Published December 14, 2019
| Version 1.0
Dataset
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Compound database and subsets generated by the fragment network for stage 3 of the PHIP2 SAMPL7 Challenge
- 1. Informatics Matters
- 2. University of Oxford
- 3. University of California, Irvine
- 4. Memorial Sloan Kettering Cancer Center
Description
The fragment network provides a convenient way to filter-out compounds that are dissimilar to the input hit(s). Overall, this search algorithm requires a compound input and 3 parameters: 1- the number of graph traversals (hops), 2- number of changes in heavy atom count (hac), 3- number of changes in ring atoms counts (rac). Please, read the reference (Hall, Murray and Verdonk, 2017) for the specifics of the methods.
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Additional details
References
- Hall, R., Murray, C. and Verdonk, M. (2017). The Fragment Network: A Chemistry Recommendation Engine Built Using a Graph Database. Journal of Medicinal Chemistry, 60(14), pp.6440-6450.