A bioavailability score.

Responding to a demonstrated need for scientists to forecast the permeability and bioavailability (F) properties of compounds before their purchase, synthesis, or advanced testing, we have developed a score that assigns the probability that a compound will have F > 10% in the rat. Neither the rule-of-five, log P, log D, nor the combination of the number of rotatable bonds and polar surface area successfully categorized compounds. Instead, different properties govern the bioavailability of compounds depending on their predominant charge at biological pH. The fraction of anions with >10% F falls from 85% if the polar surface area (PSA) is < or = 75 A(2), to 56% if 75 < PSA < 150 A(2), to 11% if PSA is > or = 150 A(2). On the other hand, whereas 55% of the neutral, zwitterionic, or cationic compounds that pass the rule-of-five have >10% F, only 17% of those that fail have > 10% F. This same categorization distinguishes compounds that are poorly permeable from those that are permeable in Caco-2 cells. Further validation is provided with human bioavailability values from the literature.

[1]  J J Baldwin,et al.  Prediction of drug absorption using multivariate statistics. , 2000, Journal of medicinal chemistry.

[2]  Tudor I. Oprea,et al.  Pharmacokinetically based mapping device for chemical space navigation. , 2002, Journal of combinatorial chemistry.

[3]  Robert D. Clark,et al.  Predicting drug pharmacokinetic properties using molecular interaction fields and SIMCA , 2003, J. Comput. Aided Mol. Des..

[4]  William J Egan,et al.  Prediction of intestinal permeability. , 2002, Advanced drug delivery reviews.

[5]  Herbert F. Spirer,et al.  Misused Statistics: Straight Talk for Twisted Numbers , 1988 .

[6]  Kristina Luthman,et al.  Prediction of Membrane Permeability to Peptides from Calculated Dynamic Molecular Surface Properties , 1999, Pharmaceutical Research.

[7]  R. Borchardt,et al.  How structural features influence the biomembrane permeability of peptides. , 1996, Journal of pharmaceutical sciences.

[8]  F. Lombardo,et al.  Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. , 2001, Advanced drug delivery reviews.

[9]  P. Kovar,et al.  Studies directed toward the design of orally active renin inhibitors. 2. Development of the efficacious, bioavailable renin inhibitor (2S)-2-benzyl-3- [[(1-methylpiperazin-4-yl)sulfonyl]propionyl]-3-thiazol-4-yl-L-alanine amide of (2S,3R,4S)-2-amino-1-cyclohexyl-3,4-dihydroxy-6-methylheptane (A-7251 , 1993, Journal of medicinal chemistry.

[10]  Y. Martin,et al.  Do structurally similar molecules have similar biological activity? , 2002, Journal of medicinal chemistry.

[11]  G Folkers,et al.  Shapes of membrane permeability-lipophilicity curves: extension of theoretical models with an aqueous pore pathway. , 1998, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.

[12]  V Ganapathy,et al.  Improvement of L-dopa absorption by dipeptidyl derivation, utilizing peptide transporter PepT1. , 1998, Journal of pharmaceutical sciences.

[13]  G. Granneman,et al.  Use of In Vitro and In Vivo Data to Estimate the Likelihood of Metabolic Pharmacokinetic Interactions , 1997, Clinical pharmacokinetics.

[14]  M. Feher,et al.  A simple model for the prediction of blood-brain partitioning. , 2000, International journal of pharmaceutics.

[15]  Thomas J. Vidmar,et al.  A non-aqueous partitioning system for predicting the oral absorption potential of peptides , 1994 .

[16]  Ulf Norinder,et al.  Theoretical Calculation and Prediction of Caco-2 Cell Permeability Using MolSurf Parametrization and PLS Statistics , 1997, Pharmaceutical Research.

[17]  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.

[18]  Stephen R. Johnson,et al.  Molecular properties that influence the oral bioavailability of drug candidates. , 2002, Journal of medicinal chemistry.

[19]  P. Artursson,et al.  Correlation between oral drug absorption in humans and apparent drug permeability coefficients in human intestinal epithelial (Caco-2) cells. , 1991, Biochemical and biophysical research communications.

[20]  Kristina Luthman,et al.  Polar Molecular Surface Properties Predict the Intestinal Absorption of Drugs in Humans , 1997, Pharmaceutical Research.

[21]  Pravin Chaturvedi,et al.  Design principles for orally bioavailable drugs , 1996 .

[22]  Thomas J. Raub,et al.  Increased lipophilicity and subsequent cell partitioning decrease passive transcellular diffusion of novel, highly lipophilic antioxidants. , 1999, The Journal of pharmacology and experimental therapeutics.

[23]  D. E. Clark,et al.  Prediction of intestinal absorption and blood-brain barrier penetration by computational methods. , 2001, Combinatorial chemistry & high throughput screening.

[24]  M Pastor,et al.  VolSurf: a new tool for the pharmacokinetic optimization of lead compounds. , 2000, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.

[25]  D. E. Clark Rapid calculation of polar molecular surface area and its application to the prediction of transport phenomena. 1. Prediction of intestinal absorption. , 1999, Journal of pharmaceutical sciences.

[26]  S. Vasavanonda,et al.  Antiviral and pharmacokinetic properties of C2 symmetric inhibitors of the human immunodeficiency virus type 1 protease , 1991, Antimicrobial Agents and Chemotherapy.

[27]  U. Norinder,et al.  Computational approaches to the prediction of the blood-brain distribution. , 2002, Advanced drug delivery reviews.

[28]  K Gubernator,et al.  Physicochemical high throughput screening: parallel artificial membrane permeation assay in the description of passive absorption processes. , 1998, Journal of medicinal chemistry.

[29]  John G. Topliss,et al.  QSAR Model for Drug Human Oral Bioavailability1 , 2000 .

[30]  I Moriguchi,et al.  Non-congeneric structure-pharmacokinetic property correlation studies using fuzzy adaptive least-squares: oral bioavailability. , 1994, Biological & pharmaceutical bulletin.

[31]  G Beck,et al.  Evaluation of human intestinal absorption data and subsequent derivation of a quantitative structure-activity relationship (QSAR) with the Abraham descriptors. , 2001, Journal of pharmaceutical sciences.

[32]  Peter C. Jurs,et al.  Prediction of Human Intestinal Absorption of Drug Compounds from Molecular Structure , 1998, J. Chem. Inf. Comput. Sci..

[33]  U Norinder,et al.  Theoretical calculation and prediction of intestinal absorption of drugs in humans using MolSurf parametrization and PLS statistics. , 1999, European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences.

[34]  K. Luthman,et al.  Correlation of drug absorption with molecular surface properties. , 1996, Journal of pharmaceutical sciences.