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Volumn 6, Issue 8, 2011, Pages 783-796

Using artificial neural networks to predict cell-penetrating compounds

Author keywords

Artificial neural network; BBB penetration; Cell membrane permeability; Cell penetrating peptides; Gastrointestinal permeation; QSAR

Indexed keywords

CELL PENETRATING PEPTIDE;

EID: 79960479289     PISSN: 17460441     EISSN: 1746045X     Source Type: Journal    
DOI: 10.1517/17460441.2011.586689     Document Type: Review
Times cited : (18)

References (84)
  • 2
    • 77958029276 scopus 로고    scopus 로고
    • Quantitative correlation of physical and chemical properties with chemical structure: Utility for prediction
    • Katritzky AR, Kuanar M, Slavov S, et al. Quantitative correlation of physical and chemical properties with chemical structure: utility for prediction. Chem Rev 2010;110(10):5714-89
    • (2010) Chem Rev , vol.110 , Issue.10 , pp. 5714-89
    • Katritzky, A.R.1    Kuanar, M.2    Slavov, S.3
  • 3
    • 0032735695 scopus 로고    scopus 로고
    • Neural networks in drug discovery: Have they lived up to their promise?
    • Manallack DT, Livingstone DJ. Neural networks in drug discovery: have they lived up to their promise? Eur J Med Chem 1999;34:195
    • (1999) Eur J Med Chem , vol.34 , pp. 195
    • Manallack, D.T.1    Livingstone, D.J.2
  • 4
    • 0031735526 scopus 로고    scopus 로고
    • Artificial neural networks for computer-based molecular design
    • Schneider G, Wrede P. Artificial neural networks for computer-based molecular design. Prog Biophys Mol Biol 1998;70:175
    • (1998) Prog Biophys Mol Biol , vol.70 , pp. 175
    • Schneider, G.1    Wrede, P.2
  • 5
    • 0346391120 scopus 로고    scopus 로고
    • Pharmacokinetic parameter prediction from drug structure using artificial neural networks
    • Turner JV, Maddalena DJ, Cutler DJ. Pharmacokinetic parameter prediction from drug structure using artificial neural networks. Int J Pharm 2004;270:209
    • (2004) Int J Pharm , vol.270 , pp. 209
    • Turner, J.V.1    Maddalena, D.J.2    Cutler, D.J.3
  • 6
    • 79960483569 scopus 로고    scopus 로고
    • MATLAB
    • MATLAB. Available from: http://www. mathworks.com/
  • 7
    • 79960496943 scopus 로고    scopus 로고
    • Statistica
    • Statistica. Available from: http://www. statsoft.com/#
  • 8
    • 79960536597 scopus 로고    scopus 로고
    • Virtual Computational Laboratory
    • Virtual Computational Laboratory. Available from: http://www.vcclab.org/ lab/asnn/
  • 9
    • 0037364162 scopus 로고    scopus 로고
    • ADMET in silico modeling: Towards the prediction paradise?
    • Van de Waterbeemd H, Gifford E. ADMET in silico modeling: towards the prediction paradise? Nat Rev Drug Discov 2003;2:192
    • (2003) Nat Rev Drug Discov , vol.2 , pp. 192
    • Van De Waterbeemd, H.1    Gifford, E.2
  • 10
    • 13244282956 scopus 로고    scopus 로고
    • Automatation and robotics in ADME screening
    • Saunders KC. Automatation and robotics in ADME screening. Drug Discov Today 2004;1:373
    • (2004) Drug Discov Today , vol.1 , pp. 373
    • Saunders, K.C.1
  • 11
    • 0034461768 scopus 로고    scopus 로고
    • Drug-like properties and the causes of poor solubility and poor permeability
    • Lipinski CA. Drug-like properties and the causes of poor solubility and poor permeability. J Pharmacol Toxicol Methods 2000;44:235
    • (2000) J Pharmacol Toxicol Methods , vol.44 , pp. 235
    • Lipinski, C.A.1
  • 12
    • 0035821601 scopus 로고    scopus 로고
    • Experimental and computational screening models for the prediction of intestinal drug absorption
    • Stenberg P, Norinder U, Luthman K, et al. Experimental and computational screening models for the prediction of intestinal drug absorption. J Med Chem 2001;44:1927
    • (2001) J Med Chem , vol.44 , pp. 1927
    • Stenberg, P.1    Norinder, U.2    Luthman, K.3
  • 13
    • 0034992583 scopus 로고    scopus 로고
    • Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors
    • Zhao YH, Le J, Abraham MH, et al. Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors. J Pharm Sci 2001;90:749
    • (2001) J Pharm Sci , vol.90 , pp. 749
    • Zhao, Y.H.1    Le Abraham J, M.H.2
  • 14
    • 33947123212 scopus 로고    scopus 로고
    • The drug binding site of human alpha1-acid glycoprotein: Insight from induced circular dichroism and electronic absorption spectra
    • Zsila F, Iwao Y. The drug binding site of human alpha1-acid glycoprotein: insight from induced circular dichroism and electronic absorption spectra. Biochim Biophys Acta 2007;1770:797
    • (2007) Biochim Biophys Acta , vol.1770 , pp. 797
    • Zsila, F.1    Iwao, Y.2
  • 15
    • 33847625066 scopus 로고    scopus 로고
    • Development of a humanized in vitro blood-brain barrier model to screen for brain penetration of antiepileptic drugs
    • Cucullo L, Hossain M, Rapp E, et al. Development of a humanized in vitro blood-brain barrier model to screen for brain penetration of antiepileptic drugs. Epilepsia 2007;48:505
    • (2007) Epilepsia , vol.48 , pp. 505
    • Cucullo, L.1    Hossain, M.2    Rapp, E.3
  • 16
    • 13844299532 scopus 로고    scopus 로고
    • In vitro models for the blood-brain barrier
    • Garberg P, Ball M, Borg N, et al. In vitro models for the blood-brain barrier. Toxicol In Vitro 2005;19:299
    • (2005) Toxicol in Vitro , vol.19 , pp. 299
    • Garberg, P.1    Ball, M.2    Borg, N.3
  • 17
    • 0031781430 scopus 로고    scopus 로고
    • Correlating partitioning and Caco-2 permeability of structurally diverse small molecular weight compounds
    • Yazdanian M, Glynn SL, Wright JL, et al. Correlating partitioning and Caco-2 permeability of structurally diverse small molecular weight compounds. Pharm Res 1998;15:1490
    • (1998) Pharm Res , vol.15 , pp. 1490
    • Yazdanian, M.1    Glynn, S.L.2    Wright, J.L.3
  • 18
    • 33846856720 scopus 로고    scopus 로고
    • Prediction of blood/brain partitioning and human serum albumin binding based on COSMO-RS s-moments
    • Wichmann K, Diedenhofen M, Klamt A. Prediction of blood/brain partitioning and human serum albumin binding based on COSMO-RS s-moments. J Chem Inf Model 2007;47:228
    • (2007) J Chem Inf Model , vol.47 , pp. 228
    • Wichmann, K.1    Diedenhofen, M.2    Klamt, A.3
  • 19
    • 34250658541 scopus 로고    scopus 로고
    • In silico ADME modeling 3: Computational models to predict human intestinal absorption using sphere exclusion and kNN QSAR methods
    • Gunturi SB, Narayanan R. In silico ADME modeling 3: computational models to predict human intestinal absorption using sphere exclusion and kNN QSAR methods. QSAR Comb Sci 2007;26:653
    • (2007) QSAR Comb Sci , vol.26 , pp. 653
    • Gunturi, S.B.1    Narayanan, R.2
  • 20
    • 0345548608 scopus 로고    scopus 로고
    • Modeling of drug albumin binding affinity with E-State topological structure representation
    • Hall LM, Hall LH, Kier LB. Modeling of drug albumin binding affinity with E-State topological structure representation. J Chem Inf Comput Sci 2003;43:2120
    • (2003) J Chem Inf Comput Sci , vol.43 , pp. 2120
    • Hall, L.M.1    Hall, L.H.2    Kier, L.B.3
  • 24
    • 0022471098 scopus 로고
    • Learning representation by back-propagating errors
    • Rumelhart DE, Hinton GE, Williams RJ. Learning representation by back-propagating errors. Nature 1986;323:533-6
    • (1986) Nature , vol.323 , pp. 533-6
    • Rumelhart, D.E.1    Hinton, G.E.2    Williams, R.J.3
  • 26
    • 25044463873 scopus 로고    scopus 로고
    • Special issue on RBF networks Part i
    • Sanchez VD. Special issue on RBF networks, Part I. Neurocomputing, 19; 1998
    • (1998) Neurocomputing , vol.19
    • Sanchez, V.D.1
  • 27
    • 25044463873 scopus 로고    scopus 로고
    • Special issue on RBF networks Part II
    • Sanchez VD. Special issue on RBF networks, Part II. Neurocomputing, 20; 1998
    • (1998) Neurocomputing , vol.20
    • Sanchez, V.D.1
  • 28
    • 0001441372 scopus 로고
    • Probable networks and plausible predictions a review of practical bayesian methods for supervised neural networks
    • Mackay DJ. Probable networks and plausible predictions a review of practical bayesian methods for supervised neural networks. Comput Neural Syst 1995;6:469
    • (1995) Comput Neural Syst , vol.6 , pp. 469
    • MacKay, D.J.1
  • 29
    • 0033549850 scopus 로고    scopus 로고
    • Robust QSAR models using bayesian regularized neural networks
    • DOI 10.1021/jm980697n
    • Burden FR, Winkler DA. Robust QSAR models using bayesian regularized neural networks. J Med Chem 1999;42:3183-7 (Pubitemid 29384055)
    • (1999) Journal of Medicinal Chemistry , vol.42 , Issue.16 , pp. 3183-3187
    • Burden, F.R.1    Winkler, D.A.2
  • 32
    • 0031501455 scopus 로고    scopus 로고
    • Genetic algorithms and their use in chemistry
    • Boyd DB, Lipkowitz KB, editors Wiley
    • Judson R. Genetic algorithms and their use in chemistry. In: Boyd DB, Lipkowitz KB, editors, Reviews in computational chemistry. Wiley; 1997
    • (1997) Reviews in Computational Chemistry
    • Judson, R.1
  • 34
    • 0035478854 scopus 로고    scopus 로고
    • Random forests
    • Breiman LE. Random forests. Mach Learn 2001;45:5-32
    • (2001) Mach Learn , vol.45 , pp. 5-32
    • Breiman, L.E.1
  • 36
    • 5544242529 scopus 로고    scopus 로고
    • MMFF VI. MMFF94s option for energy minimization studies
    • Halgren TA. MMFF VI. MMFF94s option for energy minimization studies. J Comput Chem 1999;20:720
    • (1999) J Comput Chem , vol.20 , pp. 720
    • Halgren, T.A.1
  • 38
    • 0842341771 scopus 로고
    • Development and use of quantum mechanical molecular models. AM1: A new general purpose quantum mechanical molecular model
    • Dewar MJS, Zoebisch EG, Healy EF, et al. Development and use of quantum mechanical molecular models. AM1: a new general purpose quantum mechanical molecular model. J Am Chem Soc 1985;107:3902
    • (1985) J Am Chem Soc , vol.107 , pp. 3902
    • Mjs, D.1    Zoebisch, E.G.2    Healy, E.F.3
  • 40
    • 18144404059 scopus 로고    scopus 로고
    • Correlation of boiling points with molecular structure. 1. A training set of 298 diverse organics and a test set of 9 simple inorganics
    • Katritzky AR, Mu L, Lobanov VS, et al. Correlation of boiling points with molecular structure. 1. A training set of 298 diverse organics and a test set of 9 simple inorganics. J Phys Chem 1996;100:10400
    • (1996) J Phys Chem , vol.100 , pp. 10400
    • Katritzky, A.R.1    Mu, L.2    Lobanov, V.S.3
  • 41
    • 0028467707 scopus 로고
    • Application of genetic function approximation to quantitative structure-activity relationships and quantitative structure-property relationships
    • Rogers DR, Hopfinger AJ. Application of genetic function approximation to quantitative structure-activity relationships and quantitative structure-property relationships. J Chem Inf Comput Sci 1994;34:854
    • (1994) J Chem Inf Comput Sci , vol.34 , pp. 854
    • Rogers, D.R.1    Hopfinger, A.J.2
  • 42
    • 0028548591 scopus 로고
    • Evolutionary programming applied to the development of quantitative structure-activity relationships and quantitative structure-property relationships
    • Luke BT. Evolutionary programming applied to the development of quantitative structure-activity relationships and quantitative structure-property relationships. J Chem Inf Comput Sci 1994;34:1279
    • (1994) J Chem Inf Comput Sci , vol.34 , pp. 1279
    • Luke, B.T.1
  • 43
    • 0029970338 scopus 로고    scopus 로고
    • Evolutionary optimization in quantitative structure activity relationship: An application of genetic neural networks
    • Sung-Sau S, Karplus M. Evolutionary optimization in quantitative structure activity relationship: an application of genetic neural networks. J Med Chem 1996;39:1521
    • (1996) J Med Chem , vol.39 , pp. 1521
    • Sung-Sau, S.1    Karplus, M.2
  • 44
    • 0001245212 scopus 로고    scopus 로고
    • The use of automatic relevance determination in QSAR studies using Bayesian neural nets
    • Burden FR, Ford M, Whitley D, et al. The use of automatic relevance determination in QSAR studies using Bayesian neural nets. J Chem Inf Comput Sci 2000;40:1423
    • (2000) J Chem Inf Comput Sci , vol.40 , pp. 1423
    • Burden, F.R.1    Ford, M.2    Whitley, D.3
  • 45
    • 0001447184 scopus 로고
    • Neural network studies: Comparison of overfitting and overtraining
    • Tetko IV, Livingstone DJ, Luik AI. Neural network studies: comparison of overfitting and overtraining. J Chem Inf Comput Sci 1995;35:826
    • (1995) J Chem Inf Comput Sci , vol.35 , pp. 826
    • Tetko, I.V.1    Livingstone, D.J.2    Luik, A.I.3
  • 47
    • 0026075594 scopus 로고
    • Applications of neural networks in quantitative structure-activity relationships of dihydrofolate reductase inhibitors
    • Andrea TA, Kalayeh H. Applications of neural networks in quantitative structure-activity relationships of dihydrofolate reductase inhibitors. J Med Chem 1991;34:2824
    • (1991) J Med Chem , vol.34 , pp. 2824
    • Andrea, T.A.1    Kalayeh, H.2
  • 48
    • 0035438386 scopus 로고    scopus 로고
    • Toward an optimal procedure for variable selection and QSAR model building
    • Yasri A, Hartsough D. Toward an optimal procedure for variable selection and QSAR model building. J Chem Inf Comput Sci 2001;41:1218
    • (2001) J Chem Inf Comput Sci , vol.41 , pp. 1218
    • Yasri, A.1    Hartsough, D.2
  • 49
    • 0033178249 scopus 로고    scopus 로고
    • Pharmacokinetics and metabolism in early drug discovery
    • Smith DA, van de Waterbeemd H. Pharmacokinetics and metabolism in early drug discovery. Curr Opin Chem Biol 1999;3:373
    • (1999) Curr Opin Chem Biol , vol.3 , pp. 373
    • Smith, D.A.1    Van De Waterbeemd, H.2
  • 50
    • 0001334658 scopus 로고    scopus 로고
    • Design principles for orally bioavailable drugs
    • Navia MA, Chaturvedi PR. Design principles for orally bioavailable drugs. Drug Dev Today 1996;1:179
    • (1996) Drug Dev Today , vol.1 , pp. 179
    • Navia, M.A.1    Chaturvedi, P.R.2
  • 51
    • 0000312699 scopus 로고    scopus 로고
    • Physicochemical and drug-delivery considerations for oral drug bioavailability
    • Chan OH, Stewart BH. Physicochemical and drug-delivery considerations for oral drug bioavailability. Drug Dev Today 1996;1:461
    • (1996) Drug Dev Today , vol.1 , pp. 461
    • Chan, O.H.1    Stewart, B.H.2
  • 52
    • 0031024172 scopus 로고    scopus 로고
    • Discrimination between drug candidates using models for evaluation of intestinal absorption
    • DOI 10.1016/S0169-409X(96)00424-3, PII S0169409X96004243
    • Stewart BH, Chan OH, Jezyk N, et al. Discrimination between drug candidates using models for evaluation of intestinal absorption. Adv Drug Deliv Rev 1997;23:27-45 (Pubitemid 27046992)
    • (1997) Advanced Drug Delivery Reviews , vol.23 , Issue.1-3 , pp. 27-45
    • Stewart, B.H.1    Chan, O.H.2    Jezyk, N.3    Fleisher, D.4
  • 53
    • 0033278620 scopus 로고    scopus 로고
    • Gastrointestinal absorption of drugs: Methods and studies
    • Barthe L, Woodley J, Houin G. Gastrointestinal absorption of drugs: methods and studies. Fundam Clin Pharmacol 1999;13:154
    • (1999) Fundam Clin Pharmacol , vol.13 , pp. 154
    • Barthe, L.1    Woodley, J.2    Houin, G.3
  • 54
    • 0035523263 scopus 로고    scopus 로고
    • Strategies for absorption screening in drug discovery and development
    • Bohets H, Annaert P, Mannens G, et al. Strategies for absorption screening in drug discovery and development. Curr Top Med Chem 2001;1:367
    • (2001) Curr Top Med Chem , vol.1 , pp. 367
    • Bohets, H.1    Annaert, P.2    Mannens, G.3
  • 55
    • 0347989382 scopus 로고    scopus 로고
    • In depth evaluation of Gly-Sar transport parameters as a function of culture time in the Caco-2 cell model
    • Bravo SA, Nielsen CU, Amstrup J, et al. In depth evaluation of Gly-Sar transport parameters as a function of culture time in the Caco-2 cell model. Eur J Pharm Sci 2004;21:77
    • (2004) Eur J Pharm Sci , vol.21 , pp. 77
    • Bravo, S.A.1    Nielsen, C.U.2    Amstrup, J.3
  • 56
    • 0032568397 scopus 로고    scopus 로고
    • Physicochemical high throughput screening: Parallel artificial membrane permeability assay in the description of passive absorption processes
    • Kansy M, Senner F, Gubernator K. Physicochemical high throughput screening: parallel artificial membrane permeability assay in the description of passive absorption processes. J Med Chem 1998;41:1007
    • (1998) J Med Chem , vol.41 , pp. 1007
    • Kansy, M.1    Senner, F.2    Gubernator, K.3
  • 57
    • 0001347981 scopus 로고
    • The structure and electrochemical properties of a polymer-supported lipid biosensor
    • Thompson M, Krull UJ, Worsfold P. The structure and electrochemical properties of a polymer-supported lipid biosensor. J Anal Chim Acta 1980;117:133
    • (1980) J Anal Chim Acta , vol.117 , pp. 133
    • Thompson, M.1    Krull, U.J.2    Worsfold, P.3
  • 58
    • 0037030653 scopus 로고    scopus 로고
    • Molecular properties that influence the oral bioavailability of drug candidates
    • Veber DF, Johnson SR, Cheng H-Y, et al. Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem 2002;45:2615
    • (2002) J Med Chem , vol.45 , pp. 2615
    • Veber, D.F.1    Johnson, S.R.2    Cheng, H.-Y.3
  • 59
    • 2642527944 scopus 로고    scopus 로고
    • Combined application of parallel artificial membrane permeability assay and Caco-2 permeability assays in drug discovery
    • Kerns EH, Di L, Petuskey S, et al. Combined application of parallel artificial membrane permeability assay and Caco-2 permeability assays in drug discovery. J Pharm Sci 2004;93:1440
    • (2004) J Pharm Sci , vol.93 , pp. 1440
    • Kerns, E.H.1    Di Petuskey L, S.2
  • 61
    • 0032112107 scopus 로고    scopus 로고
    • Prediction of human intestinal absorption of drug compounds from molecular structure
    • Wessel MD, Jurs PC, Tolan JW, et al. Prediction of human intestinal absorption of drug compounds from molecular structure. J Chem Inf Comput Sci 1998;38:726
    • (1998) J Chem Inf Comput Sci , vol.38 , pp. 726
    • Wessel, M.D.1    Jurs, P.C.2    Tolan, J.W.3
  • 62
    • 0035081938 scopus 로고    scopus 로고
    • Theoretically-derived molecular descriptors important in human intestinal absorption
    • Agatonovic-Kustrin S, Beresford R, Yusof APM. Theoretically-derived molecular descriptors important in human intestinal absorption. J Pharm Biomed Anal 2001;25:227
    • (2001) J Pharm Biomed Anal , vol.25 , pp. 227
    • Agatonovic-Kustrin, S.1    Beresford, R.2    Yusof, A.P.M.3
  • 63
    • 2942717219 scopus 로고    scopus 로고
    • Feature selection for descriptor based classification models 2 human intestinal absorption (HIA)
    • Wegner JK, Frohlich H, Zell A. Feature selection for descriptor based classification models 2 human intestinal absorption (HIA). J Chem Inf Comput Sci 2004;44:931
    • (2004) J Chem Inf Comput Sci , vol.44 , pp. 931
    • Wegner, J.K.1    Frohlich, H.2    Zell, A.3
  • 64
    • 0037208305 scopus 로고    scopus 로고
    • Using general regression and probabilistic neural networks to predict human intestinal absorption with topological descriptors derived from two-dimensional chemical structures
    • Niwa T. Using general regression and probabilistic neural networks to predict human intestinal absorption with topological descriptors derived from two-dimensional chemical structures. J Chem Inf Comput Sci 2003;43:113
    • (2003) J Chem Inf Comput Sci , vol.43 , pp. 113
    • Niwa, T.1
  • 65
    • 0043198439 scopus 로고    scopus 로고
    • Predicting drug pharmacokinetic properties using molecular interaction fields and SIMCA
    • Wolohan PR, Clark RD. Predicting drug pharmacokinetic properties using molecular interaction fields and SIMCA. J Comput Aided Mol Des 2003;17:65
    • (2003) J Comput Aided Mol des , vol.17 , pp. 65
    • Wolohan, P.R.1    Clark, R.D.2
  • 66
    • 29144484633 scopus 로고    scopus 로고
    • Predictive human intestinal absorption QSAR models using bayesian regularized neural networks
    • Polley MJ, Burden F, Winkler D. Predictive human intestinal absorption QSAR models using bayesian regularized neural networks. Aust J Chem 2005;58:859
    • (2005) Aust J Chem , vol.58 , pp. 859
    • Polley, M.J.1    Burden, F.2    Winkler, D.3
  • 67
    • 0034992583 scopus 로고    scopus 로고
    • Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors
    • Zhao YH, Le J, Abraham MH, et al. Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors. J Pharm Sci 2001;90:749
    • (2001) J Pharm Sci , vol.90 , pp. 749
    • Zhao, Y.H.1    Le Abraham J, M.H.2
  • 68
    • 34047170242 scopus 로고    scopus 로고
    • Caco-2 cell permeability modelling: A neural network coupled genetic algorithm approach
    • Di Fenza A, Alagona G, Ghio C, et al. Caco-2 cell permeability modelling: a neural network coupled genetic algorithm approach. J Comput Aided Mol Des 2007;21:207
    • (2007) J Comput Aided Mol des , vol.21 , pp. 207
    • Di Fenza, A.1    Alagona, G.2    Ghio, C.3
  • 69
    • 77951788893 scopus 로고    scopus 로고
    • QSAR study of pharamacological permeabilities
    • Karelson M, Karelson G, Tamm T, et al. QSAR study of pharamacological permeabilities. Arkivoc 2009;ii:218
    • (2009) Arkivoc , vol.2 , pp. 218
    • Karelson, M.1    Karelson, G.2    Tamm, T.3
  • 70
    • 85060355787 scopus 로고    scopus 로고
    • A review of blood-brain barrier transport techniques
    • Smith QR. A review of blood-brain barrier transport techniques. Methods Mol Med 2003;93:208
    • (2003) Methods Mol Med , vol.93 , pp. 208
    • Smith, Q.R.1
  • 71
    • 0033304395 scopus 로고    scopus 로고
    • Drug transfer across the blood-brain barrier and improvement of brain delivery
    • Jolliet-Riant P, Tillement JP. Drug transfer across the blood-brain barrier and improvement of brain delivery. Fundam Clin Pharmacol 1999;13:26
    • (1999) Fundam Clin Pharmacol , vol.13 , pp. 26
    • Jolliet-Riant, P.1    Tillement, J.P.2
  • 72
    • 58449085210 scopus 로고    scopus 로고
    • Current in vitro and in silico models for blood-brain barrier penetration: A practical view
    • Vastag M, Keseru GM. Current in vitro and in silico models for blood-brain barrier penetration: a practical view. Curr Opin Drug Discov Devel 2009;12(1):115
    • (2009) Curr Opin Drug Discov Devel , vol.12 , Issue.1 , pp. 115
    • Vastag, M.1    Keseru, G.M.2
  • 73
    • 2942538155 scopus 로고    scopus 로고
    • Modelling blood-brain barrier partitioning using Bayesian neural nets
    • Winkler DA, Burden FR. Modelling blood-brain barrier partitioning using Bayesian neural nets. J Mol Graph Model 2004;22:499
    • (2004) J Mol Graph Model , vol.22 , pp. 499
    • Winkler, D.A.1    Burden, F.R.2
  • 74
    • 33244467920 scopus 로고    scopus 로고
    • In silico prediction of blood brain barrier permeability: An artificial neural network model
    • Garg P, Verma J. In silico prediction of blood brain barrier permeability: an artificial neural network model. J Chem Inf Model 2006;46:289
    • (2006) J Chem Inf Model , vol.46 , pp. 289
    • Garg, P.1    Verma, J.2
  • 75
    • 70449389960 scopus 로고    scopus 로고
    • Classification of blood-brain barrier permeation by Kohonens Self-Organizing Neural Network (KohNN) and Support Vector Machine (SVM)
    • Wang Z, Yan A, Yuan Q. Classification of blood-brain barrier permeation by Kohonens Self-Organizing Neural Network (KohNN) and Support Vector Machine (SVM). QSAR Combi Sci 2009;28:989
    • (2009) QSAR Combi Sci , vol.28 , pp. 989
    • Wang, Z.1    Yan, A.2    Yuan, Q.3
  • 76
    • 33846892037 scopus 로고    scopus 로고
    • Predicting penetration across membrane from simple descriptors and fragmentation schemes
    • Zhao YH, Abraham MH, Ibrahim A, et al. Predicting penetration across membrane from simple descriptors and fragmentation schemes. J Chem Inf Model 2007;47:170
    • (2007) J Chem Inf Model , vol.47 , pp. 170
    • Zhao, Y.H.1    Abraham, M.H.2    Ibrahim, A.3
  • 77
    • 77954964981 scopus 로고    scopus 로고
    • Correlation of blood-brain penetration and human serum albumin binding with theoretical descriptors
    • Karelson M, Dobchev DA, Tamm T, et al. Correlation of blood-brain penetration and human serum albumin binding with theoretical descriptors. Arkivoc 2008;xvi:38
    • (2008) Arkivoc , vol.16 , pp. 38
    • Karelson, M.1    Dobchev, D.A.2    Tamm, T.3
  • 78
    • 0028239908 scopus 로고
    • The third helix of the Antennapedia homeodomain translocates through biological membranes
    • Derossi D, Joliot AH, Chassaing G, et al. The third helix of the Antennapedia homeodomain translocates through biological membranes. J Biol Chem 1994;8:10444
    • (1994) J Biol Chem , vol.8 , pp. 10444
    • Derossi, D.1    Joliot, A.H.2    Chassaing, G.3
  • 79
    • 0030904245 scopus 로고    scopus 로고
    • Truncated HIV-1 Tat protein basic domain rapidly translocates through the plasma membrane and accumulates in the cell nucleus
    • Vives E, Brodin P, Lebleu BA. Truncated HIV-1 Tat protein basic domain rapidly translocates through the plasma membrane and accumulates in the cell nucleus. J Biol Chem 1997;272:16010
    • (1997) J Biol Chem , vol.272 , pp. 16010
    • Vives, E.1    Brodin, P.2    Lebleu, B.A.3
  • 80
    • 39049130647 scopus 로고    scopus 로고
    • Cell-penetrating peptides for drug delivery across membrane barriers
    • Foged C, Nielsen HM. Cell-penetrating peptides for drug delivery across membrane barriers. Expert Opin Drug Deliv 2008;5:105
    • (2008) Expert Opin Drug Deliv , vol.5 , pp. 105
    • Foged, C.1    Nielsen, H.M.2
  • 81
    • 39149093340 scopus 로고    scopus 로고
    • Enhancing the cellular uptake of siRNA duplexes following noncovalent packaging with protein transduction domain peptides
    • Meade BR, Dowdy SF. Enhancing the cellular uptake of siRNA duplexes following noncovalent packaging with protein transduction domain peptides. Adv Drug Deliv Rev 2008;60:530
    • (2008) Adv Drug Deliv Rev , vol.60 , pp. 530
    • Meade, B.R.1    Dowdy, S.F.2
  • 82
    • 77953662145 scopus 로고    scopus 로고
    • Prediction of cell-penetrating peptides using artificial neural networks
    • Dobchev DA, Mager I, Tulp I, et al. Prediction of cell-penetrating peptides using artificial neural networks. Curr Comput Aided Drug Des 2010;6:79
    • (2010) Curr Comput Aided Drug des , vol.6 , pp. 79
    • Dobchev, D.A.1    Mager, I.2    Tulp, I.3
  • 84
    • 0345548661 scopus 로고    scopus 로고
    • Comparison of support vector machine and artificial neural network systems for drug/nondrug classification
    • Byvatov E, Fechner U, Sadovski J, et al. Comparison of support vector machine and artificial neural network systems for drug/nondrug classification. J Chem Inf Comput Sci 2003;43:1882
    • (2003) J Chem Inf Comput Sci , vol.43 , pp. 1882
    • Byvatov, E.1    Fechner, U.2    Sadovski, J.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.