A prediction model for blood-brain barrier permeation and analysis on its parameter biologically

Computer Methods and Programs in Biomedicine

Volumn 95, Issue 3, 2009, Pages 280-287

  Chen, Yan ^a,b   Zhu, Qing Jun ^b   Pan, Jian ^a   Yang, Yi ^a   Wu, Xiao Pei ^b  

^a HEFEI UNIVERSITY OF TECHNOLOGY   (China)

^b ANHUI UNIVERSITY   (China)

Author keywords

Blood brain barrier permeability; LogBB; Neural network models; Sensitivity analysis

Indexed keywords

ARTIFICIAL NEURAL NETWORK; BLOOD-BRAIN BARRIER; BLOOD-BRAIN BARRIER PERMEABILITY; CHEMICAL RESEARCH; DESCRIPTORS; HYDROGEN-BOND BASICITY; LOGBB; MOLECULAR DESCRIPTOR; NEURAL NETWORK MODELS; PLASMA PROTEIN BINDING; POLAR SURFACE AREAS; PREDICTION MODEL; RELIABLE MODELS; THREE-LAYER;

ALKALINITY; BACKPROPAGATION; BIOCHEMISTRY; BLOOD; BRAIN MODELS; CAPILLARITY; FEEDFORWARD NEURAL NETWORKS; HYDROGEN; MECHANICAL PERMEABILITY; NETWORK LAYERS;

SENSITIVITY ANALYSIS;

GENTISIC ACID; PLASMA PROTEIN; SALICYLURIC ACID;

ARTICLE; ARTIFICIAL NEURAL NETWORK; BLOOD BRAIN BARRIER; CHEMICAL STRUCTURE; ENDOTHELIUM CELL; HYDROGEN BOND; MEMBRANE PERMEABILITY; PASSIVE DIFFUSION; PASSIVE TRANSPORT; PREDICTION; PROBABILITY; PROTEIN BINDING; SENSITIVITY ANALYSIS; SURFACE CHARGE; THEORETICAL MODEL;

BLOOD PROTEINS; BLOOD-BRAIN BARRIER; COMPUTER SIMULATION; HUMANS; MODELS, CARDIOVASCULAR; MODELS, NEUROLOGICAL; NEURAL NETWORKS (COMPUTER); PERMEABILITY;

EID: 67649394120     PISSN: 01692607     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cmpb.2009.03.006     Document Type: Article

References (47)

1. Bickel U. How to measure drug transport across the blood-brain barrier. NeuroRX 2 (2005) 15-26
2. Abraham M.H. The factors that influence permeation across the blood-brain barrier. Eur. J. Med. Chem. 39 (2004) 235-240
3. Liu X., Tu M., Kelly R.S., Chen C., and Smith B.J. Development of a computational approach to predict blood-brain barrier permeability. Drug. Metab. Dispos. 32 (2004) 132-139
4. Young R.C., Mitchell R.C., Brown T.H., Ganellin C.R., Griffiths R., Jones M., Rana K.K., Saunders D., Smith I.R., Sore N.E., and Wilks T.J. Development of a new physicochemical model for brain penetration and its application to the design of centrally acting H2 receptor histamine antagonists. J. Med. Chem. 31 (1988) 656-671
5. van de Waterbeemd H., and Kansy M. Hydrogen-bonding capacity and brain penetration. Chimia 46 (1992) 299-303
6. Abraham M.H. Scales of solute hydrogen-bonding: their construction and application to physicochemical and biochemical process. Chem. Soc. Rev. 22 (1993) 73-83
7. Abraham M.H., Takacs-Novak K., and Mitchell R.C. On the partitioning of ampholytes: application to blood-brain distribution. J. Pharm. Sci. 86 (1997) 310-315
8. Platts J.A., Abraham M.H., Zhao Y.H., Ijaz A.H.L., and Butina D. Correlation and prediction of a large blood-brain distribution data set-an LFER study. Eur. J. Med. Chem. 36 (2001) 719-730
9. Lombardo F., Blake J.F., and Curatolo W.J. Computation of brain-blood partitioning of organic solutes via free energy calculations. J. Med. Chem. 39 (1996) 4750-4755
10. Norinder U., and Haeberlein M. Computational approaches to the prediction of the blood-brain distribution. Adv. Drug Deliv. Rev. 54 (2004) 291-313
11. Oesterberg T., and Norinder U. Prediction of polar area and drug transport process using simple parameters and PLS statistics. J. Chem. Inf. Comput. Sci. 40 (2000) 1408-1411
12. Garg P., and Verma J. In silico prediction of blood brain barrier permeability: an artificial neural network model. J. Chem. Inf. Model 46 (2006) 289-297
13. Abraham M.H., Poole C.F., and Poole S.K. Classification of stationary phases and other materials by gas chromatography. J. Chromatogr. A 842 (1999) 79-114
14. Abraham M.H., Ibrahim A., and Zissimos A.M. Determination of sets of solute descriptors from chromatographic measurements. J. Chromatogr. A 1037 (2004) 29-37
15. Feng M.R. Assessment of blood-brain barrier penetration: in silico, in vitro and in vivo. Curr. Drug. Metab. 3 (2002) 647-657
16. Fu X.C., Wang G.P., Liang W.Q., and Yu Q.S. Predicting blood-brain barrier penetration of drugs using an artificial neural network. Pharmazie 59 (2004) 126-130
17. Yap C.W., and Chen Y.Z. Quantitative structure-pharmacokinetic relationships for drug distribution properties by using general regression neural network. J. Pharm. Sci. 94 (2005) 153-168
18. Clark D.E. Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. 2. Prediction of blood-brain barrier penetration. J. Pharm. Sci. 88 (1999) 815-821
19. Kelder J., Grootenhuis P.D.J., Bayada D.M., Delbressine L.P.C., and Ploemen J.P. Polar molecular surface area as a dominating determinant for oral absorption and brain permeation of drugs. Pharm. Res. 16 (1999) 1514-1519
20. van de Waterbeemd H., Camenisch G., Folkers G., Chretien J.R., and Raevsky O.A. Estimation of blood-brain barrier crossing of drugs using molecular size and shape, and H-bonding descriptors. J. Drug. Target 6 (1998) 151-165
21. Waterhouse R.N. Determination of lipophilicity and its use as a predictor of blood-brain barrier penetration of molecular imaging agents. Mol. Imaging Biol. 5 (2003) 376-389
22. Higgins C.F., and Gottesman M.M. Is the multidrug transporter a flippase?. Trends. Biol. Sci. 17 (1992) 18-21
23. Ramakrishnan P. The role of P-glycoprotein in the blood-brain barrier. Einstein Q. J. Biol. Med. 19 (2003) 160-165
24. Schinkel A.H., Smit J.J.M., van Tellingen O., Beijnen J.H., Wagenaar E., van Deemter L., et al. Disruption of the mouse mdrla Pglycoprotein gene leads to a deficiency in the blood-brain barrier and to increased sensitivity to drugs. Cell 77 (1994) 491-502
25. Beaulieu E., Demeule M., and Ghitescu L. P-glycoprotein is strongly expressed in the luminal membranes of the endothelium of blood vessels in the brain. Biochem. J. 326 (1997) 539-544
26. Fardel O., Lecureur V., and Gullouzo A. The P-Glycoprotein multidrug transporter. Gen. Pharmacol. 27 (1996) 1283-1291
27. Loetchutinat C., Saengkhae C., Marbeuf-Gueye C., and Garnier-Suillerot A. New insights into the P-glycoprotein-mediated effluxes of rhodamines. Eur. J. Biochem. 270 (2003) 476-485
28. Ambudkarl S.V., Kimchi-Sarfatyl C., Saunal Z.E., and Gottesman M.M. P-glycoprotein: from genomics to mechanism. Oncogene 22 (2003) 7468-7485
29. du Souich P., Verges J., and Erill S. Plasma protein binding and pharmacological response. Clin. Pharmacokinet. 24 (1993) 435-440
30. Kragh-Hansen U. Molecular aspects of lignds binding to serum albumin. Pharmacol. Rev. 33 (1981) 17-53
31. Kremer J.M., Wilting J., and Janssen L.H. Drug binding to human alpha-1-acid glycoprotein in the health and disease. Pharmacol. Rev. 40 (1988) 1-47
32. Riant P., Urien S., and Albengres E. Effects of the binding of imipramine to erythrocytes and plasma proteins on its transport through the rat blood brain barrier. J. Neurochem. 51 (1988) 421-425
33. Qin M., Nilsson M., and Oie S. Decreased elimination of the drug in the presence of alpha-1-acid glycoprotein is related to a reduced hepatocyte uptake. J. Pharmacol. Exp. Ther. 269 (1994) 1176-1181
34. Weisiger R., Gollan J., and Ockner R. Receptor for albumin on the liver cell surface may mediate uptake of fatty acids and other albumin-bound substances. Science 211 (1981) 1048-1051
35. Reed R.G., and Burrington C.M. The albumin receptors effect may be due to a surface-induced conformational change in albumin. J. Biol. Chem. 264 (1989) 9867-9872
36. Kang Y.S., and Pardridge W.M. Brain delivery of biotin bound to a conjugate of neutral avidin and cationized human albumin. Pharm. Res. 11 (1994) 1257-1264
37. Lu W., Zhang Y., Tan Y.Z., Hu K.L., Jiang X.G., and Fu S.K. Cationic albumin-conjugated pegylated nanoparticles as novel drug carrier for brain delivery. J. Control. Release 107 (2005) 428-448
38. dos Santos W.L., Rahman J., Klein N., and Male D.K. Distribution and analysis of surface charge on brain endothelium in vitro and in situ. Acta Neuropathol. 90 (1995) 305-311
39. Pajouhesh H., and Lenz G.R. Medicinal chemical properties of successful central nervous system drugs. NeuroRX 2 (2005) 541-553
40. Clark D.E. In silico prediction of blood-brain barrier permeation. Drug Discov. Today 8 (2003) 927-933
41. Fischer H., Gottschlich R., and Seelig A. Blood-brain barrier permeation: molecular parameters governing passive diffusion. J. Membr. Biol. 165 (1998) 201-211
42. Sahagun G., Moore S.A., and Hart M.N. Permeability of neutral vs. anionic dextrans in cultured brain microvascular endothelium. Am. J. Physiol. l259 (1990) 162-166
43. Kaznessis Y.N., Snow M.E., and Blankley C.J. Prediction of blood-brain partitioning using Monte Carlo simulations of molecules in water. J. Comput. Aided. Mol. Des. 15 (2001) 697-708
44. Hou T.J., and Xu X.J. ADME evaluation in drug discovery. 3. Modeling blood-brain barrier partitioning using simple molecular descriptors. J. Chem. Inf. Comput. Sci. 43 (2003) 2137-2152
45. Levin V.A. Relationship of octanol/water partition coefficient and molecular weight to rat brain capillary permeability. J. Med. Chem. 23 (1980) 682-684
46. van de waterbeemd F., Alkinson S., Cole C., and Green. Lipophilicity and other parameters affecting brain penetration. Curr. Med. Chem.-Cent. Nerv. Syst. Agents 2 (2002) 229-340
47. Lipinski C.A., Lombardo F., Dominy B.W., and Feeney P.J. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 23 (1997) 4-25