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The authors also introduce a multiple reference scoring scheme by creating a frequency-weighted fingerprint from many reference structures.
With respect to the scoring, we wanted to incorporate the lessons learned from studies such as [14], e.g. usage of multiple reference scoring coupled with frequency based weighting of the interactions.
Besides, the good performance of the PADIF approaches demonstrates that (1) it is legitimate and useful to exploit the per atom score contributions of GOLD scoring functions for building interaction fingerprints and (2) that the employed multiple reference scoring combined with frequency based weighting seems to be a robust and promising way for ranking poses.
For PADIF, a multiple reference scoring was employed (reference complexes in Additional file 1: S3).
For the Bissantz ER-receptor test set, the applied scoring schemes yielded significant improvement compared to Goldscore, and multiple reference scoring seemed to outperform the single reference scoring [14].
Alternatively, the ChemSpider Combined Reference Scoring term ((S_{C_{{mathrm{CCR}}}})) can be calculated, as shown below in Eqs.
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The reference information was included using the combined reference scores introduced in Eqs.
The reference score was calculated with the number of patents (PNP) and PubMed references (PPC).
The reference score was calculated with the ChemSpider reference count (CRC).
The plot shows improved performances of the proposed metric in matching the full reference score.
The SPV was not opacified in any cases for which the CTA reference score confirmed cerebral circulation arrest.
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