Masek Brian B, Shen Lingling, Smith Karl M, Pearlman Robert S
Tripos, Inc., 1699 S. Hanley Road, St. Louis, Missouri 63144, USA.
J Chem Inf Model. 2008 Feb;48(2):256-61. doi: 10.1021/ci600383v. Epub 2008 Feb 7.
Studies to assess the risks of revealing chemical structures by sharing various chemical descriptor data are presented. Descriptors examined include "Lipinski-like" properties, 2D-BCUT descriptors, and a high-dimensional "fingerprint-like" descriptor (MACCs-vector). We demonstrate that unless sufficient precautions are taken, de novo design software such as EA-Inventor is able to derive a unique chemical structure or a set of closely related analogs from some commonly used descriptors. Based on the results of our studies, a set of guidelines or recommendations for safely sharing chemical information without revealing chemical structure is presented. A procedure for assessing the risk of revealing chemical structure when exchanging chemical descriptor information was also developed. The procedure is generic and can be applied to any chemical descriptor or combination of descriptors and to any set of structures to enable a decision about whether the exchange of information can be done without revealing the chemical structures.
本文介绍了通过共享各种化学描述符数据来评估揭示化学结构风险的研究。所研究的描述符包括“类Lipinski”性质、二维BCUT描述符以及高维“类指纹”描述符（MACCs向量）。我们证明，除非采取足够的预防措施，否则诸如EA-Inventor之类的从头设计软件能够从一些常用描述符中推导出独特的化学结构或一组密切相关的类似物。基于我们的研究结果，提出了一套在不揭示化学结构的情况下安全共享化学信息的指南或建议。还开发了一种在交换化学描述符信息时评估揭示化学结构风险的程序。该程序是通用的，可应用于任何化学描述符或描述符组合以及任何结构集，以便决定是否可以在不揭示化学结构的情况下进行信息交换。
