Early ADME/T Predictions: Toy or Tool?
Abstract
The successful development of new drugs critically depends on the ability of researchers to predict the ADME/T (absorption, distribution, metabolism, excretion, and toxicity) properties of chemical compounds. These properties are important to narrow the search for New promising Chemical Entities (NC...
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Traditionally, QSARs and other small-molecule property ML models use chemical structures as input, often encoded as SMILES.
“Traditionally, QSARs and other small-molecule property ML models use chemical structures as input, often encoded as SMILES (Simplified Molecular Input Line Entry System) (88).”
From Artificial Intelligence for Drug Discovery: Are We There Yet? (2024) · cites this paper as [88]
Cites
Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (2001) · Advanced Drug Delivery Reviews · doi:10.1016/s0169-409x(00)00129-0 · Cited by 18,139 · see citing works
Lipinski, C. A., Lombardo, F., Dominy, B. W., & Feeney, P. J. (1997) · Advanced Drug Delivery Reviews · doi:10.1016/s0169-409x(96)00423-1 · Cited by 11,484 · see citing works
Drug-like properties and the causes of poor solubility and poor permeability
Lipinski, C. A. (2000) · Journal of Pharmacological and Toxicological Methods · doi:10.1016/s1056-8719(00)00107-6 · Cited by 3,776 · see citing works
Tropsha, A., Gramatica, P., & Gombar, V. K. (2003) · QSAR & Combinatorial Science · doi:10.1002/qsar.200390007 · Cited by 2,195 · see citing works
Artursson, P., & Karlsson, J. E. (1991) · Biochemical and Biophysical Research Communications · doi:10.1016/0006-291x(91)91647-u · Cited by 1,899 · see citing works
ADMET in silico modelling: towards prediction paradise?
Waterbeemd, H. V. D., & Gifford, E. (2003) · Nature Reviews Drug Discovery · doi:10.1038/nrd1032 · Cited by 1,894 · see citing works
Artursson, P., Palm, K., & Luthman, K. (2001) · Advanced Drug Delivery Reviews · doi:10.1016/s0169-409x(00)00128-9 · Cited by 1,549 · see citing works
Virtual Computational Chemistry Laboratory – Design and Description
Tetko, I. V., Gasteiger, J., Todeschini, R., Mauri, A., Livingstone, D. J., Ertl, P., Palyulin, V. A., Radchenko, E. V., Zefirov, N. S., Makarenko, A. S., et al. (2005) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-005-8694-y · Cited by 1,504 · see citing works
Self-citationEriksson, L., Jaworska, J., Worth, A. P., Cronin, M. T. D., McDowell, R. M., & Gramatica, P. (2003) · Environmental Health Perspectives · doi:10.1289/ehp.5758 · Cited by 1,325 · see citing works
HANSCH, C., MALONEY, P. P., FUJITA, T., & MUIR, R. M. (1962) · Nature · doi:10.1038/194178b0 · Cited by 1,056 · see citing works
Martin, Y. C. (2005) · Journal of Medicinal Chemistry · doi:10.1021/jm0492002 · Cited by 1,042 · see citing works
MDCK (Madin-Darby Canine Kidney) Cells: A Tool for Membrane Permeability Screening
Irvine, J. D., Takahashi, L. H., Lockhart, K., Cheong, J., Tolan, J. W., Selick, H. E., & Grove, J. R. (1999) · Journal of Pharmaceutical Sciences · doi:10.1021/js9803205 · Cited by 984 · see citing works
Generation of a Set of Simple, Interpretable ADMET Rules of Thumb
Gleeson, M. P. (2008) · Journal of Medicinal Chemistry · doi:10.1021/jm701122q · Cited by 973 · see citing works
Are Crystal Structures Predictable?
Gavezzotti, A. (1994) · Accounts of Chemical Research · doi:10.1021/ar00046a004 · Cited by 922 · see citing works
Estimating The Cost Of New Drug Development: Is It Really $802 Million?
Adams, C., & Brantner, V. V. (2006) · Health Affairs · doi:10.1377/hlthaff.25.2.420 · Cited by 917 · see citing works
Molecular Complexity and Its Impact on the Probability of Finding Leads for Drug Discovery
Hann, M. M., Leach, A. R., & Harper, G. (2001) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci000403i · Cited by 882 · see citing works
Atom/Fragment Contribution Method for Estimating Octanol–Water Partition Coefficients
Meylan, W. M., & Howard, P. H. (1995) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.2600840120 · Cited by 862 · see citing works
Netzeva, T. I., Worth, A. P., Aldenberg, T., Benigni, R., Cronin, M., Gramatica, P., Jaworska, J. S., Kahn, S. D., Klopman, G., Marchant, C. A., et al. (2005) · Alternatives to Laboratory Animals · doi:10.1177/026119290503300209 · Cited by 840 · see citing works
The Role of ABC Transporters in Clinical Practice
Leonard, G. D., Fojo, T., & Bates, S. E. (2003) · The Oncologist · doi:10.1634/theoncologist.8-5-411 · Cited by 819 · see citing works
Is There a Difference between Leads and Drugs? A Historical Perspective
Oprea, T. I., Davis, A. M., Teague, S. J., & Leeson, P. D. (2001) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci010366a · Cited by 776 · see citing works
Self-citationCalculating log Poct from structures
Leo, A. J. (1993) · Chemical Reviews · doi:10.1021/cr00020a001 · Cited by 705 · see citing works
QSAR Applicability Domain Estimation by Projection of the Training Set in Descriptor Space: A Review
Jaworska, J. S., Nikolova-Jeliazkova, N., & Aldenberg, T. (2005) · Alternatives to Laboratory Animals · doi:10.1177/026119290503300508 · Cited by 685 · see citing works
Application of Associative Neural Networks for Prediction of Lipophilicity in ALOGPS 2.1 Program
Tetko, I. V., & Tanchuk, V. Y. (2002) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci025515j · Cited by 618 · see citing works
Self-citationCrystal structures of drugs: advances in determination, prediction and engineering
Datta, S., & Grant, D. J. W. (2004) · Nature Reviews Drug Discovery · doi:10.1038/nrd1280 · Cited by 583 · see citing works
Solubility and partitioning I: Solubility of nonelectrolytes in water
Yalkowsky, S. H., & Valvani, S. C. (1980) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.2600690814 · Cited by 581 · see citing works
Molecular fields in quantitative structure–permeation relationships: the VolSurf approach
Cruciani, G., Crivori, P., Carrupt, P., & Testa, B. (2000) · Journal of Molecular Structure THEOCHEM · doi:10.1016/s0166-1280(99)00360-7 · Cited by 569 · see citing works
Predicting plasma protein binding of drugs: a new approach
Kratochwil, N. A., Huber, W., Müller, F., Kansy, M., & Gerber, P. R. (2002) · Biochemical Pharmacology · doi:10.1016/s0006-2952(02)01074-2 · Cited by 553 · see citing works
A general pattern for substrate recognition by P‐glycoprotein
Seelig, A. (1998) · European Journal of Biochemistry · doi:10.1046/j.1432-1327.1998.2510252.x · Cited by 531 · see citing works
Zhao, Y. H., Le, J., Abraham, M. H., Hersey, A., Eddershaw, P. J., Luscombe, C. N., Boutina, D., Beck, G., Sherborne, B. S., Cooper, I., et al. (2001) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.1031 · Cited by 530 · see citing works
Young, R. C., Mitchell, R. C., Brown, T. H., Ganellin, C. R., Griffiths, R., Jones, M. L., Rana, K. K., Saunders, D. T., & Smith, I. R. L. (1988) · Journal of Medicinal Chemistry · doi:10.1021/jm00398a028 · Cited by 522 · see citing works
Pursuing the leadlikeness concept in pharmaceutical research
Hann, M. M., & Oprea, T. I. (2004) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2004.04.003 · Cited by 516 · see citing works
Self-citationDuffy, E. M., & Jorgensen, W. L. (2000) · Journal of the American Chemical Society · doi:10.1021/ja993663t · Cited by 500 · see citing works
Lennernäs, H. (1998) · Journal of Pharmaceutical Sciences · doi:10.1021/js970332a · Cited by 498 · see citing works
Fatty acid binding to human serum albumin: new insights from crystallographic studies
Curry, S., Brick, P., & Franks, N. P. (1999) · Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids · doi:10.1016/s1388-1981(99)00148-1 · Cited by 497 · see citing works
In silico prediction of blood–brain barrier permeation
Clark, D. E. (2003) · Drug Discovery Today · doi:10.1016/s1359-6446(03)02827-7 · Cited by 484 · see citing works
Yazdanian, M. A., Glynn, S. L., Wright, J. L., & Hawi, A. A. (1998) · Pharmaceutical Research · doi:10.1023/a:1011930411574 · Cited by 454 · see citing works
Tetko, I. V., Tanchuk, V. Y., & Villa, A. E. P. (2001) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci010368v · Cited by 382 · see citing works
Self-citationBlood-Brain Barrier Permeation: Molecular Parameters Governing Passive Diffusion
Fischer, H., Gottschlich, R., & Seelig, A. (1998) · The Journal of Membrane Biology · doi:10.1007/s002329900434 · Cited by 371 · see citing works
Estimation of the aqueous solubility I: Application to organic nonelectrolytes
Jain, N., & Yalkowsky, S. H. (2001) · Journal of Pharmaceutical Sciences · doi:10.1002/1520-6017(200102)90:2 · Cited by 368 · see citing works
Prediction of drug solubility from Monte Carlo simulations
Jorgensen, W. L., & Duffy, E. M. (2000) · Bioorganic & Medicinal Chemistry Letters · doi:10.1016/s0960-894x(00)00172-4 · Cited by 362 · see citing works
Chemography: The Art of Navigating in Chemical Space
Oprea, T. I., & Gottfries, J. (2001) · Journal of Combinatorial Chemistry · doi:10.1021/cc0000388 · Cited by 351 · see citing works
Self-citationValko, K. L., Nunhuck, S., Bevan, C., Abraham, M. H., & Reynolds, D. P. (2003) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.10494 · Cited by 346 · see citing works
Estimation of Aqueous Solubility of Chemical Compounds Using E-State Indices
Tetko, I. V., Tanchuk, V. Y., Kasheva, T. N., & Villa, A. E. P. (2001) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci000392t · Cited by 331 · see citing works
Self-citationEstimation of Aqueous Solubility for a Diverse Set of Organic Compounds Based on Molecular Topology
Huuskonen, J. J. (2000) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci9901338 · Cited by 307 · see citing works
Computational approaches to the prediction of the blood–brain distribution
Norinder, U., & Haeberlein, M. (2002) · Advanced Drug Delivery Reviews · doi:10.1016/s0169-409x(02)00005-4 · Cited by 305 · see citing works
Intestinal permeability and its relevance for absorption and elimination
Lennernäs, H. (2007) · Xenobiotica · doi:10.1080/00498250701704819 · Cited by 304 · see citing works
Similarity to Molecules in the Training Set Is a Good Discriminator for Prediction Accuracy in QSAR
Sheridan, R. P., Feuston, B. P., Maiorov, V. N., & Kearsley, S. K. (2004) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci049782w · Cited by 298 · see citing works
In silico prediction of drug‐binding strengths to human serum albumin
Colmenarejo, G. (2003) · Medicinal Research Reviews · doi:10.1002/med.10039 · Cited by 292 · see citing works
Computer Automated log P Calculations Based on an Extended Group Contribution Approach
Klopman, G., Li, J.-Y., Wang, S., & Dimayuga, M. (1994) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci00020a009 · Cited by 286 · see citing works
Prediction of aqueous solubility of drugs and pesticides with COSMO‐RS
Klamt, A., Eckert, F., Hornig, M., Beck, M. E., & Bürger, T. (2001) · Journal of Computational Chemistry · doi:10.1002/jcc.1168 · Cited by 279 · see citing works
Lipophilicity in drug action and toxicology
Pliška, V., Testa, B., & Waterbeemd, H. V. D. (1996) · Methods and principles in medicinal chemistry · doi:10.1002/9783527614998 · Cited by 267 · see citing works
Cheminformatic Models To Predict Binding Affinities to Human Serum Albumin
Colmenarejo, G., Álvarez-Pedraglio, A. I., & Lavandera, J.-L. (2001) · Journal of Medicinal Chemistry · doi:10.1021/jm010960b · Cited by 255 · see citing works
Experimental and Computational Screening Models for the Prediction of Intestinal Drug Absorption
Stenberg, P., Norinder, U., Luthman, K., & Artursson, P. (2001) · Journal of Medicinal Chemistry · doi:10.1021/jm001101a · Cited by 253 · see citing works
Integrating virtual screening in lead discovery
Oprea, T. I., & Matter, H. (2004) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2004.06.008 · Cited by 251 · see citing works
Self-citationAbsorption Classification of Oral Drugs Based on Molecular Surface Properties
Bergström, C. A. S., Strafford, M., Lazorova, L., Avdeef, A., Luthman, K., & Artursson, P. (2003) · Journal of Medicinal Chemistry · doi:10.1021/jm020986i · Cited by 248 · see citing works
Horrobin, D. F. (2003) · Nature Reviews Drug Discovery · doi:10.1038/nrd1012 · Cited by 248 · see citing works
DEVELOPMENT OF A COMPUTATIONAL APPROACH TO PREDICT BLOOD-BRAIN BARRIER PERMEABILITY
Liu, X., Tu, M., Kelly, R. S., Chen, C., & Smith, B. J. (2004) · Drug Metabolism and Disposition · doi:10.1124/dmd.32.1.132 · Cited by 245 · see citing works
Can we estimate the accuracy of ADME–Tox predictions?
Tetko, I. V., Bruneau, P., Mewes, H., Rohrer, D. C., & Poda, G. I. (2006) · Drug Discovery Today · doi:10.1016/j.drudis.2006.06.013 · Cited by 243 · see citing works
Self-citationHou, T., Wang, J., Zhang, W., & Xu, X. (2006) · Journal of Chemical Information and Modeling · doi:10.1021/ci600343x · Cited by 234 · see citing works
Decision Forest: Combining the Predictions of Multiple Independent Decision Tree Models
Tong, W., Hong, H., Fang, H., Xie, Q., & Perkins, R. (2003) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci020058s · Cited by 228 · see citing works
Prediction of Drug Solubility by the General Solubility Equation (GSE)
Ran, Y., & Yalkowsky, S. H. (2001) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci000338c · Cited by 219 · see citing works
Gramatica, P., Pilutti, P., & Papa, E. (2004) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci049923u · Cited by 209 · see citing works
Tetko, I. V., & Bruneau, P. (2004) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.20217 · Cited by 204 · see citing works
Self-citationHou, T., Zhang, W., Xia, K., Qiao, X. B., & Xu, X. J. (2004) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci049884m · Cited by 201 · see citing works
Estimation of Caco‐2 Cell Permeability using Calculated Molecular Descriptors
Waterbeemd, H. V. D., Camenisch, G., Folkers, G., & Raevsky, O. A. (1996) · Quantitative Structure-Activity Relationships · doi:10.1002/qsar.19960150604 · Cited by 200 · see citing works
Predicting aqueous solubility from structure
Delaney, J. S. (2005) · Drug Discovery Today · doi:10.1016/s1359-6446(04)03365-3 · Cited by 192 · see citing works
Solubility and Partitioning VI: Octanol Solubility and Octanol–Water Partition Coefficients
YalkowskyX, S. H., Valvani, S. C., & Roseman, T. J. (1983) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.2600720808 · Cited by 190 · see citing works
Calculating partition coefficient by atom-additive method
Wang, R., Gao, Y. D., & Lai, L. (2000) · Perspectives in Drug Discovery and Design · doi:10.1023/a:1008763405023 · Cited by 188 · see citing works
Balakin, K. V., Savchuk, N., & Tetko, I. V. (2005) · Current Medicinal Chemistry · doi:10.2174/092986706775197917 · Cited by 184 · see citing works
Self-citationShen, M., Xiao, Y.-D., Golbraikh, A., Gombar, V. K., & Tropsha, A. (2003) · Journal of Medicinal Chemistry · doi:10.1021/jm020491t · Cited by 183 · see citing works
Substructure and whole molecule approaches for calculating log P
Mannhold, R., & Waterbeemd, H. V. D. (2001) · Journal of Computer-Aided Molecular Design · doi:10.1023/a:1011107422318 · Cited by 178 · see citing works
A Computational Ensemble Pharmacophore Model for Identifying Substrates of P-Glycoprotein
Penzotti, J. E., Lamb, M. L., Evensen, E., & Grootenhuis, P. D. J. (2002) · Journal of Medicinal Chemistry · doi:10.1021/jm0255062 · Cited by 178 · see citing works
In silico ADME/Tox: why models fail
Stouch, T. R., Kenyon, J. R., Johnson, S. R., Chen, X., Doweyko, A. M., & Li, Y. (2003) · Journal of Computer-Aided Molecular Design · doi:10.1023/a:1025358319677 · Cited by 176 · see citing works
Papa, E., Villa, F., & Gramatica, P. (2005) · Journal of Chemical Information and Modeling · doi:10.1021/ci050212l · Cited by 165 · see citing works
Prediction of Aqueous Solubility of Organic Compounds by the General Solubility Equation (GSE)
Ran, Y., Jain, N., & Yalkowsky, S. H. (2001) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci010287z · Cited by 161 · see citing works
Lombardo, F., Obach, R. S., Shalaeva, M. Y., & Gao, F. (2004) · Journal of Medicinal Chemistry · doi:10.1021/jm030408h · Cited by 159 · see citing works
Estimation of the Aqueous Solubility of Organic Molecules by the Group Contribution Approach
Klopman, G., & Zhu, H. (2001) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci000152d · Cited by 156 · see citing works
Group contribution methods to estimate water solubility of organic chemicals
Kühne, R., Ebert, R., Kleint, F., Schmidt, G. A., & Schüürmann, G. (1995) · Chemosphere · doi:10.1016/0045-6535(95)00084-l · Cited by 152 · see citing works
Abraham, M. H., Ibrahim, A., Zhao, Y. H., & Acree, W. E. (2006) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.20595 · Cited by 149 · see citing works
Virtual Screening for Bioactive Molecules
Böhm, H., & Schneider, G. (2000) · Methods and principles in medicinal chemistry · doi:10.1002/9783527613083 · Cited by 141 · see citing works
Mayer, C. R., Cabuil, V., Lalot, T., & Thouvenot, R. (1999) · Angewandte Chemie International Edition · doi:10.1002/(sici)1521-3773(19991216)38:24 · Cited by 139 · see citing works
Combinatorial QSAR Modeling of P-Glycoprotein Substrates
Lima, P. D. C., Golbraikh, A., Oloff, S., Xiao, Y.-D., & Tropsha, A. (2006) · Journal of Chemical Information and Modeling · doi:10.1021/ci0504317 · Cited by 138 · see citing works
Petrauskas, A. A., & Kolovanov, E. A. (2000) · Perspectives in Drug Discovery and Design · doi:10.1023/a:1008719622770 · Cited by 135 · see citing works
Virtual Screening in Lead Discovery: A Viewpoint
Oprea, T. I. (2002) · Molecules · doi:10.3390/70100051 · Cited by 133 · see citing works
Self-citationKlopman, G., Stefan, L. R., & Saiakhov, R. (2002) · European Journal of Pharmaceutical Sciences · doi:10.1016/s0928-0987(02)00219-1 · Cited by 130 · see citing works
Application of ALOGPS 2.1 to Predict log D Distribution Coefficient for Pfizer Proprietary Compounds
Tetko, I. V., & Poda, G. I. (2004) · Journal of Medicinal Chemistry · doi:10.1021/jm049509l · Cited by 126 · see citing works
Self-citationEstimating log P with atom/fragments and water solubility with log P
Meylan, W. M., & Howard, P. H. (2000) · Perspectives in Drug Discovery and Design · doi:10.1023/a:1008715521862 · Cited by 120 · see citing works
Computational prediction of the plasma protein‐binding percent of diverse pharmaceutical compounds
Yamazaki, K., & Kanaoka, M. (2004) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.20059 · Cited by 113 · see citing works
In Silico ADMET Traffic Lights as a Tool for the Prioritization of HTS Hits
Lobell, M., Hendrix, M., Hinzen, B., Keldenich, J., Meier, H., Schmeck, C., Schohe-Loop, R., Wunberg, T., & Hillisch, A. (2006) · ChemMedChem · doi:10.1002/cmdc.200600168 · Cited by 112 · see citing works
Lombardo, F., Obach, R. S., DiCapua, F. M., Bakken, G. A., Lu, J., Potter, D. M., Gao, F., Miller, M. D., & Zhang, Y. (2006) · Journal of Medicinal Chemistry · doi:10.1021/jm050200r · Cited by 107 · see citing works
Leo, A. J., & Hoekman, D. A. (2000) · Perspectives in Drug Discovery and Design · doi:10.1023/a:1008739110753 · Cited by 105 · see citing works
Toward minimalistic modeling of oral drug absorption
Oprea, T. I., & Gottfries, J. (1999) · Journal of Molecular Graphics and Modelling · doi:10.1016/s1093-3263(99)00034-0 · Cited by 99 · see citing works
Self-citationLiu, R., & So, S. (2001) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci010289j · Cited by 96 · see citing works
Assessment of n-Octanol/Water Partition Coefficient: When Is the Assessment Reliable?
Gombar, V. K., & Enslein, K. (1996) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci960028n · Cited by 91 · see citing works
Prediction of human pharmacokinetics —gastrointestinal absorption
Fagerholm, U. (2007) · Journal of Pharmacy and Pharmacology · doi:10.1211/jpp.59.7.0001 · Cited by 91 · see citing works
Chemical biology : from small molecules to systems biology and drug design
Schreiber, S. L., Kapoor, T. M., & Wess, G. (2007) · Wiley-VCH eBooks · Cited by 90 · see citing works
Hornig, M., & Klamt, A. (2005) · Journal of Chemical Information and Modeling · doi:10.1021/ci0501948 · Cited by 90 · see citing works
Sakurai, A., Onishi, Y., Hirano, H., Seigneuret, M., Obanayama, K., Kim, G., Liew, E. L., Sakaeda, T., Yoshiura, K.-I., Niikawa, N., et al. (2007) · Biochemistry · doi:10.1021/bi700330b · Cited by 90 · see citing works
Breindl, A., Beck, B., Clark, T., & Glen, R. C. (1997) · Journal of Molecular Modeling · doi:10.1007/s008940050027 · Cited by 86 · see citing works
Computational toxicology: risk assessment for pharmaceutical and environmental chemicals
(2008) · Choice Reviews Online · doi:10.5860/choice.45-4386 · Cited by 85 · see citing works
Mannhold, R., & Rekker, R. F. (2000) · Perspectives in Drug Discovery and Design · doi:10.1023/a:1008782809845 · Cited by 80 · see citing works
Accurate Solubility Prediction with Error Bars for Electrolytes: A Machine Learning Approach
Schwaighofer, A., Schroeter, T. S., Mika, S., Laub, J., ter Laak, A., Sülzle, D., Ganzer, U., Heinrich, N., & Müller, K. (2007) · Journal of Chemical Information and Modeling · doi:10.1021/ci600205g · Cited by 80 · see citing works
Pharmacokinetically Based Mapping Device for Chemical Space Navigation
Oprea, T. I., Zamora, I., & Ungell, A.-L. (2002) · Journal of Combinatorial Chemistry · doi:10.1021/cc010093w · Cited by 77 · see citing works
Self-citationPrediction of human pharmacokinetics — renal metabolic and excretion clearance
Fagerholm, U. (2007) · Journal of Pharmacy and Pharmacology · doi:10.1211/jpp.59.11.0002 · Cited by 76 · see citing works
Livingstone, D. J., Ford, M. G., Huuskonen, J. J., & Salt, D. W. (2001) · Journal of Computer-Aided Molecular Design · doi:10.1023/a:1012284411691 · Cited by 75 · see citing works
Segall, M., Beresford, A. P., Gola, J. M. R., Hawksley, D., & Tarbit, M. (2006) · Expert Opinion on Drug Metabolism & Toxicology · doi:10.1517/17425255.2.2.325 · Cited by 71 · see citing works
Identifying P-Glycoprotein Substrates Using a Support Vector Machine Optimized by a Particle Swarm
Huang, J., Ma, G., Ishtiaq, M., & Cheng, Y. (2007) · Journal of Chemical Information and Modeling · doi:10.1021/ci700083n · Cited by 69 · see citing works
Saiakhov, R., Stefan, L. R., & Klopman, G. (2000) · Perspectives in Drug Discovery and Design · doi:10.1023/a:1008723723679 · Cited by 67 · see citing works
Bruneau, P., & McElroy, N. R. (2005) · Journal of Chemical Information and Modeling · doi:10.1021/ci0504014 · Cited by 66 · see citing works
Ivnitski‐Steele, I. D., Larson, R. A., Lovato, D. M., Khawaja, H. M., Winter, S. S., Oprea, T. I., Sklar, L. A., & Edwards, B. S. (2008) · Assay and Drug Development Technologies · doi:10.1089/adt.2007.107 · Cited by 63 · see citing works
Self-citationBasak, S. C., & Grunwald, G. D. (1995) · Chemosphere · doi:10.1016/0045-6535(95)00122-o · Cited by 63 · see citing works
A Consensus Neural Network-Based Technique for Discriminating Soluble and Poorly Soluble Compounds
Manallack, D. T., Tehan, B. G., Gancia, E., Hudson, B. D., Ford, M. G., Livingstone, D. J., Whitley, D. C., & Pitt, W. R. (2003) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci0202741 · Cited by 62 · see citing works
Fragmental Methods in the Design of New Compounds. Applications of The Advanced Algorithm Builder
Japertas, P., Didžiapetris, R., & Petrauskas, A. A. (2002) · Quantitative Structure-Activity Relationships · doi:10.1002/1521-3838(200205)21:1 · Cited by 62 · see citing works
Surface Descriptors for Protein−Ligand Affinity Prediction
Zamora, I., Oprea, T. I., Cruciani, G., Pastor, M., & Ungell, A.-L. B. (2002) · Journal of Medicinal Chemistry · doi:10.1021/jm011051p · Cited by 60 · see citing works
Self-citationPrediction of Caco-2 cell permeability using a combination of MO-calculation and neural network
Fujiwara, S., Yamashita, F., & Hashida, M. (2002) · International Journal of Pharmaceutics · doi:10.1016/s0378-5173(02)00045-5 · Cited by 60 · see citing works
Feature Selection for Descriptor Based Classification Models. 2. Human Intestinal Absorption (HIA)
Wegner, J. K., Fröhlich, H., & Zell, A. (2004) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci034233w · Cited by 59 · see citing works
Yamashita, F., Wanchana, S., & Hashida, M. (2002) · Journal of Pharmaceutical Sciences · doi:10.1002/jps.10214 · Cited by 56 · see citing works
Structure-Activity Relationships and Drug Disposition
Lien, E. J. C. (1981) · The Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev.pa.21.040181.000335 · Cited by 52 · see citing works
Mannhold, R., Rekker, R. F., Dross, K. P., Bijloo, G. J., & de Vries, G. (1998) · Quantitative Structure-Activity Relationships · doi:10.1002/(sici)1521-3838(199812)17:06 · Cited by 49 · see citing works
Use of Classification Regression Tree in Predicting Oral Absorption in Humans
Bai, J. P. F., Utis, A., Crippen, G. M., He, H., Fischer, V., Tullman, R. H., Yin, H., Hsu, C., Jiang, L., & Hwang, K. (2004) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci040023n · Cited by 47 · see citing works
Substructure versus Whole‐molecule Approaches for Calculating Log P
Mannhold, R., & Petrauskas, A. A. (2003) · QSAR & Combinatorial Science · doi:10.1002/qsar.200390036 · Cited by 46 · see citing works
Votano, J. R., Parham, M., Hall, L. H., & Kier, L. B. (2004) · Molecular Diversity · doi:10.1023/b:modi.0000047512.82293.75 · Cited by 43 · see citing works
A Quantum Mechanical/Neural Net Model for Boiling Points with Error Estimation
Chalk, A. J., Beck, B., & Clark, T. (2001) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci0004614 · Cited by 42 · see citing works
Schroeter, T. S., Schwaighofer, A., Mika, S., ter Laak, A., Suelzle, D., Ganzer, U., Heinrich, N., & Müller, K. (2007) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-007-9160-9 · Cited by 40 · see citing works
Comparison of Two Methods for Predicting Aqueous Solubility
Peterson, D. L., & Yalkowsky, S. H. (2001) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci010298s · Cited by 38 · see citing works
Wada, M. (2005) · Cancer Letters · doi:10.1016/j.canlet.2005.06.050 · Cited by 35 · see citing works
Göller, A. H., Hennemann, M., Keldenich, J., & Clark, T. (2006) · Journal of Chemical Information and Modeling · doi:10.1021/ci0503210 · Cited by 34 · see citing works
Prediction of Partition Coefficients (LOGPoct) Using Autocorrelation Descriptors
Devillers, J., Domine, D., Guillon, C., Bintein, S., & Karcher, W. (1997) · SAR and QSAR in environmental research · doi:10.1080/10629369708039129 · Cited by 30 · see citing works
Fragmental Methods in the Analysis of Biological Activities of Diverse Compound Sets
Japertas, P., Didžiapetris, R., & Petrauskas, A. A. (2003) · Mini-Reviews in Medicinal Chemistry · doi:10.2174/1389557033487601 · Cited by 29 · see citing works
Winter, S. S., Lovato, D. M., Khawaja, H. M., Edwards, B. S., Steele, I. D., Young, S. M., Oprea, T. I., Sklar, L. A., & Larson, R. S. (2008) · SLAS DISCOVERY · doi:10.1177/1087057108314610 · Cited by 29 · see citing works
Self-citationViswanadhan, V. N., Ghose, A. K., & Wendoloski, J. J. (2000) · Perspectives in Drug Discovery and Design · doi:10.1023/a:1008767505932 · Cited by 27 · see citing works
QSAR Studies on Blood-Brain Barrier Permeation
Luco, J. M., & Marchevsky, E. (2006) · Current Computer - Aided Drug Design · doi:10.2174/157340906776056437 · Cited by 24 · see citing works
How to escape the bottleneck of medicinal chemistry
Wess, G. (2002) · Drug Discovery Today · doi:10.1016/s1359-6446(02)02252-3 · Cited by 23 · see citing works
Reliable Assessment of Log P of Compounds of Pharmaceutical Relevance
Gombar, V. K. (1999) · SAR and QSAR in environmental research · doi:10.1080/10629369908039105 · Cited by 23 · see citing works
What Works and What Does Not: Lessons From Experience in a Pharmaceutical Company
Martin, Y. C. (2006) · QSAR & Combinatorial Science · doi:10.1002/qsar.200610102 · Cited by 18 · see citing works
Training ACD/LogP with Experimental Data
Walker, M. J. P. (2004) · QSAR & Combinatorial Science · doi:10.1002/qsar.200410010 · Cited by 13 · see citing works
Zdrazil, B., Kaiser, D., Kopp, S., Chiba, P., & Ecker, G. F. (2007) · QSAR & Combinatorial Science · doi:10.1002/qsar.200610149 · Cited by 13 · see citing works
Ranade, V. (2006) · American Journal of Therapeutics · doi:10.1097/00045391-200607000-00020 · Cited by 13 · see citing works
Computational Chemistry at Novartis
Lewis, R., Ertl, P., Jacoby, E., Tintelnot‐Blomley, M., Gedeck, P., Wolf, R. M., & Peitsch, M. C. (2005) · CHIMIA International Journal for Chemistry · doi:10.2533/000942905777676155 · Cited by 7 · see citing works
Flagged first, then by citations
Cited by
Sorted by citations
BDDCS Applied to Over 900 Drugs
Benet, L. Z., Broccatelli, F., & Oprea, T. I. (2011) · The AAPS Journal · doi:10.1208/s12248-011-9290-9 · Cited by 636 · see citing works
Self-citationArtificial Intelligence for Drug Discovery: Are We There Yet?
Hasselgren, C., & Oprea, T. I. (2024) · Annual Review of Pharmacology and Toxicology · doi:10.1146/annurev-pharmtox-040323-040828 · Cited by 236 · see citing works
Self-citationIn silico estimation of basic activity-relevant parameters for a set of drug absorption promoters
Bąk, A., Kozik, V., Smoliński, A., & Jampílek, J. (2017) · SAR and QSAR in environmental research · doi:10.1080/1062936x.2017.1327459 · Cited by 17 · see citing works
Optimal ADME Properties for Clinical Candidate and Investigational New Drug (IND) Package
Bhardwaj, R., & Chandrasena, G. (2012) · doi:10.1002/9781118180778.ch2 · Cited by 4 · see citing works
Sharma, K., & Kapoor, J. K. (2026) · New Journal of Chemistry · doi:10.1039/d6nj01536k
- Authors
- Tetko, I. V., & Oprea, T. I.
- Affiliations
- Helmholtz Munich (DE)
- University of New Mexico (US)
- Venue
- Chemoinformatics Approaches to Virtual Screening
- Publisher
- The Royal Society of Chemistry
- Published
- 2008-09-29
- Pages
- 240-267
- OpenAlex
- W2341261432
- Cited by
- 5
- References
- 139
- Citations by year
- 2026: 1 · 2023: 1 · 2017: 1 · 2012: 1
- FWCI
- 0.97
- Type
- book chapter
- Language
- en
- Open access
- closed
- Locations
- Royal Society of Chemistry eBooks (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmacology › Pharmacogenetics and Drug Metabolism
- Health Sciences › Veterinary › Small Animals › Animal testing and alternatives
- Keywords
- ADMET prediction, drug discovery, absorption, distribution, metabolism, excretion, toxicity, predictive toxicology, chemical compound properties
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review