Possibilities for transfer of relevant data without revealing structural information
Possibilities for transfer of relevant data without revealing structural information
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DOI：
10.1007/s10822-005-9026-y
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发表时间：
2005-09-01
影响因子：
3.5
通讯作者：
Güner, OF
中科院分区：
文献类型：
--
作者：
Clement, OO;Güner, OF
在本文中，我们讨论了在预测性ADME/Tox模型开发的早期，我们如何在第三方之间安全地交换专有数据。当时，行业科学家希望评估预测模型，但不愿意与软件供应商共享其结构。与此同时，模型开发人员愿意在他们的模型中运行科学家的结构，但他们不愿意透露哪些描述符对特定的预测模型很重要。我们开发了一个过程，科学家可以对大量的商业可用的公共描述符进行计算，并将结果作为属性文件而不是其结构进行转发。与此同时，模型开发人员可以提取预测模型中使用的描述符，运行模型，并将结果返回给科学家。在接下来的几页中，我们将讨论这种方法的优点和缺点，并解决以下问题：ADME/Tox模型中的描述符是否会损害专有的结构信息？ADME/Tox预测是否可以纯粹从描述符进行，而不需要明确的化学结构知识，专有或其他？
In this paper, we discuss how we safely exchanged proprietary data between third parties in the early years of predictive ADME/Tox model development. At that time, industry scientists wanted to evaluate predictive models, but were not willing to share their structures with software vendors. At the same time, model developers were willing to run the scientists' structures through their models, but they were not willing to reveal which descriptors were important for a particular predictive model. We developed a process where scientists could perform calculations on a broad number of commercially available public descriptors and forward results as a property file, instead of their structures. Meanwhile, the model developer could extract descriptors used in the predictive model, run the model, and pass results back to the scientist. On the following pages, we discuss the pros and cons of this approach, and we address questions such as: Can structural information that is proprietary be compromised from descriptors in ADME/Tox models? Can ADME/Tox predictions be made purely from descriptors, without the explicit knowledge of chemical structures, proprietary or otherwise?