Modeling Blood-Brain Barrier Partitioning Using the Electrotopological State

The challenging problem of modeling blood-brain barrier partitioning is approached through topological representation of molecular structure. A QSAR model is developed for in vivo blood-brain partitioning data treated as the logarithm of the blood-brain concentration ratio. The model consists of three structure descriptors: the hydrogen E-State index for hydrogen bond donors, HS(T)(HBd); the hydrogen E-State index for aromatic CHs, HS(T)(arom); and the second order difference valence molecular connectivity index, d(2)chi(v) (q(2) = 0.62.) The model for the set of 106 compounds is validated through use of an external validation test set (20 compounds of the 106, MAE = 0.33, rms = 0.38), 5-fold cross-validation (MAE = 0.38, rms = 0.47), prediction of +/- values for an external test set (27/28 correct), and estimation of logBB values for a large data set of 20 039 drugs and drug-like compounds. Because no 3D structure information is used, computation of logBB by the model is very fast. The quality of the validation statistics supports the claim that the model may be used for estimation of logBB values for drug and drug-like molecules. Detailed structure interpretation is given for the structure indices in the model. The model indicates that molecules that penetrate the blood-brain barrier have large HS(T)(arom) values (presence of aromatic groups) but small values of HS(T)(HBd) (fewer or weaker H-Bond donors) and smaller d(2)chi(v) values (less branched molecules with fewer electronegative atoms). These three structure descriptors encode influence of molecular context of groups as well as counts of those groups.

[1]  F. Lombardo,et al.  Computation of brain-blood partitioning of organic solutes via free energy calculations. , 1996, Journal of medicinal chemistry.

[2]  Harpreet S. Chadha,et al.  Hydrogen bonding. 33. Factors that influence the distribution of solutes between blood and brain. , 1994, Journal of pharmaceutical sciences.

[3]  Lowell H. Hall,et al.  Modeling Antileukemic Activity of Carboquinones with Electrotopological State and Chi Indices , 1999, J. Chem. Inf. Comput. Sci..

[4]  D. E. Clark,et al.  Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. 2. Prediction of blood-brain barrier penetration. , 1999, Journal of pharmaceutical sciences.

[5]  M Macka,et al.  Decomposition of cisplatin in aqueous solutions containing chlorides by ultrasonic energy and light. , 1994, Journal of pharmaceutical sciences.

[6]  J. Taskinen,et al.  Relationship between immobilised artificial membrane chromatographic retention and the brain penetration of structurally diverse drugs. , 1997, Journal of pharmaceutical and biomedical analysis.

[7]  L B Kier,et al.  Database Organization and Searching with E-State Indices , 2001, SAR and QSAR in environmental research.

[8]  C R Ganellin,et al.  Predicting the brain-penetrating capability of histaminergic compounds. , 1994, Drug design and discovery.

[9]  György M. Keserü,et al.  High-throughput prediction of blood-brain partitioning: a thermodynamic approach. , 2001, Journal of chemical information and computer sciences.

[10]  Juan M. Luco,et al.  Prediction of the Brain-Blood Distribution of a Large Set of Drugs from Structurally Derived Descriptors Using Partial Least-Squares (PLS) Modeling , 1999, J. Chem. Inf. Comput. Sci..

[11]  Lowell H. Hall,et al.  Modeling the toxicity of amide herbicides using the electrotopological state , 1999 .

[12]  J J Baldwin,et al.  Application of the three-dimensional structures of protein target molecules in structure-based drug design. , 1994, Journal of medicinal chemistry.

[13]  R Griffiths,et al.  Development of a new physicochemical model for brain penetration and its application to the design of centrally acting H2 receptor histamine antagonists. , 1988, Journal of medicinal chemistry.

[14]  M. Yazdanian,et al.  In vitro blood-brain barrier permeability of nevirapine compared to other HIV antiretroviral agents. , 1998, Journal of pharmaceutical sciences.

[15]  B Testa,et al.  Predicting blood-brain barrier permeation from three-dimensional molecular structure. , 2000, Journal of medicinal chemistry.

[16]  J. Gálvez,et al.  Molecular search of new active drugs against Toxoplasma gondii. , 1999, SAR and QSAR in environmental research.

[17]  Lowell H. Hall,et al.  E-State Modeling of HIV-1 Protease Inhibitor Binding Independent of 3D Information , 2002, J. Chem. Inf. Comput. Sci..

[18]  Jarmo Huuskonen,et al.  Estimation of Aqueous Solubility for a Diverse Set of Organic Compounds Based on Molecular Topology , 2000, J. Chem. Inf. Comput. Sci..

[19]  Lemont B. Kier,et al.  Molecular Similarity Based on Novel Atom-Type Electrotopological State Indices , 1995, J. Chem. Inf. Comput. Sci..

[20]  Lemont B. Kier,et al.  Comparison of electrotopological state indexes with molecular orbital parameters : inhibition of MAO by hydrazides , 1993 .

[21]  Peter C. Jurs,et al.  Prediction of IC50 Values for ACAT Inhibitors from Molecular Structure , 2000, J. Chem. Inf. Comput. Sci..

[22]  L B Kier,et al.  Molecular connectivity: intermolecular accessibility and encounter simulation. , 2001, Journal of molecular graphics & modelling.

[23]  Lowell H. Hall,et al.  E-State Modeling of Corticosteroids Binding AffinityValidation of Model for Small Data Set , 2001, J. Chem. Inf. Comput. Sci..

[24]  Lemont B. Kier,et al.  Intermolecular Accessibility: The Meaning of Molecular Connectivity , 2000, J. Chem. Inf. Comput. Sci..

[25]  Lemont B. Kier,et al.  Electrotopological State Indices for Atom Types: A Novel Combination of Electronic, Topological, and Valence State Information , 1995, J. Chem. Inf. Comput. Sci..

[26]  Lowell H. Hall,et al.  E-State Modeling of Dopamine Transporter Binding. Validation of the Model for a Small Data Set , 2000, J. Chem. Inf. Comput. Sci..

[27]  Lemont B. Kier,et al.  The E-State as the Basis for Molecular Structure Space Definition and Structure Similarity , 2000, J. Chem. Inf. Comput. Sci..

[28]  Jarmo Huuskonen.  QSAR Modeling with the Electrotopological State: TIBO Derivatives , 2001, J. Chem. Inf. Comput. Sci..