J)21Ti specifies the rotation needed to generate prediction j starting from prediction i. Equation 5 is an analytical expression and can be evaluated rapidly. Because we use fixed sets of angles in our docking algorithm ZDOCK (thus with fixed rotation matrices T), we can pre-compute the lists of the closest neighbors for each rotation and use the results to evaluate the predictions of any docking run.ResultsIn Figure 1 we plot the RMSD against the angular distance between the top ZDOCK prediction of the 1BJ1 25033180 complex and 2000 predictions (top 1000 and bottom 1000 according toAngular Distance in Protein-Protein DockingFigure 9. Average hit count for 156 and 66 rotational sampling, the Intercept and Slope funnel properties (based on 10 closed neighbors using angular distance), and the scores and properties combined in a weighted linear function (training and testing using 22-fold cross validation). doi:10.1371/journal.pone.0056645.g17 of the angle sets of a standard 6u sampling run (68,760 angle sets), or a 6-fold reduction in total computational time. Figure 3 shows the SR of both the standard 6u sampling and the 15u/6u hybrid-resolution runs. The performances are nearly identical, with ISR = 0.239 for the hybrid-resolution and 0.241 for the standard 6u sampling run. Figure 4 shows the AHC, which is also nearly identical for the standard and hybrid-resolution runs. Previously we showed that there was a tradeoff between SR and AHC: decreasing the total number of predictions increases the SR and decreases the AHC and vice versa [20]. However, we see fromFigures 3 and 4 that with the hybrid-resolution approach we can reduce the number of predictions by a factor of about 10 PS-1145 chemical information compared with a standard 6u sampling run while maintaining the same performance as measured by SR and AHC. To further analyze the performance of the hybrid-resolution approach, we compared for each complex in our test set the best prediction obtained using the standard approach (uniform 6u rotational sampling) with the best prediction obtained using the hybrid-resolution approach. The best prediction of a set is defined as that with the lowest interface RMSD (IRMSD) from the boundTable 1. ISR’s for funnel properties obtained using angular distance or RMSD.Angular N 5 10 15 20 30 50 100 150 200 Intercept 0.072 0.293 0.255 0.247 0.236 0.228 0.218 0.215 0.Angular Slope 0.062 0.290 0.248 0.251 0.236 0.233 0.223 0.219 0.Angular Average score 0.210 0.212 0.209 0.206 0.202 0.196 0.188 0.181 0.RMSD Intercept 0.200 0.239 0.244 0.237 0.237 0.228 0.212 0.204 0.RMSD Slope 0.202 0.245 0.252 0.242 0.249 0.236 0.229 0.223 0.RMSD Average score 0.216 0.209 0.199 0.198 0.192 0.184 0.173 0.166 0.N is the number of the closest neighbors used to calculate the properties. The best prediction for each property is in bold. doi:10.1371/journal.pone.0056645.tAngular Distance in Protein-Protein Dockingcomplex [5]. In Figure 5 we show the best prediction among the top 100 and the top 1000 predictions (by ZDOCK score) respectively, for each test case. We see that for both the top 100 and the top 1000 predictions, most of the IRMSD’s lie on the diagonal, which indicates that the best predictions of the two buy POR8 approaches are very similar. For the top 100 predictions (Figure 5 top), the best predictions obtained with the two approaches differ only for a few test cases, mostly from the `others’ category. The overall performance is very similar, indicated by the similar number of points above and below the d.J)21Ti specifies the rotation needed to generate prediction j starting from prediction i. Equation 5 is an analytical expression and can be evaluated rapidly. Because we use fixed sets of angles in our docking algorithm ZDOCK (thus with fixed rotation matrices T), we can pre-compute the lists of the closest neighbors for each rotation and use the results to evaluate the predictions of any docking run.ResultsIn Figure 1 we plot the RMSD against the angular distance between the top ZDOCK prediction of the 1BJ1 25033180 complex and 2000 predictions (top 1000 and bottom 1000 according toAngular Distance in Protein-Protein DockingFigure 9. Average hit count for 156 and 66 rotational sampling, the Intercept and Slope funnel properties (based on 10 closed neighbors using angular distance), and the scores and properties combined in a weighted linear function (training and testing using 22-fold cross validation). doi:10.1371/journal.pone.0056645.g17 of the angle sets of a standard 6u sampling run (68,760 angle sets), or a 6-fold reduction in total computational time. Figure 3 shows the SR of both the standard 6u sampling and the 15u/6u hybrid-resolution runs. The performances are nearly identical, with ISR = 0.239 for the hybrid-resolution and 0.241 for the standard 6u sampling run. Figure 4 shows the AHC, which is also nearly identical for the standard and hybrid-resolution runs. Previously we showed that there was a tradeoff between SR and AHC: decreasing the total number of predictions increases the SR and decreases the AHC and vice versa [20]. However, we see fromFigures 3 and 4 that with the hybrid-resolution approach we can reduce the number of predictions by a factor of about 10 compared with a standard 6u sampling run while maintaining the same performance as measured by SR and AHC. To further analyze the performance of the hybrid-resolution approach, we compared for each complex in our test set the best prediction obtained using the standard approach (uniform 6u rotational sampling) with the best prediction obtained using the hybrid-resolution approach. The best prediction of a set is defined as that with the lowest interface RMSD (IRMSD) from the boundTable 1. ISR’s for funnel properties obtained using angular distance or RMSD.Angular N 5 10 15 20 30 50 100 150 200 Intercept 0.072 0.293 0.255 0.247 0.236 0.228 0.218 0.215 0.Angular Slope 0.062 0.290 0.248 0.251 0.236 0.233 0.223 0.219 0.Angular Average score 0.210 0.212 0.209 0.206 0.202 0.196 0.188 0.181 0.RMSD Intercept 0.200 0.239 0.244 0.237 0.237 0.228 0.212 0.204 0.RMSD Slope 0.202 0.245 0.252 0.242 0.249 0.236 0.229 0.223 0.RMSD Average score 0.216 0.209 0.199 0.198 0.192 0.184 0.173 0.166 0.N is the number of the closest neighbors used to calculate the properties. The best prediction for each property is in bold. doi:10.1371/journal.pone.0056645.tAngular Distance in Protein-Protein Dockingcomplex [5]. In Figure 5 we show the best prediction among the top 100 and the top 1000 predictions (by ZDOCK score) respectively, for each test case. We see that for both the top 100 and the top 1000 predictions, most of the IRMSD’s lie on the diagonal, which indicates that the best predictions of the two approaches are very similar. For the top 100 predictions (Figure 5 top), the best predictions obtained with the two approaches differ only for a few test cases, mostly from the `others’ category. The overall performance is very similar, indicated by the similar number of points above and below the d.