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Predictive/in silico ADME

Computer-aided methods are key components of the drug discovery and development process. For example, computer-aided methods allow for chemical screening in silico to identify and prioritize the most interesting compounds for further analysis. This reduces the cost and time associated with the drug screening process. In addition, computer-aided methods can guide chemical synthesis by using 3D structural information of the target-binding site; or, by using quantitative structure-activity relationships (QSAR) models or quantitative structure-property relationships (QSPR) models to correlate descriptors of chemical compounds with affinities or pharmacokinetic properties. Finally, computer-aided techniques can be applied to areas outside of drug design including computational modeling of pharmaceutical nanotechnology and physicochemical modeling of drug transport and pharmacokinetics. At CDR, multiple groups are active in the area of computational drug discovery and pharmaceutical modeling:

The Computational ADME group currently focuses on four research areas:

  • Molecular modeling of protein structure and receptor-ligand complexes, with special expertise in G protein-coupled receptors, monoamine transporters, and some key enzymes.
  • Design and screening of compound libraries.
  • Prediction of pharmacokinetic properties by using QSAR/QSPR modeling.
  • Structural bioinformatics approaches for design of novel drug scaffolds in peptide mimetic chemistry.

The Computational Drug ADME Group actively participates in the Drug Discovery and Chemical Biology (DDCB) consortium within Biocenter Finland (BF), a national infrastructure for drug discovery and chemical biology research in Finland. As a member of BF, they provide contract services and expertise in virtual screening, molecular modeling, chemoinformatics, and in silico ADMET. For more information or to inquire about contract services in these areas, please contact This email address is being protected from spambots. You need JavaScript enabled to view it..

Selected Publications:


Cellular and computational models are developed for improved prediction of clinical ADME properties. We are using and further developing the following epithelial cell models: Caco-2, MDCK, MDCK cell lines with transfected human transporter genes, blood-retinal barrier models, corneal and epidermal models. Furthermore, we have generated numerous Sf9 cells that stably express various human ABS efflux transporters. These cell models can be used for drug permeability and transporter interaction studies. Computational modeling activities can be divided into two categories: structure-based models and pharmacokinetic models. Structure-based models include QSAR for oral drug absorption. QSAR models for efflux transport and volume of drug distribution are being developed and tested continuously. Both in vitro and in silico data are integrated into pharmacokinetic simulation models that can be used to estimate the importance of different factors in the physiological setting.

All Publications

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