TY - JOUR
T1 - Computational models for predicting the interaction with ABC transporters
AU - Pinto, Marta
AU - Digles, Daniela
AU - Ecker, Gerhard F
N1 - Funding Information:
We gratefully acknowledge financial support provided by the Austrian Science Fund under the framework of the special research programme SFB35 ‘Transmembrane Transporters in Health and Disease (F3502)’. The research leading to these results has also received support from the Innovative Medicines Initiative Joint Undertaking under grant agreements n° 115002 (eTOX), resources of which are composed of financial contribution from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution.
PY - 2014/6
Y1 - 2014/6
N2 - There is strong evidence that ATP-binding cassette (ABC) transporters play a critical role in the pharmacokinetic and pharmacodynamic properties of many drugs and xenobiotics. Due to their pharmacological role, several computational approaches have been developed to understand and predict the interaction between ABC transporters and their ligands. Here, we provide an overview of the current state of the art of the ligand-based models that, derived from the transport and inhibitory activities of a set of ligands, have been published for ABC transporters.
AB - There is strong evidence that ATP-binding cassette (ABC) transporters play a critical role in the pharmacokinetic and pharmacodynamic properties of many drugs and xenobiotics. Due to their pharmacological role, several computational approaches have been developed to understand and predict the interaction between ABC transporters and their ligands. Here, we provide an overview of the current state of the art of the ligand-based models that, derived from the transport and inhibitory activities of a set of ligands, have been published for ABC transporters.
UR - https://www.scopus.com/pages/publications/84901191208
U2 - 10.1016/j.ddtec.2014.03.007
DO - 10.1016/j.ddtec.2014.03.007
M3 - Article
C2 - 25027377
VL - 12
SP - e69-e77
JO - Drug Discovery Today: Technologies
JF - Drug Discovery Today: Technologies
ER -