Structure – ADME relationship : still a long way to go ?

BACKGROUND Theoretical models for predicting absorption, distribution, metabolism and excretion (ADME) properties play increasingly important roles in support of the drug development process. OBJECTIVE We briefly review the in silico prediction models for three important ADME properties, namely, aqueous solubility, human intestinal absorption, and oral bioavailability. METHODS Rather than giving detailed descriptions of the ADME prediction models, we focus on the discussions of the prediction accuracies of the in silico models. RESULTS/CONCLUSION We find that the robustness and predictive capability of the ADME models are directly associated with the complexity of the ADME property. For the ADME properties involving complex phenomena, such as bioavailability, the in silico models usually cannot give satisfactory predictions. Moreover, the lack of large and high-quality data sets also greatly hinder the reliability of ADME predictions. While considerable progress has been achieved in ADME predictions, many challenges remain to be overcome.

[1]  A. Li,et al.  Screening for human ADME/Tox drug properties in drug discovery. , 2001, Drug discovery today.

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

[3]  Timothy Clark,et al.  In Silico Prediction of Buffer Solubility Based on Quantum-Mechanical and HQSAR- and Topology-Based Descriptors , 2006, J. Chem. Inf. Model..

[4]  I. Kola,et al.  Can the pharmaceutical industry reduce attrition rates? , 2004, Nature Reviews Drug Discovery.

[5]  Ola Engkvist,et al.  High-Throughput, In Silico Prediction of Aqueous Solubility Based on One- and Two-Dimensional Descriptors , 2002, J. Chem. Inf. Comput. Sci..

[6]  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.

[7]  Tingjun Hou,et al.  ADME Evaluation in Drug Discovery, 8. The Prediction of Human Intestinal Absorption by a Support Vector Machine , 2007, J. Chem. Inf. Model..

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

[9]  Shaomeng Wang,et al.  Estimation of aqueous solubility of organic molecules by the group contribution approach. Application to the study of biodegradation , 1992, J. Chem. Inf. Comput. Sci..

[10]  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.

[11]  H. van de Waterbeemd,et al.  ADMET in silico modelling: towards prediction paradise? , 2003, Nature reviews. Drug discovery.

[12]  J. Delaney Predicting aqueous solubility from structure. , 2005, Drug discovery today.

[13]  Tingjun Hou,et al.  Recent development and application of virtual screening in drug discovery: an overview. , 2004, Current pharmaceutical design.

[14]  R E Speece,et al.  Prediction of aqueous solubility of organic chemicals based on molecular structure. , 1988, Environmental science & technology.

[15]  Jorge A. Marrero,et al.  Group-Contribution-Based Estimation of Octanol/Water Partition Coefficient and Aqueous Solubility , 2002 .

[16]  Takahiro Suzuki,et al.  Development of an automatic estimation system for both the partition coefficient and aqueous solubility , 1991, J. Comput. Aided Mol. Des..

[17]  B. W. Penman,et al.  Microtiter plate assays for inhibition of human, drug-metabolizing cytochromes P450. , 1997, Analytical biochemistry.

[18]  J. Topliss,et al.  QSAR model for drug human oral bioavailability. , 2000, Journal of medicinal chemistry.

[19]  Johann Gasteiger,et al.  Prediction of Aqueous Solubility of Organic Compounds Based on a 3D Structure Representation , 2003, J. Chem. Inf. Comput. Sci..

[20]  L. Wienkers,et al.  Predicting in vivo drug interactions from in vitro drug discovery data , 2005, Nature Reviews Drug Discovery.

[21]  Joelle M. R. Gola,et al.  Focus on success: using a probabilistic approach to achieve an optimal balance of compound properties in drug discovery , 2006, Expert opinion on drug metabolism & toxicology.

[22]  James W. McFarland,et al.  Estimating the Water Solubilities of Crystalline Compounds from Their Chemical Structures Alone , 2001, J. Chem. Inf. Comput. Sci..

[23]  Tingjun Hou,et al.  Development of Reliable Aqueous Solubility Models and Their Application in Druglike Analysis , 2007, J. Chem. Inf. Model..

[24]  Søren Brunak,et al.  Prediction of pH-Dependent Aqueous Solubility of Druglike Molecules , 2006, J. Chem. Inf. Model..

[25]  Peter C. Jurs,et al.  Prediction of Aqueous Solubility of Heteroatom‐Containing Organic Compounds from Molecular Structure. , 2001 .

[26]  U. Fagerholm Prediction of human pharmacokinetics —gastrointestinal absorption , 2007, The Journal of pharmacy and pharmacology.

[27]  W. L. Jorgensen,et al.  Prediction of drug solubility from structure. , 2002, Advanced drug delivery reviews.

[28]  M. Abraham,et al.  The correlation and prediction of the solubility of compounds in water using an amended solvation energy relationship. , 1999, Journal of pharmaceutical sciences.

[29]  P. Carrupt,et al.  Molecular fields in quantitative structure–permeation relationships: the VolSurf approach , 2000 .

[30]  Darko Butina,et al.  Modeling Aqueous Solubility , 2003, J. Chem. Inf. Comput. Sci..

[31]  Tingjun Hou,et al.  ADME evaluation in drug discovery , 2002, Journal of molecular modeling.

[32]  Sean Ekins,et al.  Methods for predicting human drug metabolism. , 2007, Advances in clinical chemistry.

[33]  Junmei Wang,et al.  Genetic Algorithm-Optimized QSPR Models for Bioavailability, Protein Binding, and Urinary Excretion , 2006, J. Chem. Inf. Model..

[34]  P Chiba,et al.  Future directions for drug transporter modelling , 2007, Xenobiotica; the fate of foreign compounds in biological systems.

[35]  D. Leifer Still a long way to go. , 1994, Nursing standard (Royal College of Nursing (Great Britain) : 1987).

[36]  Mehran Yazdanian,et al.  The “High Solubility” Definition of the Current FDA Guidance on Biopharmaceutical Classification System May Be Too Strict for Acidic Drugs , 2004, Pharmaceutical Research.

[37]  Yi Li,et al.  In silico ADME/Tox: why models fail , 2003, J. Comput. Aided Mol. Des..

[38]  Stephen R. Johnson,et al.  Recent progress in the computational prediction of aqueous solubility and absorption , 2006, The AAPS Journal.

[39]  Tingjun Hou,et al.  ADME Evaluation in Drug Discovery, 6. Can Oral Bioavailability in Humans Be Effectively Predicted by Simple Molecular Property-Based Rules? , 2007, J. Chem. Inf. Model..

[40]  Ruifeng Liu,et al.  Development of Quantitative Structure-Property Relationship Models for Early ADME Evaluation in Drug Discovery. 2. Blood-Brain Barrier Penetration , 2001, J. Chem. Inf. Comput. Sci..

[41]  Philip H. Howard,et al.  Estimating log P with atom/fragments and water solubility with log P , 2000 .

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

[43]  S. Yalkowsky,et al.  Estimation of the aqueous solubility I: application to organic nonelectrolytes. , 2001, Journal of pharmaceutical sciences.

[44]  W L Jorgensen,et al.  Prediction of drug solubility from Monte Carlo simulations. , 2000, Bioorganic & medicinal chemistry letters.

[45]  Joseph V. Turner,et al.  Prediction of drug bioavailability based on molecular structure , 2003 .

[46]  Wei Zhang,et al.  Recent advances in computational prediction of drug absorption and permeability in drug discovery. , 2006, Current medicinal chemistry.

[47]  T Abshear,et al.  A model validation and consensus building environment , 2006, SAR and QSAR in environmental research.

[48]  Ulf Norinder,et al.  Prediction of ADMET Properties , 2006, ChemMedChem.

[49]  S. Yalkowsky,et al.  Solubility and partitioning I: Solubility of nonelectrolytes in water. , 1980, Journal of pharmaceutical sciences.

[50]  Lawrence X. Yu,et al.  Predicting Human Oral Bioavailability of a Compound: Development of a Novel Quantitative Structure-Bioavailability Relationship , 2000, Pharmaceutical Research.

[51]  C. Bevan,et al.  A high-throughput screening method for the determination of aqueous drug solubility using laser nephelometry in microtiter plates. , 2000, Analytical chemistry.

[52]  U. Fagerholm Evaluation and suggested improvements of the Biopharmaceutics Classification System (BCS) , 2007, The Journal of pharmacy and pharmacology.

[53]  Matthew D. Segall,et al.  ADMET Property Prediction: The State of the Art and Current Challenges , 2006 .

[54]  J. Huuskonen,et al.  Estimation of water solubility from atom‐type electrotopological state indices , 2001, Environmental toxicology and chemistry.

[55]  Tingjun Hou,et al.  ADME Evaluation in Drug Discovery. 4. Prediction of Aqueous Solubility Based on Atom Contribution Approach , 2004, J. Chem. Inf. Model..

[56]  G. Grass,et al.  Effect of diverse datasets on the predictive capability of ADME models in drug discovery , 2001 .

[57]  T. Kennedy Managing the drug discovery/development interface , 1997 .

[58]  Jyrki Taskinen,et al.  Aqueous Solubility Prediction of Drugs Based on Molecular Topology and Neural Network Modeling , 1998, J. Chem. Inf. Comput. Sci..

[59]  A. Beresford,et al.  The emerging importance of predictive ADME simulation in drug discovery. , 2002, Drug discovery today.

[60]  Thierry Lavé,et al.  An evaluation of the utility of physiologically based models of pharmacokinetics in early drug discovery. , 2005, Journal of pharmaceutical sciences.

[61]  Igor V. Tetko,et al.  Estimation of Aqueous Solubility of Chemical Compounds Using E-State Indices , 2001, J. Chem. Inf. Comput. Sci..

[62]  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..

[63]  Ralph Kühne,et al.  Model Selection Based on Structural Similarity-Method Description and Application to Water Solubility Prediction , 2006, J. Chem. Inf. Model..

[64]  David Raunig,et al.  In vitro drug interactions of cytochrome p450: an evaluation of fluorogenic to conventional substrates. , 2003, Drug metabolism and disposition: the biological fate of chemicals.

[65]  Samuel H. Yalkowsky,et al.  Comment on “Prediction of Aqueous Solubility of Organic Chemicals Based on Molecular Structure. 2. Application to PNAs, PCBs, PCDDs, etc.” , 1989 .

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

[67]  Hao Zhu,et al.  Estimation of the Aqueous Solubility of Organic Molecules by the Group Contribution Approach , 2001, J. Chem. Inf. Comput. Sci..

[68]  M. Kansy,et al.  Hydrogen-Bonding Capacity and Brain Penetration , 1992, Chimia (Basel).