Docking results for CSAR complex ‘set1_120’.

<p>Top left: Experimental structure of PDB: 1IUP, coded as CSAR datapoint ‘set1_120’. Waters (Oxygen only) are shown as red spheres. Black lines represent polar contacts predicted by PyMOL. Top right and bottom row: native ligand (lines) and waters (spheres) are shown in grey for comparison. Docked waters are shown as sticks (note that Rosetta adds hydrogens). Docked ligands are shown in cyan, yellow, and green. For each study the models were sorted by total score, then interface energy. The first model with RMSD <2.0 Å is depicted. Its position in the sorted list (rank) and its RMSD to native are shown.</p

P-values calculated using a one-tailed binomial distribution.

<p>Probabilities in columns 2–3 are extrapolated using best-fit lines from <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067536#pone-0067536-g006" target="_blank">Figure 6</a> assuming 1000 models are produced. Probabilities in columns 4–5 were observed for N = 400 (from Table S3 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067536#pone.0067536.s001" target="_blank">File S1</a>, last row). Whether p-values are calculated using extrapolated probabilities or probabilities observed for N = 400, it is clear that changes in docking success cannot be attributed to chance.</p

Probability of changes in CSAR docking success upon replication of docking study.

<p>Success is measured as whether the top scoring model by interface score has a ligand pose within 2.0 Å RMSD of the native pose. As sampling size increases, the probability that resampling with would change the outcome of docking decreases. Equations for the best-fit lines are available in Table S4 in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067536#pone.0067536.s001" target="_blank">File S1</a>.</p

Using RosettaLigand for Small Molecule Docking into Comparative Models

<div><p>Computational small molecule docking into comparative models of proteins is widely used to query protein function and in the development of small molecule therapeutics. We benchmark RosettaLigand docking into comparative models for nine proteins built during CASP8 that contain ligands. We supplement the study with 21 additional protein/ligand complexes to cover a wider space of chemotypes. During a full docking run in 21 of the 30 cases, RosettaLigand successfully found a native-like binding mode among the top ten scoring binding modes. From the benchmark cases we find that careful template selection based on ligand occupancy provides the best chance of success while overall sequence identity between template and target do not appear to improve results. We also find that binding energy normalized by atom number is often less than −0.4 in native-like binding modes.</p> </div

RMSD vs Rosetta interface score for CSAR predictions.

<p>Each plot contains the top 100 Rosetta models by total score for both standard (red) and water (blue) docking for particular CSAR datapoint. Each plot is identified by its CSAR label (e.g ‘set1_91’). CSAR labels are followed by rank before and after water docking. Ranks of ‘n/a’ indicate that no model below 2 Å RMSD was sampled by Rosetta. Each set of 3 plots represent the largest rank changes seen in that category. Successes are defined as ranks that decrease and failures as ranks that increase.</p

Towards Ligand Docking Including Explicit Interface Water Molecules

<div><p>Small molecule docking predicts the interaction of a small molecule ligand with a protein at atomic-detail accuracy including position and conformation the ligand but also conformational changes of the protein upon ligand binding. While successful in the majority of cases, docking algorithms including RosettaLigand fail in some cases to predict the correct protein/ligand complex structure. In this study we show that simultaneous docking of explicit interface water molecules greatly improves Rosetta’s ability to distinguish correct from incorrect ligand poses. This result holds true for both protein-centric water docking wherein waters are located relative to the protein binding site and ligand-centric water docking wherein waters move with the ligand during docking. Protein-centric docking is used to model 99 HIV-1 protease/protease inhibitor structures. We find protease inhibitor placement improving at a ratio of 9∶1 when one critical interface water molecule is included in the docking simulation. Ligand-centric docking is applied to 341 structures from the CSAR benchmark of diverse protein/ligand complexes <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0067536#pone.0067536-Dunbar1" target="_blank">[1]</a>. Across this diverse dataset we see up to 56% recovery of failed docking studies, when waters are included in the docking simulation.</p></div

RMSD and rank comparisons between standard and protein-centric water docking of HIV-1 PR/PI.

<p>Left panel: RMSD of top scoring Rosetta model. 69 models fall below the diagonal (improved RMSDs) while 30 lie above it. Red dashed lines represent the 2 Å RMSD metric for successful docking. Predictions in the lower-right quadrant turn from failures to successes up on water docking. Upper-left quadrant contains predictions that succeeded without water docking and fail with water docking. Right panel: rank of the lowest scoring Rosetta model with RMSD under 2 Å. Where multiple HIV-1 cross-docking predictions achieved the same rank with and without water docking, these points are replaced with text indicating the number of overlapping points.</p

Comparison of protocols for the 2 benchmark studies presented in this paper.

<p>Comparison of protocols for the 2 benchmark studies presented in this paper.</p

Relation between binding pocket crowdedness and the improvements in CSAR model ranking when water is docked.

<p>Crowdedness is calculated as the number of ligand/protein contacts divided by the total number of ligand atoms. Datapoints with rank changes between −10 and 10 were omitted to focus on data where water docking makes a large impact on results. Note that below a crowdedness threshold of 2, addition of water rarely worsens rank.</p

Docking results for CSAR complex set1_181.

<p>Top: experimental structure with ligand in blue, water as a red sphere, and polar contacts as black dashed lines. 22 polar contacts are predicted by PyMOL, 4 of which contact the water molecule. Middle: Top scoring model from docking without water. Native ligand and water in grey, Rosetta model in cyan. PyMOL predicts 16 polar contacts. Bottom: Lowest RMSD model from docking with loose waters. Rosetta model shown in green. No model within the top 100 by total energy score has RMSD <2.0 Å (hence rank is ‘n/a’). Shown is the lowest RMSD structure. PyMOL predicts 11 polar contacts (1 with water).</p