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A Simple Representation Of Three-Dimensional Molecular Structure
[article]
2017
bioRxiv
pre-print
Statistical and machine learning approaches predict drug-to-target relationships from 2D small-molecule topology patterns. One might expect 3D information to improve these calculations. Here we apply the logic of the Extended Connectivity FingerPrint (ECFP) to develop a rapid, alignment-invariant 3D representation of molecular conformers, the Extended Three-Dimensional FingerPrint (E3FP). By integrating E3FP with the Similarity Ensemble Approach (SEA), we achieve higher precision-recall
doi:10.1101/136705
fatcat:spjnyzatzvcfri5insngzrysvm