Visible analysis was employed for receptor evaluation since AUC values from ROC curves were too very similar. in row 1. For every stop of 10 rows; the least (in green), standard (in white), and optimum (in crimson) values from the absolute rates were calculated and colored. More predictive targets have more green and white in each block and less red, they have more blocks (the subsequent Virtual Screens of the SAMPL4 compounds). For example, about a dozen different sets of interaction-based filters were investigated for the LEDGF results, and two particular filters were selected, since they harvested a reasonable number of docked modes per target for visual inspection. For the LEDGF site, the filter requirements consisted of a minimum of 2 predicted hydrogen bonds to IN, and either: (-)-Borneol (Fa) a hydrogen bond with Glu170; or (Fb) a hydrogen bond to the backbone amino group of His171 (similar to the ALLINIs). The method used for choosing receptors for virtual screening of the IN models for the LEDGF site described here is the same for the FBP site. For each LEDGF target, the top-ranked docked mode of all of the positive control ligands (from all 3 sites) that exceeded a particular filter were sorted according to the estimated Free Energy of Binding as calculated by AD Vina. This sorting process determined the for each compound whether they be known LEDGF-site binders or decoys (observed to bind at the FBP or Y3 sites). The ligands that crystallized in the LEDGF site were then extracted from that sorted list, and their order in that LEDGF-site specific list decided their visualization process formalized into our Rank Difference Ratio (RDR) procedure where the relative ranking of the appropriate positive control ligands was used with the corresponding absolute ranking as the Rank Difference Ratio metric for a receptor and are the absolute and relative rankings, respectively, for ligand procedure. For targets that displayed comparable RDR values using a particular filter, receptor models were selected to maximize structural diversity. Further, if two forms of a structure had a difference of total number of LEDGF-site hits less than 2, the receptor model with the lower RDR value was chosen. A similar strategy was used to select the FBP targets. For the small set of Y3 receptor models, the median statistic of rankings was sufficient to choose the best receptor model, 3NF8_B. Open in a separate window Physique 4 Hydrogen bond interactions of “type”:”entrez-protein”,”attrs”:”text”:”AVX17561″,”term_id”:”1375985333″,”term_text”:”AVX17561″AVX17561 (sticks with green carbon atoms) docked with the LEDGF KCY antibody site (white ribbon) of HIV integrase. Three residues (sticks with pink carbon atoms) are shown with hydrogen bonds (magenta dotted lines) to the ligand model. Two hydrogen bonds (Glu170 and His171) were required by the conversation filters. The set of 106 receptor models representing the FBP, LEDGF, and Y3 sites enabled the selection of the following (-)-Borneol number of targets per site: 6 crystal structures of the LEDGF site, 6 structures of the FBP site, and 1 crystal structure of the Y3 site. The LEDGF targets selected were: 3ZSO_B, 3ZT4_B, 3ZT1_A, 3ZT3_A, 3NF8_A, and 3ZCM_A.[25,26] The FBP targets selected were: 3AO1, 3AO2, 3VQD, 3VQE_A, 3VQ4, and 3VQ7.[27,28] The Y3 target selected was 3NF8_B.[26] Virtual Screen of the SAMPL4 compounds using AutoDock Vina AutoDock Vina (AD Vina) was used to screen the SAMPL4 compound library against these (-)-Borneol 13 receptor models of IN.[24] See Determine 5 for a summary of the workflow used for the LEDGF targets. A similar strategy was utilized for the FBP and Y3 sites. The same grid box size, location, and settings for AD Vina from the positive controls were also used in these Virtual Screens (see Physique 3). The 321 compounds provided by SAMPL4 were used as inputs by the Levy Lab for LigPrep and Epik [29,30] at a pH of 7 2, which generated additional tautomers and protonation says of some compounds to produce a final set of 451 models of the SAMPL4 compounds. All 451 ligand models of the compounds were docked against the 6 LEDGF targets, 6 FBP targets, and 1 Y3 target, using the TSRI Linux cluster. The same filters used in the positive control dockings were applied to the results of the SAMPL4 dockings. Open in a separate window Physique 5 Selection of the 6 crystal structures that.4). block and less red, they have more blocks (the subsequent Virtual Screens of the SAMPL4 compounds). For example, about a dozen different sets of interaction-based filters were investigated for the LEDGF results, and two particular filters were selected, since they harvested a reasonable number of docked modes per target for visual inspection. For the LEDGF site, the filter requirements consisted of a minimum of 2 predicted hydrogen bonds to IN, and either: (Fa) a hydrogen bond with Glu170; or (Fb) a hydrogen bond to the backbone amino group of His171 (similar to the ALLINIs). The method used for choosing receptors for virtual screening of the IN models for the LEDGF site described here is the same for the FBP site. For each LEDGF target, the top-ranked docked mode of all of the positive control ligands (from all 3 sites) that exceeded a particular filter were sorted according to the estimated Free Energy of Binding as calculated by AD Vina. This sorting process determined the for each compound whether they be known LEDGF-site binders or decoys (observed to bind at the FBP or Y3 sites). The ligands that crystallized in the LEDGF site were then extracted from that sorted list, and their order in that LEDGF-site specific list decided their visualization process formalized into our Rank Difference Ratio (RDR) procedure where the relative ranking of the appropriate positive control ligands was used with the corresponding absolute ranking as the Rank Difference Ratio metric for a receptor and are the absolute and relative rankings, respectively, for ligand procedure. For targets that displayed comparable RDR values using a particular filter, receptor models were selected to maximize structural diversity. Further, if two forms of a structure had a difference of total number of LEDGF-site hits less than 2, the receptor model with the lower RDR value was chosen. A similar strategy was used to select the FBP targets. For the small set of Y3 receptor models, the median statistic of rankings was sufficient to choose the best receptor model, 3NF8_B. Open in a separate window Physique 4 Hydrogen bond interactions of “type”:”entrez-protein”,”attrs”:”text”:”AVX17561″,”term_id”:”1375985333″,”term_text”:”AVX17561″AVX17561 (sticks with green carbon atoms) docked with the LEDGF site (white ribbon) of HIV integrase. Three residues (sticks with pink carbon atoms) are shown with hydrogen bonds (magenta dotted lines) to the ligand model. Two hydrogen bonds (Glu170 and His171) were required (-)-Borneol by the conversation filters. The set of 106 receptor models representing the FBP, LEDGF, and Y3 sites enabled the selection of the following number of targets per site: 6 crystal structures of the LEDGF site, 6 structures of the FBP site, and 1 crystal structure of the Y3 site. The LEDGF targets selected were: 3ZSO_B, 3ZT4_B, 3ZT1_A, 3ZT3_A, 3NF8_A, and 3ZCM_A.[25,26] The FBP targets selected were: 3AO1, 3AO2, 3VQD, 3VQE_A, 3VQ4, and 3VQ7.[27,28] The Y3 target selected was 3NF8_B.[26] Virtual Screen of the SAMPL4 compounds using AutoDock Vina AutoDock Vina (AD Vina) was used to screen the SAMPL4 compound library against these 13 receptor models of IN.[24] See Determine 5 for a summary of the workflow used for the LEDGF targets. A similar strategy was utilized for the FBP and Y3 sites. The same grid box size, location, and settings for AD Vina from the positive controls were also used in these Virtual Screens (see Physique 3). The 321 compounds provided by SAMPL4 were used as inputs by the Levy Lab for LigPrep and Epik [29,30] at a pH of 7 2, which generated additional tautomers and protonation says of some compounds to produce a final set of 451 models of the SAMPL4 compounds. All 451 ligand models of the compounds were docked against the 6 LEDGF targets, 6 FBP targets, and 1 Y3 target, using the TSRI Linux cluster. The same filters used in the positive control dockings were applied to the results of the SAMPL4 dockings. Open in a separate window Physique 5 Selection of the 6 crystal structures that were used as targets for the LEDGF site during the Virtual Screen of the SAMPL4 compounds. The X-axis indicates the number of docked models of LEDGF ligands that exceeded through a particular filter during the positive control cross-docking experiments, while the Y-axis plots the Rank Difference Ratio metric that quantifies how well the LEDGF ligands ranked, in relation to the FBP.