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• W2091839997 abstract "UDP-glucuronosyltransferase 1A10 (UGT1A10) catalyzes glucuronidation of a wide range of chemicals including many drugs. Here, we report the first in silico model quantifying the substrate selectivity and binding affinity (as Km) for UGT1A10. The training set for model construction comprises 32 structurally diverse compounds, which are known substrates for UGT1A10. The model was derived by applying the standard VolSurf method involving calculation of VolSurf descriptors and partial least square (PLS) analyses. The yielded PLS model with two components shows statistical significance in both fitting and internal predicting (r2 = 0.827, q2 = 0.774). The model predictability was further validated against a test set of 11 external compounds. The activity values for all test substrates were predicted within 1 log unit. Moreover, the model reveals an overlay of chemical features influencing the enzyme–substrate binding. Those include the size and shape, capacity factors, hydrophilic regions, hydrophobic regions, and polarizability. In conclusion, the VolSurf approach is successfully utilized to establish a predictive model for UGT1A10. The derived model should be an efficient tool for high-throughput prediction of UGT1A10 metabolism. © 2012 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 101:3531–3539, 2012 UDP-glucuronosyltransferase 1A10 (UGT1A10) catalyzes glucuronidation of a wide range of chemicals including many drugs. Here, we report the first in silico model quantifying the substrate selectivity and binding affinity (as Km) for UGT1A10. The training set for model construction comprises 32 structurally diverse compounds, which are known substrates for UGT1A10. The model was derived by applying the standard VolSurf method involving calculation of VolSurf descriptors and partial least square (PLS) analyses. The yielded PLS model with two components shows statistical significance in both fitting and internal predicting (r2 = 0.827, q2 = 0.774). The model predictability was further validated against a test set of 11 external compounds. The activity values for all test substrates were predicted within 1 log unit. Moreover, the model reveals an overlay of chemical features influencing the enzyme–substrate binding. Those include the size and shape, capacity factors, hydrophilic regions, hydrophobic regions, and polarizability. In conclusion, the VolSurf approach is successfully utilized to establish a predictive model for UGT1A10. The derived model should be an efficient tool for high-throughput prediction of UGT1A10 metabolism. © 2012 Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 101:3531–3539, 2012 Abbreviations used:CoMFAcomparative molecular field analysisH-bondhydrogen bondPCprincipal componentQSARquantitative structure–activity relationshipUGTUDP-glucuronosyltransferaseINTRODUCTIONDrug-metabolizing enzymes catalyze the metabolic reactions such as oxidation, reduction, and conjugation. As a result, a foreign compound is inactivated and readily eliminated from the body, though, in some cases, bioactivation of a foreign compound is possible through these metabolic actions.1.Sheweita S.A. Drug-metabolizing enzymes: Mechanisms and functions.Curr Drug Metab. 2000; 1: 107-132Crossref PubMed Scopus (177) Google Scholar Given their key role in xenobiotic/drug disposition, considerable efforts have been directed to understand the functions, catalytic mechanisms, structures, and regulation of drug-metabolizing enzymes.1.Sheweita S.A. Drug-metabolizing enzymes: Mechanisms and functions.Curr Drug Metab. 2000; 1: 107-132Crossref PubMed Scopus (177) Google Scholar2.Tolson A.H. Wang H. Regulation of drug-metabolizing enzymes by xenobiotic receptors: PXR and CAR.Adv Drug Deliv Rev. 2010; 62: 1238-1249Crossref PubMed Scopus (277) Google Scholar Of note, the substrate selectivity of these enzymes has been an area of long-standing interest. This is because the knowledge can be used to predict the metabolic fate of a new chemical entity, and also to derive the contribution of a particular enzyme to the overall metabolism.UDP-glucuronosyltransferase 1A10 (UGT1A10) is a member of the UGT family (EC 2.4.1.17). Enzymes of this family mediate the glucuronidation reaction, an important metabolic pathway in humans. Because of its high expression in the gastrointestinal tract, UGT1A10 plays a significant role in first-pass glucuronidation of raloxifene, limiting the oral bioavailability (∼2%) of this drug.3.Mizuma T. Intestinal glucuronidation metabolism may have a greater impact on oral bioavailability than hepatic glucuronidation metabolism in humans: A study with raloxifene, substrate for UGT1A1, 1A8, 1A9, and 1A10.Int J Pharm. 2009; 378: 140-141Crossref PubMed Scopus (79) Google Scholar, 4.Jeong E.J. Liu Y. Lin H. Hu M. Species- and disposition model-dependent metabolism of raloxifene in gut and liver: Role of UGT1A10.Drug Metab Dispos. 2005; 33: 785-794Crossref PubMed Scopus (94) Google Scholar, 5.Kosaka K. Sakai N. Endo Y. Fukuhara Y. Tsuda-Tsukimoto M. Ohtsuka T. Kino I. Tanimoto T. Takeba N. Takahashi M. Kume T. Impact of intestinal glucuronidation on the pharmacokinetics of raloxifene.Drug Metab Dispos. 2011; 39: 1495-1502Crossref PubMed Scopus (36) Google Scholar Although lacking support from in vivo experiments, major contribution of UGT1A10 to intestinal metabolism of darexaban and magnolol is also possible.6.Zhu L. Ge G. Zhang H. Liu H. He G. Liang S. Zhang Y. Fang Z. Dong P. Finel M. Yang L. Characterization of hepatic and intestinal glucuronidation of magnolol: Application of the RAF approach to decipher the contributions of multiple UGT isoforms.Drug Metab Dispos. 2012; 40: 529-538Crossref PubMed Scopus (61) Google Scholar7.Shiraga T. Yajima K. Suzuki K. Suzuki K. Hashimoto T. Iwatsubo T. Miyashita A. Usui T. Identification of UDP-glucuronosyltransferases responsible for the glucuronidation of darexaban, an oral factor Xa inhibitor, in human liver and intestine.Drug Metab Dispos. 2012; 40: 276-282Crossref PubMed Scopus (25) Google Scholar In addition, the UGT1A10 polymorphisms (e.g., E129K) with altered enzyme activity have been identified; and they may be an important determinant in risk for various cancers as well as in intersubject variability for pharmacokinetics.8.Dellinger R.W. Fang J.L. Chen G. Weinberg R. Lazarus P. Importance of UDP-glucuronosyltransferase 1A10 (UGT1A10) in the detoxification of polycyclic aromatic hydrocarbons: Decreased glucuronidative activity of the UGT1A10139Lys isoform.Drug Metab Dispos. 2006; 34: 943-949PubMed Google Scholar9.Dellinger R.W. Chen G. Blevins-Primeau A.S. Krzeminski J. Amin S. Lazarus P. Glucuronidation of PhIP and N-OH-PhIP by UDP-glucuronosyltransferase 1A10.Carcinogenesis. 2007; 28: 2412-2418Crossref PubMed Scopus (49) Google ScholarLike other UGT isoforms (e.g., UGT1A1, UGT1A4, and UGT1A9),10.Sorich M.J. Smith P.A. McKinnon R.A. Miners J.O. Pharmacophore and quantitative structure activity relationship modelling of UDP-glucuronosyltransferase 1A1 (UGT1A1) substrates.Pharmacogenetics. 2002; 12: 635-645Crossref PubMed Scopus (69) Google Scholar, 11.Smith P.A. Sorich M.J. McKinnon R.A. Miners J.O. Pharmacophore and quantitative structure–activity relationship modeling: Complementary approaches for the rationalization and prediction of UDP-glucuronosyltransferase 1A4 substrate selectivity.J Med Chem. 2003; 46: 1617-1626Crossref PubMed Scopus (72) Google Scholar, 12.Smith P.A. Sorich M.J. Low L.S. McKinnon R.A. Miners J.O. Towards integrated ADME prediction: Past, present and future directions for modelling metabolism by UDP-glucuronosyltransferases.J Mol Graph Model. 2004; 22: 507-517Crossref PubMed Scopus (60) Google Scholar UGT1A10 demonstrates broad substrate selectivity. The substrates of UGT1A10 include simple phenols, nitrosamines, flavonoids, estrogens, and polycyclic aromatic hydrocarbons.9.Dellinger R.W. Chen G. Blevins-Primeau A.S. Krzeminski J. Amin S. Lazarus P. Glucuronidation of PhIP and N-OH-PhIP by UDP-glucuronosyltransferase 1A10.Carcinogenesis. 2007; 28: 2412-2418Crossref PubMed Scopus (49) Google Scholar,13.Balliet R.M. Chen G. Dellinger R.W. Lazarus P. UDP-glucuronosyltransferase 1A10: Activity against the tobacco-specific nitrosamine, 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol, and a potential role for a novel UGT1A10 promoter deletion polymorphism in cancer susceptibility.Drug Metab Dispos. 2010; 38: 484-490Crossref PubMed Scopus (21) Google Scholar, 14.Xiong Y. Bernardi D. Bratton S. Ward M.D. Battaglia E. Finel M. Drake R.R. Radominska-Pandya A. Phenylalanine 90 and 93 are localized within the phenol binding site of human UDP-glucuronosyltransferase 1A10 as determined by photoaffinity labeling, mass spectrometry, and site-directed mutagenesis.Biochemistry. 2006; 45: 2322-2332Crossref PubMed Scopus (36) Google Scholar, 15.Höglund C. Sneitz N. Radominska-Pandya A. Laakonen L. Finel M. Phenylalanine 93 of the human UGT1A10 plays a major role in the interactions of the enzyme with estrogens.Steroids. 2011; 76: 1465-1473Crossref PubMed Scopus (9) Google Scholar, 16.Lewinsky R.H. Smith P.A. Mackenzie P.I. Glucuronidation of bioflavonoids by human UGT1A10: Structure–function relationships.Xenobiotica. 2005; 35: 117-129Crossref PubMed Scopus (28) Google Scholar This promiscuity in substrate selection is advantageous for detoxification of chemicals, but it poses significant challenges in understanding the chemical features for UGT substrates. Nonetheless, Miners' group has successfully established substrate models for UGT1A1 and UGT1A4 using two-dimensional (2D)-/three-dimensional (3D)-quantitative structure–activity relationship (QSAR) techniques (including pharmacophore).10.Sorich M.J. Smith P.A. McKinnon R.A. Miners J.O. Pharmacophore and quantitative structure activity relationship modelling of UDP-glucuronosyltransferase 1A1 (UGT1A1) substrates.Pharmacogenetics. 2002; 12: 635-645Crossref PubMed Scopus (69) Google Scholar11.Smith P.A. Sorich M.J. McKinnon R.A. Miners J.O. Pharmacophore and quantitative structure–activity relationship modeling: Complementary approaches for the rationalization and prediction of UDP-glucuronosyltransferase 1A4 substrate selectivity.J Med Chem. 2003; 46: 1617-1626Crossref PubMed Scopus (72) Google Scholar Unexpectedly, attempts to modeling UGT1A9 substrates with the same methods by the same group of investigators were unsuccessful.12.Smith P.A. Sorich M.J. Low L.S. McKinnon R.A. Miners J.O. Towards integrated ADME prediction: Past, present and future directions for modelling metabolism by UDP-glucuronosyltransferases.J Mol Graph Model. 2004; 22: 507-517Crossref PubMed Scopus (60) Google Scholar In a later study, UGT1A9 substrate models were constructed by applying comparative molecular field analysis (CoMFA) method.17.Wu B. Morrow J.K. Singh R. Zhang S. Hu M. Three-dimensional quantitative structure–activity relationship studies on UGT1A9-mediated 3-O-glucuronidation of natural flavonols using a pharmacophore-based comparative molecular field analysis model.J Pharmacol Exp Ther. 2011; 336: 403-413Crossref PubMed Scopus (33) Google Scholar Taken together, this indicates that modeling/predicting substrates for different UGT isoforms may require distinct algorithms. Here, we aim to elucidate the substrate selectivity of UGT1A10 using the VolSurf approach. VolSurf is a computational procedure to produce 2D molecular descriptors from 3D molecular interaction energy grid maps.18.Cruciani G. Crivori P. Carrupt P.-.A. Testa B. Molecular fields in quantitative structure-permeation relationships: The VolSurf approach.J Mol Struct: THEOCHEM. 2000; 503: 17-30Crossref Scopus (547) Google Scholar19.Cruciani G. Pastor M. Guba W. VolSurf: A new tool for the pharmacokinetic optimization of lead compounds.Eur J Pharm Sci Suppl. 2000; 2: S29-S39Crossref Scopus (394) Google Scholar The principal advantage of these descriptors is that they do not require structural superposition and mapping for a 3D-QSAR, as are required, respectively, in CoMFA and pharmacophore modeling (two other 3D-QSAR techniques, please refer to the literature for detailed introduction).20.Cramer R.D. Patterson D.E. Bunce J.D. Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins.J Am Chem Soc. 1988; 110: 5959-5967Crossref PubMed Scopus (4061) Google Scholar21.Langer T. Hoffmann R.D. Pharmacophores and pharmacophore searches. Wiley-VCH, Weinheim2006Crossref Scopus (9) Google ScholarMATERIALS AND METHODSData SetA data set (Km values) of 43 diverse UGT1A10 substrates, 32 of which were used as a training set and 11 of which were used as a test set, was collated from the literature (Table 1).Table 1Experimental and Calculated UGT1A10 Activities for the Training Set (No. 1–32) and Test Set (No. 33–43) compounds in this studyCompoundNameKm (mM)Log(1/Km) ExperimentalInitial Model Log(1/Km)aPredicted values from the initial UGT1A10 model.Refined Model Log(1/Km)bPredicted values from the refined UGT1A10 model.Reference1.3-Hydroxybenzo(a)pyrene0.0102.011.732.038.Dellinger R.W. Fang J.L. Chen G. Weinberg R. Lazarus P. Importance of UDP-glucuronosyltransferase 1A10 (UGT1A10) in the detoxification of polycyclic aromatic hydrocarbons: Decreased glucuronidative activity of the UGT1A10139Lys isoform.Drug Metab Dispos. 2006; 34: 943-949PubMed Google Scholar2.4-Methylumbelliferone0.1230.910.200.3114.Xiong Y. Bernardi D. Bratton S. Ward M.D. Battaglia E. Finel M. Drake R.R. Radominska-Pandya A. Phenylalanine 90 and 93 are localized within the phenol binding site of human UDP-glucuronosyltransferase 1A10 as determined by photoaffinity labeling, mass spectrometry, and site-directed mutagenesis.Biochemistry. 2006; 45: 2322-2332Crossref PubMed Scopus (36) Google Scholar3.4-Nitrophenol0.3870.410.140.1515.Höglund C. Sneitz N. Radominska-Pandya A. Laakonen L. Finel M. Phenylalanine 93 of the human UGT1A10 plays a major role in the interactions of the enzyme with estrogens.Steroids. 2011; 76: 1465-1473Crossref PubMed Scopus (9) Google Scholar4.4-Hydroxyindole3.624−0.560.340.2622.Manevski N. Kurkela M. Höglund C. Mauriala T. Court M.H. Yli-Kauhaluoma J. Finel M. Glucuronidation of psilocin and 4-hydroxyindole by the human UDP-glucuronosyltransferases.Drug Metab Dispos. 2010; 38: 386-395Crossref PubMed Scopus (36) Google Scholar5.7-Hydroxybenzo(a)pyrene0.0102.011.711.948.Dellinger R.W. Fang J.L. Chen G. Weinberg R. Lazarus P. Importance of UDP-glucuronosyltransferase 1A10 (UGT1A10) in the detoxification of polycyclic aromatic hydrocarbons: Decreased glucuronidative activity of the UGT1A10139Lys isoform.Drug Metab Dispos. 2006; 34: 943-949PubMed Google Scholar6.7-Hydroxywarfarin0.1700.771.271.0623.Miller G.P. Lichti C.F. Zielinska A.K. Mazur A. Bratton S.M. Gallus-Zawada A. Finel M. Moran J.H. Radominska-Pandya A. Identification of hydroxywarfarin binding site in human UDP glucuronosyltransferase 1a10: Phenylalanine90 is crucial for the glucuronidation of 6- and 7-hydroxywarfarin but not 8-hydroxywarfarin.Drug Metab Dispos. 2008; 36: 2211-2218Crossref PubMed Scopus (11) Google Scholar7.Aldosterone0.3890.410.580.5124.Knights K.M. Winner L.K. Elliot D.J. Bowalgaha K. Miners J.O. Aldosterone glucuronidation by human liver and kidney microsomes and recombinant UDP-glucuronosyltransferases: Inhibition by NSAIDs.Br J Clin Pharmacol. 2009; 68: 402-412Crossref PubMed Scopus (50) Google Scholar8.Alizarin0.1250.901.000.9425.Cheng Z. Radominska-Pandya A. Tephly T.R. Studies on the substrate specificity of human intestinal UDP-lucuronosyltransferases 1A8 and 1A10.Drug Metab Dispos. 1999; 27: 1165-1170PubMed Google Scholar9.Apigenin0.0231.641.331.4625.Cheng Z. Radominska-Pandya A. Tephly T.R. 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Phenylalanine 93 of the human UGT1A10 plays a major role in the interactions of the enzyme with estrogens.Steroids. 2011; 76: 1465-1473Crossref PubMed Scopus (9) Google Scholar16.Feruic acid2.490−0.400.030.0130.Li X. Shang L. Wu Y. Abbas S. Li D. Netter P. Ouzzine M. Wang H. Magdalou J. Identification of the human UDP-glucuronosyltransferase isoforms involved in the glucuronidation of the phytochemical ferulic acid.Drug Metab Pharmacokinet. 2011; 26: 341-350Crossref PubMed Scopus (16) Google Scholar17.Genistein0.0121.911.431.3131.Tang L. Singh R. Liu Z. Hu M. Structure and concentration changes affect characterization of UGT isoform-specific metabolism of isoflavones.Mol Pharm. 2009; 6: 1466-1482Crossref PubMed Scopus (87) Google Scholar18.Hesperetin0.0301.521.281.0632.Brand W. Boersma M.G. Bik H. Hoek-van den Hil E.F. Vervoort J. Barron D. Meinl W. Glatt H. Williamson G. van Bladeren P.J. Rietjens I.M. 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Identification of hydroxywarfarin binding site in human UDP glucuronosyltransferase 1a10: Phenylalanine90 is crucial for the glucuronidation of 6- and 7-hydroxywarfarin but not 8-hydroxywarfarin.Drug Metab Dispos. 2008; 36: 2211-2218Crossref PubMed Scopus (11) Google Scholar34.8-Hydroxywarfarin0.3900.411.200.9423.Miller G.P. Lichti C.F. Zielinska A.K. Mazur A. Bratton S.M. Gallus-Zawada A. Finel M. Moran J.H. Radominska-Pandya A. Identification of hydroxywarfarin binding site in human UDP glucuronosyltransferase 1a10: Phenylalanine90 is crucial for the glucuronidation of 6- and 7-hydroxywarfarin but not 8-hydroxywarfarin.Drug Metab Dispos. 2008; 36: 2211-2218Crossref PubMed Scopus (11) Google Scholar35.Estradiol0.0641.191.100.9144.Basu N.K. Kubota S. Meselhy M.R. Ciotti M. Chowdhury B. Hartori M. Owens I.S. Gastrointestinally distributed UDP-glucuronosyltransferase 1A10, which metabolizes estrogens and nonsteroidal anti-inflammatory drugs, depends upon phosphorylation.J Biol Chem. 2004; 279: 28320-28329Crossref PubMed Scopus (47) Google Scholar36.Eugenol0.0781.110.380.2625.Cheng Z. Radominska-Pandya A. Tephly T.R. Studies on the substrate specificity of human intestinal UDP-lucuronosyltransferases 1A8 and 1A10.Drug Metab Dispos. 1999; 27: 1165-1170PubMed Google Scholar37.Prunetin0.0042.371.501.5031.Tang L. Singh R. Liu Z. Hu M. Structure and concentration changes affect characterization of UGT isoform-specific metabolism of isoflavones.Mol Pharm. 2009; 6: 1466-1482Crossref PubMed Scopus (87) Google Scholar38.4-Hydroxytamoxifen0.0961.022.152.0728.Blevins-Primeau A.S. Sun D. Chen G. Sharma A.K. Gallagher C.J. Amin S. Lazarus P. Functional significance of UDP-glucuronosyltransferase variants in the metabolism of active tamoxifen metabolites.Cancer Res. 2009; 69: 1892-1900Crossref PubMed Scopus (68) Google Scholar39.1-Hydroxypyrene0.0111.951.141.368.Dellinger R.W. Fang J.L. Chen G. Weinberg R. Lazarus P. Importance of UDP-glucuronosyltransferase 1A10 (UGT1A10) in the detoxification of polycyclic aromatic hydrocarbons: Decreased glucuronidative activity of the UGT1A10139Lys isoform.Drug Metab Dispos. 2006; 34: 943-949PubMed Google Scholar40.Cis-resveratrol0.2500.601.121.0145.Iwuchukwu O.F. Nagar S. Cis-resveratrol glucuronidation kinetics in human and recombinant UGT1A sources.Xenobiotica. 2010; 40: 102-108Crossref PubMed Scopus (10) Google Scholar41.N-hydroxy PhIP0.0761.121.231.439.Dellinger R.W. Chen G. Blevins-Primeau A.S. Krzeminski J. Amin S. Lazarus P. Glucuronidation of PhIP and N-OH-PhIP by UDP-glucuronosyltransferase 1A10.Carcinogenesis. 2007; 28: 2412-2418Crossref PubMed Scopus (49) Google Scholar42.Psilocin3.851−0.590.380.3022.Manevski N. Kurkela M. Höglund C. Mauriala T. Court M.H. Yli-Kauhaluoma J. Finel M. Glucuronidation of psilocin and 4-hydroxyindole by the human UDP-glucuronosyltransferases.Drug Metab Dispos. 2010; 38: 386-395Crossref PubMed Scopus (36) Google Scholar43.9-Hydroxybenzo(a)pyrene0.0381.421.711.998.Dellinger R.W. Fang J.L. Chen G. Weinberg R. Lazarus P. Importance of UDP-glucuronosyltransferase 1A10 (UGT1A10) in the detoxification of polycyclic aromatic hydrocarbons: Decreased glucuronidative activity of the UGT1A10139Lys isoform.Drug Metab Dispos. 2006; 34: 943-949PubMed Google ScholarPlease see Figures 1 and 3 for correlation plots of experimental versus calculated values.a Predicted values from the initial UGT1A10 model.b Predicted values from the refined UGT1A10 model. Open table in a new tab Km value is the Michaelis constant derived from experimental kinetic profiling using recombinant UGT1A10. All enzyme assays were performed without addition of albumen (bovine serum albumin or human serum albumin), which has been shown to alter Km value of glucuronidation mediated by UGT isoforms such as UGT1A9.46.Rowland A. Knights K.M. Mackenzie P.I. Miners J.O. The “albumin effect” and drug glucuronidation: Bovine serum albumin and fatty acid-free human serum albumin enhance the glucuronidation of UDP-glucuronosyltransferase (UGT) 1A9 substrates but not UGT1A1 and UGT1A6 activities.Drug Metab Dispos. 2008; 36: 1056-1062Crossref PubMed Scopus (139) Google Scholar The training set was used for model building, and the test set was used for an external validation of the model. The 3D structures for all substrates were prepared using SYBYL 8.0 (Tripos, St. Louis, Missouri). Amine (primary, secondary, and tertiary) groups were protonated. Carboxylate groups were considered to be deprotonated. Partial atomic charges were determined using Gasteiger–Marsili method. Energy minimizations were performed using the Tripos force field with a distance-dependent dielectric and a conjugate gradient method (convergence criterion 0.01 kcal/mol).Calculation of VolSurf Descriptors and Statistical AnalysisA set of 94 Volsurf descriptors were generated from 3D molecular fields by using the Volsurf program contained in SYBYL 8.0 (Tripos). Detailed definitions of these descriptors are provided in the literature.18.Cruciani G. Crivori P. Carrupt P.-.A. Testa B. Molecular fields in quantitative structure-permeation relationships: The VolSurf approach.J Mol Struct: THEOCHEM. 2000; 503: 17-30Crossref Scopus (547) Google Scholar47.Crivori P. Cruciani G. Carrupt P.A. Testa B. Predicting blood–brain barrier permeation from three-dimensional molecular structure.J Med Chem. 2000; 43: 2204-2216Crossref PubMed Scopus (433) Google Scholar The water probe (OH2) was used to simulate solvation–desolvation processes, whereas the hydrophobic probe (DRY) and the carbonyl probe (O) were used to simulate drug–membrane interactions.47.Crivori P. Cruciani G. Carrupt P.A. Testa B. Predicting blood–brain barrier permeation from three-dimensional molecular structure.J Med Chem. 2000; 43: 2204-2216Crossref PubMed Scopus (433) Google Scholar The DRY probe is a specific probe for the computation of the hydrophobic energy; the overall energy of the hydrophobic probe, R, is computed at each grid point as Eentropy + ELJ–EHB, where Eentropy is the ideal entropic component of the hydrophobic effect in an aqueous environment, ELJ measures the induction and dispersion interactions occurring between any pair of molecules, and EHB measures the H-bonding interactions between water molecules and polar groups on the target surface.Partial least square (PLS) analyses were implemented in the Volsurf program. To check the statistical significance of the model, cross-validations were performed by means of the “leave-one-out” procedure. The optimal number of components [or principal components (PCs)] was determined by selecting the highest q2 value. The q2 (cross-validated r2) and r2 (noncross-validated r2) were computed as defined in VolSurf program. The fractional factorial design (FFD) procedure was used to select the variables, which have the largest effect on predictability.R" @default.
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