Sanz Ferran, Carrió Pau, López Oriol, Capoferri Luigi, Kooi Derk P, Vermeulen Nico P E, Geerke Daan P, Montanari Floriane, Ecker Gerhard F, Schwab Christof H, Kleinöder Thomas, Magdziarz Tomasz, Pastor Manuel
Research Programme on Biomedical Informatics (GRIB), Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Hospital del Mar Medical Research Institute (IMIM), Dr. Aiguader 88, E-08003 Barcelona, Spain phone/fax: +34933160512; +34933160550.
AIMMS Division of Molecular Toxicology, Department of Chemistry and Pharmaceutical Sciences, Faculty of Sciences, VU University Amsterdam, De Boelelaan 1083, 1081 HV Amsterdam, The Netherlands.
Mol Inform. 2015 Jun;34(6-7):477-84. doi: 10.1002/minf.201400193. Epub 2015 Jun 11.
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).
在药物研发过程中对安全问题进行早期预测,既极具吸引力,又极具挑战性。近期的进展凸显了理解导致可观察到的毒性结果的整个因果事件链的重要性。在此,我们描述了一种基于这些理念的综合建模策略,该策略指导了eTOXsys的设计,eTOXsys是eTOX项目所使用的预测系统。从本质上讲,eTOXsys由一台中央服务器组成,该服务器整理对一组独立预测模型的请求,并为整个系统提供单一用户界面。每个这样的模型都存在于一个易于维护和安装的独立虚拟机中。所有模型自身都会生成与毒性相关的预测,但有些模型的结果可以进一步整合并提升其规模,从而得出体内毒性预测结果。本文还讨论了与模型实施、维护和文档编制相关的技术方面。最后,通过展示三个利用不同方法(3D-QSAR和决策树、分子动力学模拟和线性相互作用能理论以及基于指纹的QSAR)的示例模型,来说明目前在eTOXsys中实施的模型类型。