Integrative Modeling Strategies for Predicting Drug Toxicities at the eTOX Project

Authors/others:Sanz, Ferran (University Pompeu Fabra); Carriõ, Pau (University Pompeu Fabra); Lõpez, Oriol (University Pompeu Fabra); Capoferri, Luigi (Vrije Universiteit Amsterdam); Kooi, Derk P. (Vrije Universiteit Amsterdam); Vermeulen, Nico P E (Vrije Universiteit Amsterdam); Geerke, Daan P. (Vrije Universiteit Amsterdam); Montanari, Floriane; Ecker, Gerhard F.; Schwab, Christof H. (Molecular Networks GmbH); Kleinöder, Thomas (Molecular Networks GmbH); Magdziarz, Tomasz (Molecular Networks GmbH); Pastor, Manuel (University Pompeu Fabra)
Abstract:

Early prediction of safety issues in drug development is at the same time highly desirable and highly challenging. Recent advances emphasize the importance of understanding the whole chain of causal events leading to observable toxic outcomes. Here we describe an integrative modeling strategy based on these ideas that guided the design of eTOXsys, the prediction system used by the eTOX project. Essentially, eTOXsys consists of a central server that marshals requests to a collection of independent prediction models and offers a single user interface to the whole system. Every of such model lives in a self-contained virtual machine easy to maintain and install. All models produce toxicity-relevant predictions on their own but the results of some can be further integrated and upgrade its scale, yielding in vivo toxicity predictions. Technical aspects related with model implementation, maintenance and documentation are also discussed here. Finally, the kind of models currently implemented in eTOXsys is illustrated presenting three example models making use of diverse methodology (3D-QSAR and decision trees, Molecular Dynamics simulations and Linear Interaction Energy theory, and fingerprint-based QSAR).

Language:English
Number of pages:8
Date of publication:1.6.2015
Journal title:Molecular Informatics
Volume:34
Number:6-7
Pages:477-484
Peer reviewed:true
Links:
Digital Object Identifier (DOI):http://dx.doi.org/10.1002/minf.201400193
Publication Type:Article
Portal:https://ucris.univie.ac.at/portal/en/publications/integrative-modeling-strategies-for-predicting-drug-toxicities-at-the-etox-project(e1d4f36f-9453-4a00-86cc-a61b96a2ef3c).html