U.S. Environmental Protection Agency Office of Research and Development EPA www.epa.gov Hindered phenols are phenols with one or more bulky functional groups ortho to the hydroxyl group. E.g. 3-Chloro-4- hydroxybenzoic acid ( ) Distribution of hindered and non-hindered phenols in the source analog dataset A Systematic Evaluation of Analogs for Read-across Prediction of Estrogenicity Prachi Pradeep1, Kamel Mansouri1, Grace Patlewicz2 and Richard Judson2 1Oak Ridge Institute for Science Education Fellow, National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA 2National Center for Computational Toxicology, Office of Research and Development, U.S. Environmental Protection Agency, Research Triangle Park, NC, USA INTRODUCTION METHODS ANALYSIS ILLUSTRATIVE EXAMPLES CONCLUSIONS Prachi Pradeep l pradeep.prachi@epa.gov l 919-541-5150 Read-across is a data gap filling technique which is commonly used within category and analog approaches to predict a biological property for a target (data-poor) chemical using known information from similar (source analog) chemical(s). Analog identification and evaluation are critical steps in deriving a robust read-across prediction. Potential source analogs are typically identified based on structural similarity. Despite the available frameworks for read-across, few guiding principles exist to help evaluate the scientific validity of any source analogs identified. This case study used a two-tiered approach to analyze structurally related source analogs to read-across estrogenicity for target chemicals of interest. Structural source analogs were identified using 3 different chemical descriptor approaches (Pubchem, Chemotyper and MoSS MCSS) and Tanimoto similarity index as a cut-off. The measured estrogenicity outcomes for the source analogs were then compared with those for the target chemicals to determine the extent of their agreement. A dataset of 2834 phenols as taken from the CERAPP project was used as an inventory of potential source analogs for 2231 hindered phenols (targets). The analysis suggests that none of the 3 descriptor approaches could be considered as an unequivocal method for analog identification for reading across estrogenicity. Analog Selection Method Binding Agreement (%) Number of Target-Analog Pairs Pubchem/ Chemotyper/ MCSS 92.5 87 Chemotyper/ MoSS MCSS 90.0 124 MoSS MCSS 83.9 226 Pubchem/ MoSS MCSS 83.8 136 Chemotyper 67.0 1060 Pubchem/ Chemotyper 63.5 358 Pubchem 59.6 2274 Analog Selection Method Binding Agreement (%) Number of Target-Analog Pairs Chemotyper/ MoSS MCSS 76.5 930 Pubchem/ Chemotyper 76.5 3722 Pubchem/ Chemotyper/ MCSS 76.0 830 Pubchem/ MoSS MCSS 70.0 1780 Chemotyper 69.0 7878 MoSS MCSS 68.0 2314 Pubchem 62.0 19456 Analog Selection Method Number Pubchem Chemotyper MCSS Pubchem/ Chemotyper Pubchem/ MCSS Chemotyper/ MCSS Pubchem/ Chemotyper/ MCSS True Positives (Binders) 502 206 136 172 120 90 90 False Negatives 314 79 50 39 39 19 19 Total Positives 816 285 186 211 159 109 109 True Negatives (Non-binders) 528 148 78 82 64 34 30 False Positives 314 79 50 39 39 19 19 Total Negatives 842 227 128 121 103 53 49 Analog Selection Method Number Pubchem Chemotyper MCSS Pubchem/ Chemotyper Pubchem/ MCSS Chemotyper/ MCSS Pubchem/ Chemotyper/ MCSS True Positives (Binders) 209 94 39 35 25 28 21 False Negatives 25 18 1 10 1 0 0 Total Positives 234 112 40 45 26 28 21 True Negatives (Non-binders) 52 52 13 19 6 8 4 False Positives 152 54 9 11 5 4 2 Total Negatives 204 106 22 40 11 12 6 Number Assay Hindered Non-hindered Total Actives Total Actives Binding 462 207 257 155 Agonist 396 45 204 96 Antagonist 360 46 169 14 Underlying basis for each of the three chemical descriptor approaches Analog Evaluation Method • Select hindered and non-hindered analogs using both: 1. Tanimoto similarity cut-off (0.1 – 0.9), & 2. Number of analogs (1-10) • Analyze the consistency in experimental estrogenic