Sharing chemical information without sharing chemical structure.

Area of Science:

• Medicinal Chemistry
• Cheminformatics
• Computational Chemistry

Background:

• Chemical descriptor data is crucial for drug discovery and development.
• Sharing such data is common practice but carries inherent risks of structure elucidation.
• Existing methods for assessing these risks are limited.

Purpose of the Study:

• To evaluate the risk of revealing chemical structures from commonly used chemical descriptors.
• To develop a generic procedure for assessing the risk associated with sharing descriptor information.
• To provide guidelines for safely sharing chemical information.

Main Methods:

• Analysis of "Lipinski-like" properties, 2D-BCUT descriptors, and MACCS-vectors.
• Utilizing de novo design software (e.g., EA-Inventor) to attempt structure reconstruction.
• Development of a risk assessment procedure applicable to various descriptors and structure sets.

Main Results:

• Certain chemical descriptors, when shared without precautions, allow de novo design software to derive unique or closely related chemical structures.
• The developed risk assessment procedure can be applied to any descriptor or combination of descriptors.
• Guidelines for safe chemical information sharing were established based on the findings.

Conclusions:

• Sharing specific chemical descriptor data poses a significant risk of revealing proprietary chemical structures.
• A robust risk assessment procedure is essential before exchanging chemical descriptor information.
• Implementing the recommended guidelines ensures the secure sharing of chemical data in cheminformatics and drug discovery.