The Open Cyclodextrin database allows users to search and access to the association constant of various guest molecules with cyclodextrins. The database supports various structural query formats, including SMILES, InChI, and Molecular Formula. To maintain the quality and reliability of the data, the Open Cyclodextrin database follows a rigorous review process. Contributions from researchers are carefully reviewed and verified by moderators to ensure the accuracy and integrity of the information. This collaborative approach ensures that the database contains a diverse range of valuable data from various sources. Additionally, the database includes a predictor tool based on Machine Learning model that allows users to estimate the association constant between guest molecules and different cyclodextrins.
The search tool enables users to query the Open Cyclodextrin databases using chemical structure or chemical structure pattern. Users have the ability to define their structural queries using SMILES, InChI, or Molecular Formula. Furthermore, the tool provides users with the option to manually draw a query.
The Machine Learning predictor tool enables users to predict the association constant between guest molecules and different cyclodextrins. Users can provide the structural information of the guest molecule by using SMILES, InChI, Molecular Formula, or by manually drawing it.
The Open Cyclodextrin databases is an open and collaborative database, welcoming contributions from all researchers who can add their published data. To maintain data integrity and reliability, the submissions are carefully reviewed and verified by moderators. This collaborative approach ensures that the database contains a diverse range of valuable information from various sources.