Diuretic therapy. N Engl J Med. 1998;339(6):387-95. doi: 10.1056/nejm199808063390607
- Bule M, Abdurahman A, Nikfar S, Abdollahi M, Amini M. A systematic review and meta-analysis of the effect of quercetin supplementation on plasma lipid profiles, blood pressure and glucose levels. Food Chem Toxicol. 2019;125:494-502. doi: 10.1016/j.fct.2019.01.037.
- Dabeek WM, Marra MV. Dietary quercetin and kaempferol: bioavailability and potential cardiovascular-related bioactivity in humans. Nutrients. 2019;11(10):2288. doi: 10.3390/nu11102288.
- Rivera L, Morón R, Sánchez M, Zarzuelo A, Galisteo M. Quercetin ameliorates metabolic syndrome and improves the inflammatory status in obese Zucker rats. Obesity. 2008;16(9):2081-7. doi: 10.1038/oby.2008.315.
- Stefani M, et al. Role of natural compounds in the modulation of DPP-4 activity: potential implications for the treatment of type 2 diabetes. J Enzyme Inhib Med Chem. 2018;33(1):839-53. doi: 10.1080/14756366.2018.1458915.
- Goldstein BJ, Feinglos MN, Lunceford JK, Johnson J, Williams-Herman DE. Effect of initial combination therapy with sitagliptin, a dipeptidyl peptidase-4 inhibitor, and metformin on glycemic control in patients with type 2 diabetes. Diabetes Care. 2007;30(8):1979-87. doi: 10.2337/dc07-0627.
- Green BD, Flatt PR, Bailey CJ. Dipeptidyl peptidase IV (DPP IV) inhibitors: a newly emerging drug class for the treatment of type 2 diabetes. Diabetes Vasc Dis Res. 2006;3(3):159-65. doi: 10.3132/dvdr.2006.024.
- Deacon CF. Physiology and pharmacology of DPP-4 in glucose homeostasis and the treatment of type 2 diabetes. Front Endocrinol. 2019;10:80. doi: 10.3389/fendo.2019.00080.
- Aroda VR, Henry RR, Han J, Huang W, DeYoung MB, Darsow T, et al. Efficacy of GLP-1 receptor agonists and DPP-4 inhibitors in type 2 diabetes. Endocr Pract. 2012;18(6):738-48. doi: 10.1016/j.clinthera.2012.04.013.
References
Mohammad T, Mathur Y, Hassan MI. InstaDock: A single-click graphical user interface for molecular docking-based virtual high-throughput screening. Brief Bioinform. 2020;22(4):1-8. doi: 10.1093/bib/bbaa279.
Hassan NM, Alhossary AA, Mu Y, Kwoh CK. Protein-ligand blind docking using QuickVina-W with inter-process spatio-temporal integration. Sci Rep. 2017;7(1):1-13. doi: 10.1038/s41598-017-15571-7.
Trott O, Olson AJ. AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2010;31(2):455-61. doi: 10.1002/jcc.21334.
Shityakov S, Foerster C. In silico structure-based screening of versatile P-glycoprotein inhibitors using polynomial empirical scoring functions. Adv Appl Bioinform Chem. 2014;7:1-9. doi: 10.2147/aabc.s56046.
Hopkins AL, Groom CR, Alex A. Ligand efficiency: a useful metric for lead selection. Drug Discov Today. 2004;9(10):430-1. doi: 10.1016/s1359-6446(04)03069-7.
Gallwitz B. Dipeptidyl-peptidase-4 inhibitors in the management of type 2 diabetes: a critical review. Diabetes Care. 2013;36(Suppl 2):S203-9. doi: 10.2337/dc13-s203.
Mulvihill EE, Drucker DJ. Pharmacology, physiology, and mechanisms of action of dipeptidyl peptidase-4 inhibitors. Endocr Rev. 2014;35(6):992-1019. doi: 10.1210/er.2014-1035.
Lionta E, Spyrou G, Vassilatis DK, Cournia Z. Structure-based virtual screening for drug discovery: principles, applications and recent advances. Curr Top Med Chem. 2014;14(16):1923-38. doi: 10.2174/1568026614666140929124445.
Ferreira LG, dos Santos RN, Oliva G, Andricopulo AD. Molecular docking and structure-based drug design strategies. Molecules. 2015;20(7):13384-421. doi: 10.3390/molecules200713384.
Yuriev E, Ramsland PA. Latest developments in molecular docking: 2010-2011 in review. J Mol Recognit. 2013;26(5):215-39. doi: 10.1002/jmr.2266.
Eid HM, Haddad PS. The antidiabetic potential of quercetin: underlying mechanisms. Curr Med Chem. 2017;24(4):355-64. doi: 10.2174/0929867323666160909153707.
Sharma M, Gupta YK. Quercetin: A promising drug candidate for the treatment of type 2 diabetes mellitus. Eur J Pharmacol. 2019;862:172591. doi: 10.1016/j.ejphar.2019.172591.
Paniagua-Pérez R, Madrigal-Bujaidar E, Reyes-Cadena S, et al. Celecoxib induces antidiabetic, antioxidant and anti-inflammatory effects in a rat model of type 2 diabetes. Life Sci. 2017;183:1-8. doi: 10.1016/j.lfs.2017.06.028.
Solomon DH, Schneeweiss S, Glynn RJ, et al. Relationship between COX-2 specific inhibitors and diabetes risk. Diabetes Care. 2006;29(2):247-52. doi: 10.2337/dc05-1998.
Sattar N, Preiss D, Murray HM, Welsh P, Buckley BM, de Craen AJ, et al. Statins and risk of incident diabetes: a collaborative meta-analysis of randomised statin trials. Lancet. 2010;375(9716):735-42. doi: 10.1016/s0140-6736(09)61965-6.
Preiss D, Seshasai SR, Welsh P, et al. Risk of incident diabetes with statin therapy: meta-analysis of randomised controlled trials. BMJ. 2012;344:e494. doi: 10.1136/bmj.e494.
Wang J, Chen L, Chen B, et al. Proton pump inhibitors and the risk of diabetes: a systematic review and meta-analysis. Diabetes Res Clin Pract. 2020;166:108297. doi: 10.4239/wjd.v14.i2.120.
Filippatos TD, Elisaf MS. Effect of furosemide on glucose metabolism: a review. Diabetes Metab Syndr. 2018;12(6):1049-53. doi: 10.1016/j.dsx.2018.05.003.
Kalra S, Gupta Y. Oral antidiabetic agents: current role in type 2 diabetes mellitus. Indian J Endocrinol Metab. 2017;21(4):546-51. doi: 10.4103/ijem.IJEM_202_17.
Wu Y, Ding Y, Tanaka Y, Zhang W. Risk factors contributing to type 2 diabetes and recent advances in the treatment and prevention. Int J Med Sci. 2014;11(11):1185-200. doi: 10.7150/ijms.10001.
Kim S, Chen J, Cheng T, Gindulyte A, He J, He S, et al. PubChem in 2021: new data content and improved web interfaces. Nucleic Acids Res. 2021;49(D1):D1388-95. doi: 10.1093/nar/gkaa971.
Berman HM, Westbrook J, Feng Z, et al. The Protein Data Bank. Nucleic Acids Res. 2000;28(1):235-42. doi: 10.1093/nar/28.1.235.
BIOVIA, Dassault Systèmes. Discovery Studio Modeling Environment, Release 2025. San Diego: Dassault Systèmes; 2024.
Schrödinger LLC. The PyMOL Molecular Graphics System, Version 2.0. New York: Schrödinger; 2015.
Daina A, Michielin O, Zoete V. SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci Rep. 2017;7:42717. doi: 10.1038/srep42717.
Daina A, Michielin O, Zoete V. SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules. Nucleic Acids Res. 2019;47(W1):W357-64. doi: 10.1093/nar/gkz382.
Lagunin A, Stepanchikova A, Filimonov D, Poroikov V. PASS: prediction of activity spectra for biologically active substances. Bioinformatics. 2000;16(8):747-8. doi: 10.1093/bioinformatics/16.8.747.
Duffy SJ, et al. The effect of DPP-4 inhibition on endothelial function and postprandial lipids in type 2 diabetes. J Clin Endocrinol Metab. 2013;98(4):1596-603. doi: 10.1210/jc.2012-3314.
Drucker DJ. The biology of incretin hormones. Cell Metab. 2006;3(3):153-65. doi: 10.1016/j.cmet.2006.01.004.
Thornberry NA, Gallwitz B. Mechanism of action of incretin-based therapies and DPP-4 inhibitors. Best Pract Res Clin Endocrinol Metab. 2009;23(4):479-86. doi: 10.1016/j.beem.2009.03.004.
Mentlein R. Mechanisms underlying the rapid degradation and elimination of the incretin hormones GLP-1 and GIP. Best Pract Res Clin Endocrinol Metab. 2009;23(4):443-52. doi: 10.1016/j.beem.2009.03.005.
Mulvihill EE, Drucker DJ. Dipeptidyl peptidase-4 inhibition and the gut microbiome: current concepts and future directions. Metabolism. 2019;96:23-32. doi: 10.1016/j.metabol.2019.01.013.
Andres S, Pevny S, Ziegenhagen R, Bakhiya N, Schäfer B, Hirsch-Ernst KI, et al. Safety aspects of the use of quercetin as a dietary supplement. Mol Nutr Food Res. 2018;62(1):1700447. doi: 10.1002/mnfr.201700447.
Boots AW, Haenen GR, Bast A. Health effects of quercetin: from antioxidant to nutraceutical. Eur J Pharmacol. 2008;585(2-3):325-37. doi: 10.1016/j.ejphar.2008.03.008.
McTaggart F, Buckett L, Davidson R, et al. Atorvastatin: an overview. J Int Med Res. 1999;27(1):1-19. doi: 10.1177/030006059902700101.
Corsini A, Bellosta S, Baetta R, Fumagalli R, Paoletti R, Bernini F. New insights into the pharmacodynamic and pharmacokinetic properties of statins. Pharmacol Ther. 1999;84(3):413-28. doi: 10.1016/s0163-7258(99)00045-5.
Zocor and Lipitor: pharmacokinetic and pharmacodynamic comparison. JAMA. 2001;286(4):442-7. doi: 10.1001/jama.286.4.442.
Solomon SD, McMurray JJ, Pfeffer MA, Wittes J, Fowler R, Finn P, et al. Cardiovascular risk associated with celecoxib in a clinical trial for colorectal adenoma prevention. N Engl J Med. 2005;352(11):1071-80. doi: 10.1056/nejmoa050405.
Nissen SE, Yeomans ND, Solomon DH, Lüscher TF, Libby P, Husni ME, et al. Cardiovascular safety of celecoxib, naproxen, or ibuprofen for arthritis. N Engl J Med. 2016;375(26):2519-29. doi: 10.1056/nejmoa1611593.
Schachter M. Chemical, pharmacokinetic and pharmacodynamic properties of statins: an update. Fundam Clin Pharmacol. 2005;19(1):117-25. doi: 10.1111/j.1472-8206.2004.00299.x
Agwuh KN, MacGowan A. Pharmacokinetics and pharmacodynamics of the tetracyclines including glycylcyclines. J Antimicrob Chemother. 2006;58(2):256-65. doi: 10.1093/jac/dkl224.
Andersson T, Weidolf L. Stereoselective disposition of omeprazole in humans. Clin Pharmacokinet. 2001;40(7):455-66. doi: 10.2165/00003088-200140060-00003.
Brater DC. Diuretic therapy. N Engl J Med. 1998;339(6):387-95. doi: 10.1056/nejm199808063390607
Bule M, Abdurahman A, Nikfar S, Abdollahi M, Amini M. A systematic review and meta-analysis of the effect of quercetin supplementation on plasma lipid profiles, blood pressure and glucose levels. Food Chem Toxicol. 2019;125:494-502. doi: 10.1016/j.fct.2019.01.037.
Dabeek WM, Marra MV. Dietary quercetin and kaempferol: bioavailability and potential cardiovascular-related bioactivity in humans. Nutrients. 2019;11(10):2288. doi: 10.3390/nu11102288.
Rivera L, Morón R, Sánchez M, Zarzuelo A, Galisteo M. Quercetin ameliorates metabolic syndrome and improves the inflammatory status in obese Zucker rats. Obesity. 2008;16(9):2081-7. doi: 10.1038/oby.2008.315.
Stefani M, et al. Role of natural compounds in the modulation of DPP-4 activity: potential implications for the treatment of type 2 diabetes. J Enzyme Inhib Med Chem. 2018;33(1):839-53. doi: 10.1080/14756366.2018.1458915.
Goldstein BJ, Feinglos MN, Lunceford JK, Johnson J, Williams-Herman DE. Effect of initial combination therapy with sitagliptin, a dipeptidyl peptidase-4 inhibitor, and metformin on glycemic control in patients with type 2 diabetes. Diabetes Care. 2007;30(8):1979-87. doi: 10.2337/dc07-0627.
Green BD, Flatt PR, Bailey CJ. Dipeptidyl peptidase IV (DPP IV) inhibitors: a newly emerging drug class for the treatment of type 2 diabetes. Diabetes Vasc Dis Res. 2006;3(3):159-65. doi: 10.3132/dvdr.2006.024.
Deacon CF. Physiology and pharmacology of DPP-4 in glucose homeostasis and the treatment of type 2 diabetes. Front Endocrinol. 2019;10:80. doi: 10.3389/fendo.2019.00080.
Aroda VR, Henry RR, Han J, Huang W, DeYoung MB, Darsow T, et al. Efficacy of GLP-1 receptor agonists and DPP-4 inhibitors in type 2 diabetes. Endocr Pract. 2012;18(6):738-48. doi: 10.1016/j.clinthera.2012.04.013.
