We collected experimental ADMET data from the published literature. The availability of reliable experimental data and basic structural information is crucial for successful ADMET modeling. PKKB contains 31412 experimental or predicted values for 1685 drug or drug-like molecules. The data in PKKB can be roughly divided into eight categories, i.e. molecular basic information, molecular experimental or predicted physicochemical properties, pharmacology information, and the properties of ADMET (absorption, distribution, metabolism, excretion and toxicity).
| Classification | Property | Measurements |
|---|---|---|
| Molecular Properties | Molecular weight | 1684 |
| logP (experiment) | 1019 | |
| logP (predicted,AB/logP v2.0) | 1625 | |
| Pka | 638 | |
| logD (pH=7,predicted) | 1625 | |
| Solubility( experiment) | 800 | |
| logS (predicted,ACD/Labs)(pH=7) | 1614 | |
| logSw (predicted,AB/LogSw 2.0) | 1625 | |
| Sw(mg/ml) (predicted,ACD/Labs) | 1613 | |
| Sw (predicted) | 1625 | |
| No. of hbond donors | 1625 | |
| No. of hbond acceptors | 1625 | |
| No. of rotatable bonds | 1625 | |
| TPSA | 1625 | |
| Pharmacology | Status | 1372 |
| Administration | 501 | |
| Pharmacology | 1543 | |
| Absorption | Intestinal absorption | 679 |
| Absorption(description) | 699 | |
| Caco-2 | 64 | |
| Human bioavailability | 992 | |
| Distribution | Plasma protein binding | 1058 |
| Volume of distribution(Vd) | 646 | |
| D-blood | 66 | |
| Metabolism | Metabolism | 1111 |
| Half-time | 1116 | |
| Excretion | Excretion | 855 |
| Urinary excretion | 281 | |
| Clearance | 410 | |
| Toxicity | Toxicity | 873 |
| LD50(rat) | 219 | |
| LD50(mouse) | 243 |
- Drug design & Chemoinformatics
- Drug Design Resources [Link]
- Drugbank database [Link]
- Zinc database: a free database for virtual screening[Link]
- HIV Drug Resistance Database[Link]
- Pymol[Link]
- VMD:Visual Molecular Dynamics[Link]
- Chimera: a extensible molecular modeling system[Link]
- Autodock[Link]
- UCSF Dock[Link]
- 3D-Dock Suite[Link]
- OEChem Toolkit[Link]
- Open Babel A Package to Decypher Computational Chemistry[Link]
- Computational biology
- Gromacs[Link]
- Amber[Link]
- CHARMM: Chemistry at HARvard Molecular Mechanics[Link]
- NAMD: Scalable Molecular Dynamics[Link]
- Tinker: Software Tools for Molecular Design[Link]
- Atlas of Protein Side-Chain Interactions[HTML]
- Rosetta[Link]
- Delphi[Link]
- Bioinformatics
- NCBI: National Center for Biotechnology Information[Link]
- PDB database[Link]
- Swiss-prot database[Link]
- PIR: protein information resource[Link]
- Prosite: database of protein domains, families and functional sites[Link]
- ProDom: database of protein domains generated from Uniprot[Link]
- Pfam: database of domains and HMMs[Link]
- BIND: e Biomolecular Interaction Network Database[Link]
- MINT: Molecular INTeraction database[Link]
- Important Journals
- Nature (Nature)[Link]
- Science (Highwire)[Link]
- Journal of Chemical Information and Modeling (ACS)[Link]
- Jounal of Medicinal Chemistry (ACS)[Link]
- Journal of Chemical Theory and Computation (ACS)[Link]
- Journal of Computer-aided Molecular Design (Springer)[Link]
- Journal of Molecular Graphics and Modeling (Elsevier)[Link]
- Journal of Molecular Modeling (Springer)[Link]
- Journal of Molecular Biology (Elsevier)[Link]
- PLoS Computational Biology[Link]
- Proteins: Functions, Structure and Bioinformatics (Wiley)[Link]
- Nucleic Acids Research (Oxford)[Link]
- Bioorganic and Medicinal Chemistry (Elsevier)[Link]
- Bioinformatics (Oxford)[Link]
- Biophysical Journal (Cell)[Link]
1. Hou, T.J.; Wang, J.M.; Zhang, W.; Xu, X.J. ADME Evaluation in Drug Discovery. 7. Prediction of Oral Absorption by Correlation and Classification. J. Chem. Inf. Model. 2007, 47, 208-218.
1. Tian, S.; Li, Y.Y.; Wang, J.M.; Zhang, J.; Hou, T.J. ADME Evaluation in Drug Discovery. 9. Prediction of Oral Bioavailability in Human based on Molecular Properties and Structural Fingerprints, Molecular Pharmaceutics, 2011, in press.
2. Hou, T.J; Wang, J.M.; Zhang, W.; Xu, X.J. ADME Evaluation in Drug Discovery. 6. Can Oral Bioavailability in Humans Be Effectively Predicted by Simple Molecular Property-Based Rules? J. Chem. Inf. Model. 2007, 47, 460-463.
1. Hou, T.J.; Zhang, W.; Xia, K.; Xu, X.J. ADME Evaluation in Drug Discovery. 5. Correlation of Caco-2 Permeation with Simple Molecular Properties, Journal of Chemical Information and Computer Sciences, 2004, 44, 1585-1600.
1. Hou, T.J.; Xu, X.J. ADME Evaluation in Drug Discovery. 3. Modeling Blood-Brain Barrier Partitioning Using Simple Molecular Descriptors. Journal of Chemical Information and Computer Sciences, 2003, 43, 2137-2152.
2. Hou, T.J.; Xu, X.J. ADME Evaluation in Drug Discovery. 1. Applications of Genetic Algorithms on the Prediction of Blood-brain Partitioning of a Large Set of Drugs from Structurally Derived Descriptors, Journal of Molecular Modeling, 2002, 8, 337-349.
1. Chen, L.; Li, Y.Y.; Zhao, Q.; Peng, H.; Hou, T.J. ADME Evaluation in Drug Discovery. 10. Predictions of P-Glycoprotein Inhibitors using Recursive Partitioning and Naïve Bayesian Classification Techniques, Molecular Pharmaceutics, 2011, (in press)
1. Hou, T.J.; Xia, K.; Zhang, W.; Xu, X.J. ADME Evaluation in Drug Discovery. 4. Prediction of Aqueous Solubility Based on Atom Contribution Approach. Journal of Chemical Information and Modeling, 2004, 44, 266-275.
2. Wang, J.M.; Krudy, G.; Hou, T.J.; Holland, G.; Xu, X.J. Development of Reliable Aqueous Solubility Models and Their Application in Drug-Like Analysis. Journal of Chemical Information and Modeling, 2007, 47, 1395-1404.
3. Wang, J.M.; Hou, T.J.; Xu, X.J. Aqueous Solubility Prediction Based on Weighted Atom Type Counts and Solvent Accessible Surface Areas, Journal of Chemical Information and Modeling, 2009, 49, 571-581.
1. Wang, J. M.; Krudy, G.; Xie, X. Q.; Wu, C. D.; Holland, G. Genetic algorithm-optimized QSPR models for bioavailability, protein binding, and urinary excretion. Journal of Chemical Information and Modeling, 2006, 46, 2674-2683.
2. Goodman, L. S.; Gilman, A.; Brunton, L. L.; Teton Data Systems (Firm). Goodman & Gilman's the pharmacological basis of therapeutics.
3. Physicians’ Desk Reference (PDR); Thomson 2005, 59th ed.
We have developed an integrated ADMET database which includes useful information on a variety of important pharmacokinetic and toxic properties. PKKB will be continuously updated as new information becomes available, and we hope it can provide effective help for researchers in the drug discovery field. Moreover, we will afford on-line prediction functions for several important ADMET properties in the next version of PKKB.
Professor Tingjun Hou
Institute of Functional Nano & Soft Materials (FUNSOM),
Soochow University, Suzhou, Jiangsu 215123, China
Email: tjhou@suda.edu.cn
Professor Junmei Wang
Department of Pharmacology,
The University of Texas Southwestern Medical Center,
5323 Harry Hines Blvd., Dallas, TX 75390
Email: Junmei.Wang@UTSouthwestern.edu