CDD Vault now allows you to build predictive models. Because we believe in collaboration and reproducible results, we are releasing the core algorithms that underly this feature as open source software. The chemical fingerprints are detailed below, and we have also released our modified Bayesian model. Send an email to info@collaborativedrug.com if you'd like to try using models in CDD Vault.
By Alex Clark; portions of this post originally appeared in Cheminformatics 2.0 As of now, the latest version of the popular open source Chemistry Development Kit (CDK) has its own implementation of the highly regarded ECFP and FCFP classes of chemical structure fingerprints (sometimes referred to as circular or Morgan fingerprints). While the general recipe for this kind of fingerprint has been available for awhile, and there are a number of implementations in various different toolkits, this one distinguishes itself in several ways: it has been implemented as closely as possible to the description of the original definition (without having access to the trade secrets that were left out of the paper); it includes resolution of chiral centers; it is freely available as open source Java code; and, last but not least, the algorithm is designed to be as portable as possible, with no major dependencies on specific programming languages or cheminformatics toolkits. [caption id="attachment_7271" align="alignnone" width="603"]
![Building predictive models in CDD Vault](https://www.collaborativedrug.com/hs-fs/hubfs/Imported_Blog_Media/roc_screenshot-1.png?width=603&height=594&name=roc_screenshot-1.png)
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