Quantitative structure/property relationship analysis of Caco‐2 permeability using a genetic algorithm‐based partial least squares method
Caco‐2 cell monolayers are widely used systems for predicting human intestinal absorption. This study was carried out to develop a quantitative structure–property relationship (QSPR) model of Caco‐2 permeability using a novel genetic algorithm‐based partial least squares (GA‐PLS) method. The Caco‐2...
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| Published in | Journal of pharmaceutical sciences Vol. 91; no. 10; pp. 2230 - 2239 |
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| Main Authors | , , |
| Format | Journal Article |
| Language | English |
| Published |
New York
Elsevier Inc
01.10.2002
Wiley Subscription Services, Inc., A Wiley Company Wiley American Pharmaceutical Association |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0022-3549 1520-6017 |
| DOI | 10.1002/jps.10214 |
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| Abstract | Caco‐2 cell monolayers are widely used systems for predicting human intestinal absorption. This study was carried out to develop a quantitative structure–property relationship (QSPR) model of Caco‐2 permeability using a novel genetic algorithm‐based partial least squares (GA‐PLS) method. The Caco‐2 permeability data for 73 compounds were taken from the literature. Molconn‐Z descriptors of these compounds were calculated as molecular descriptors, and the optimal subset of the descriptors was explored by GA‐PLS analysis. A fitness function considering both goodness‐of‐fit to the training data and predictability of the testing data was adopted throughout the genetic algorithm‐driven optimization procedure. The final PLS model consisting of 24 descriptors gave a correlation coefficient (r) of 0.886 for the entire dataset and a predictive correlation coefficient (rpred) of 0.825 that was evaluated by a leave‐some‐out cross‐validation procedure. Thus, the GA‐PLS analysis proved to be a reasonable QSPR modeling approach for predicting Caco‐2 permeability. © 2002 Wiley‐Liss Inc. and the American Pharmaceutical Association J Pharm Sci 91:2230–2239, 2002 |
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| AbstractList | Caco‐2 cell monolayers are widely used systems for predicting human intestinal absorption. This study was carried out to develop a quantitative structure–property relationship (QSPR) model of Caco‐2 permeability using a novel genetic algorithm‐based partial least squares (GA‐PLS) method. The Caco‐2 permeability data for 73 compounds were taken from the literature. Molconn‐Z descriptors of these compounds were calculated as molecular descriptors, and the optimal subset of the descriptors was explored by GA‐PLS analysis. A fitness function considering both goodness‐of‐fit to the training data and predictability of the testing data was adopted throughout the genetic algorithm‐driven optimization procedure. The final PLS model consisting of 24 descriptors gave a correlation coefficient (r) of 0.886 for the entire dataset and a predictive correlation coefficient (rpred) of 0.825 that was evaluated by a leave‐some‐out cross‐validation procedure. Thus, the GA‐PLS analysis proved to be a reasonable QSPR modeling approach for predicting Caco‐2 permeability. © 2002 Wiley‐Liss Inc. and the American Pharmaceutical Association J Pharm Sci 91:2230–2239, 2002 Caco-2 cell monolayers are widely used systems for predicting human intestinal absorption. This study was carried out to develop a quantitative structure-property relationship (QSPR) model of Caco-2 permeability using a novel genetic algorithm-based partial least squares (GA-PLS) method. The Caco-2 permeability data for 73 compounds were taken from the literature. Molconn-Z descriptors of these compounds were calculated as molecular descriptors, and the optimal subset of the descriptors was explored by GA-PLS analysis. A fitness function considering both goodness-of-fit to the training data and predictability of the testing data was adopted throughout the genetic algorithm-driven optimization procedure. The final PLS model consisting of 24 descriptors gave a correlation coefficient (r) of 0.886 for the entire dataset and a predictive correlation coefficient (r(pred)) of 0.825 that was evaluated by a leave-some-out cross-validation procedure. Thus, the GA-PLS analysis proved to be a reasonable QSPR modeling approach for predicting Caco-2 permeability.Caco-2 cell monolayers are widely used systems for predicting human intestinal absorption. This study was carried out to develop a quantitative structure-property relationship (QSPR) model of Caco-2 permeability using a novel genetic algorithm-based partial least squares (GA-PLS) method. The Caco-2 permeability data for 73 compounds were taken from the literature. Molconn-Z descriptors of these compounds were calculated as molecular descriptors, and the optimal subset of the descriptors was explored by GA-PLS analysis. A fitness function considering both goodness-of-fit to the training data and predictability of the testing data was adopted throughout the genetic algorithm-driven optimization procedure. The final PLS model consisting of 24 descriptors gave a correlation coefficient (r) of 0.886 for the entire dataset and a predictive correlation coefficient (r(pred)) of 0.825 that was evaluated by a leave-some-out cross-validation procedure. Thus, the GA-PLS analysis proved to be a reasonable QSPR modeling approach for predicting Caco-2 permeability. Caco-2 cell monolayers are widely used systems for predicting human intestinal absorption. This study was carried out to develop a quantitative structure-property relationship (QSPR) model of Caco-2 permeability using a novel genetic algorithm-based partial least squares (GA-PLS) method. The Caco-2 permeability data for 73 compounds were taken from the literature. Molconn-Z descriptors of these compounds were calculated as molecular descriptors, and the optimal subset of the descriptors was explored by GA-PLS analysis. A fitness function considering both goodness-of-fit to the training data and predictability of the testing data was adopted throughout the genetic algorithm-driven optimization procedure. The final PLS model consisting of 24 descriptors gave a correlation coefficient (r) of 0.886 for the entire dataset and a predictive correlation coefficient (r(pred)) of 0.825 that was evaluated by a leave-some-out cross-validation procedure. Thus, the GA-PLS analysis proved to be a reasonable QSPR modeling approach for predicting Caco-2 permeability. |
| Author | Yamashita, Fumiyoshi Hashida, Mitsuru Wanchana, Suchada |
| Author_xml | – sequence: 1 givenname: Fumiyoshi surname: Yamashita fullname: Yamashita, Fumiyoshi organization: Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University, Yoshidashimoadachi‐cho, Sakyo‐ku, Kyoto 606‐8501, Japan – sequence: 2 givenname: Suchada surname: Wanchana fullname: Wanchana, Suchada organization: Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University, Yoshidashimoadachi‐cho, Sakyo‐ku, Kyoto 606‐8501, Japan – sequence: 3 givenname: Mitsuru surname: Hashida fullname: Hashida, Mitsuru email: hashidam@pharm.kyotou.ac.jp organization: Department of Drug Delivery Research, Graduate School of Pharmaceutical Sciences, Kyoto University, Yoshidashimoadachi‐cho, Sakyo‐ku, Kyoto 606‐8501, Japan |
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| Keywords | genetic algorithm Caco‐2 permeability partial least squares Molconn‐Z quantitative structure–property relationship Human Caco-2 permeability Digestive system quantitative structure-property relationship Gut Permeation Prediction Permeability Absorption Genetic algorithm Least squares method Established cell line Property structure relationship Molconn-Z Partial least squares Tumor cell Quantitative analysis |
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Krarup LH, Christensen IT, Hovgaard L, Frokjaer S. 1998. Predicting drug absorption from molecular surface properties based on molecular dynamics simulations. Pharm Res 15: 972-978. Van de Waterbeemd H, Camenisch G, Folkers G, Raevsky OA. 1996. Estimation of Caco-2 cell permeability using calculated molecular descriptors. Quant Struct-Act Relat 15: 480-490. Yoshida F, Topliss JG. 2000. QSAR model for drug human oral bioavailability. J Med Chem 43: 2575-2585. Gough JD, Hall LH. 1999. Antileukemic activity of carboquinones with electrotopological state and chi indices. J Chem Inf Comput Sci 39: 356-361. Palm K, Luthman K, Ungell AL, Strandlund G, Beigi F, Lundahl P, Artursson P. 1998. Evaluation of dynamic polar molecular surface area as predictor of drug absorption: Comparison with other computational and experimental predictors. J Med Chem 41: 5382-5392. Hoffman B, Cho SJ, Zheng W, Wyrick S, Nichols DE, Mailman RB, Tropsha A. 1999. Quantitative structure activity relationship modeling of dopamine D1 antagonists using comparative molecular field analysis, genetic algorithms-partial least squares, and K nearest neighbor methods. J Med Chem 42: 3217-3226. Geladi P, Kowalski BR. 1986. Partial least-squares regression: a tutorial. Anal Chim Acta 185: 1-17. Hovgaard L, Brondsted H, Buur A, Bundgaard H. 1995. Drug delivery studies in Caco-2 monolayers: Synthesis, hydrolysis and transport of o-cyclopropane carboxylic acid ester prodrugs of various beta blocking agents. Pharm Res 12: 387-392. Norinder U, Österberg T, Artursson P. 1997. Theoretical calculation and prediction of Caco-2 cell permeability using Molsurf parameterization and PLS statistics. Pharm Res 14: 1786-1791. Wessel MD, Jurs PC, Tolan JW, Muskal SM. 1998. Prediction of human intestinal absorption of drug compounds from molecular structure. J Chem Inf Comput Sci 38: 726-735. Rubas W, Jezyk N, Grass GM. 1993. Comparison of the permeability characteristics of a human colonic epithelail (Caco-2) cell line to colon of rabbit, monkey, and dog intestinal and human drug absorption. Pharm Res 10: 113-118. 1991; 175 1990; 79 2001; 90 1997; 86 2000; 43 2002; 57 1995; 12 1997; 23 1999; 88 1999; 42 1999; 63 1998; 41 1999; 8 1996; 36 1996; 13 1998; 87 1996; 15 2001; 41 2001; 20 1999 1998; 251 1998; 38 1998; 15 1992; 9 2000; 17 2001; 7 2002; 64 2000; 54 1999; 17 1997; 37 1999; 39 1993; 33 1999; 16 1997; 14 1993; 10 1986; 185 1986 1996; 85 1983; 4598 1989 1996; 22 Yazdanian (10.1002/jps.10214_bb0175) 1998; 15 Norinder (10.1002/jps.10214_bb0095) 1999; 8 Hall (10.1002/jps.10214_bb0255) 1996; 36 Randic (10.1002/jps.10214_bb0215) 2001; 20 Collett (10.1002/jps.10214_bb0165) 1996; 13 Hasegawa (10.1002/jps.10214_bb0110) 1997; 37 Tropsha (10.1002/jps.10214_bb0120) 2001; 7 Kier (10.1002/jps.10214_bb0135) 1986 Oprea (10.1002/jps.10214_bb0025) 1999; 17 Lipinski (10.1002/jps.10214_bb0010) 1997; 23 Wessel (10.1002/jps.10214_bb0060) 1998; 38 Clark (10.1002/jps.10214_bb0080) 1999; 88 Yoshida (10.1002/jps.10214_bb0045) 2000; 43 Artursson (10.1002/jps.10214_bb0140) 1990; 79 Sugawara (10.1002/jps.10214_bb0030) 1998; 87 Hunskonen (10.1002/jps.10214_bb0240) 1998; 38 Artusson (10.1002/jps.10214_bb0220) 1996; 22 Kirkpatrick (10.1002/jps.10214_bb0105) 1983; 4598 Katritzky (10.1002/jps.10214_bb0250) 1993; 33 Palm (10.1002/jps.10214_bb0085) 1997; 14 Wanchana (10.1002/jps.10214_bb0125) 2002; 57 Krarup (10.1002/jps.10214_bb0065) 1998; 15 Ren (10.1002/jps.10214_bb0020) 2000; 54 Palm (10.1002/jps.10214_bb0070) 1998; 41 Murcia‐Soler (10.1002/jps.10214_bb0210) 2001; 41 Van de Waterbeemd (10.1002/jps.10214_bb0055) 1996; 15 Geladi (10.1002/jps.10214_bb0260) 1986; 185 Artursson (10.1002/jps.10214_bb0145) 1991; 175 Sutter (10.1002/jps.10214_bb0230) 1996; 36 Hoffman (10.1002/jps.10214_bb0115) 1999; 42 Hovgaard (10.1002/jps.10214_bb0155) 1995; 12 Huuskonen (10.1002/jps.10214_bb0245) 1999; 88 Stenberg (10.1002/jps.10214_bb0050) 1999; 16 Norinder (10.1002/jps.10214_bb0090) 1997; 14 Palm (10.1002/jps.10214_bb0075) 1996; 85 Delie (10.1002/jps.10214_bb0225) 1997; 14 Augustijns (10.1002/jps.10214_bb0160) 1996; 85 Huuskonen (10.1002/jps.10214_bb0235) 1997; 86 Estrada (10.1002/jps.10214_bb0200) 2001; 41 Andrews (10.1002/jps.10214_bb0015) 2000; 17 Goldberg (10.1002/jps.10214_bb0100) 1989 Seelig (10.1002/jps.10214_bb0190) 1998; 251 Yee (10.1002/jps.10214_bb0170) 1997; 14 Gough (10.1002/jps.10214_bb0205) 1999; 39 Bai (10.1002/jps.10214_bb0185) 1992; 9 Rubas (10.1002/jps.10214_bb0150) 1993; 10 Lolkema (10.1002/jps.10214_bb0180) 1999; 63 Russel (10.1002/jps.10214_bb0195) 2002; 64 Kier (10.1002/jps.10214_bb0130) 1999 Egan (10.1002/jps.10214_bb0040) 2000; 43 Norinder (10.1002/jps.10214_bb0035) 2001; 90 |
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| Title | Quantitative structure/property relationship analysis of Caco‐2 permeability using a genetic algorithm‐based partial least squares method |
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