RosettaAntibody generated models for a dataset of 49 antibody-Fv structures

<p><strong>Structures of antibody-Fv domains computationally generated by RosettaAntibody based on the protocol of </strong><a href="https://www.nature.com/articles/nprot.2016.180?proof=true&amp;draft=marketing">Weitzner, Jeliazkov, Lyskov et al.</a><strong> (Nature Protocols 12, 401&ndash;416, 2017). There are 49 antibody targets, with about 2800 decoy structures provided per antibody. A table is also provided with the H3-loop rmsd of each structure from the experimental crystal structure.</strong></p> <p><strong>These structures can be used to evaluate whether a score function can identify the near-native structures from the pool of decoys. These structures can also be used for comparison with other sets of structures generated by other antibody structure prediction programs.</strong></p> <p><strong>The&nbsp;research study on this set is unpublished and a manuscript is under preparation. Please cite Jeliazkov, Frick, Zhou &amp; Gray, &ldquo;Robustification of RosettaAntibody and Rosetta SnugDock,&rdquo; in preparation, 2020.</strong></p> <p><strong>The homology modeling stage of RosettaAntibody was run with stringent homolog exclusion settings, excluding CDR templates of over 95% identity and FR templates of over 90% identity. The H3 modeling stage was run as described by <a href="https://www.nature.com/articles/nprot.2016.180">Weitzner, Jeliazkov, Lyskov et al.</a> (Nature Protocols 12, 401&ndash;416, 2017).&nbsp;</strong></p> <p><strong>The set of 49 antibody-Fv domains was originally compiled by <a href="https://academic.oup.com/peds/article/29/10/409/2462315">Marze et al. </a>(Protein Eng. Des. Sel. 29(10), 409-418, 2016). The dataset was first used to evaluate CDR-H3 loop rmsds in <a href="https://www.jimmunol.org/content/early/2016/11/18/jimmunol.1601137">Weitzner and Gray </a>(J. Immunology 198(1):505-515, 2017).</strong></p> <p><strong>The dataset can be extracted on a linux interface using:&nbsp;</strong></p> <p><strong>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;tar -xvzf <a href="https://www.zenodo.org/api/files/c2ba9da2-0d46-4aba-adbf-8ddd39b52b29/decoys_rosettaantibody_20200323.tar.gz?versionId=df264fc5-c79c-47b4-82bf-d1cda1e025e2">decoys_rosettaantibody_20200323.tar.gz</a>&nbsp;</strong></p> <p><strong>When extracted the output comprises RosettaAntibody generated models for 49 antibodies in the format:</strong></p> <p><strong>&lt;Antibody pdb id&gt; / model-&lt;id 1&gt;.relaxed_&lt;id 2&gt;.pdb.gz</strong></p> <p><strong>The Rosetta &quot;ref2015&quot; scores (ref2015_score) and rmsd of the H3 loop (h3_rmsd) for every model (model) is&nbsp;provided in model_scores_and_rmsds.txt . RMSDs are calculated with respect to the corresponding crystal structure (pdb id) over all heavy atoms in the h3 loop (93&ndash;102 in Chothia numbering) after superposition of the framework residues. ID 1 comes from the homology model source (lower is better). ID 2 indicates the loop model.</strong></p> <p><strong>The decoy PDB files contain additional metrics following the ATOM records such as VH&ndash;VL relative orientation metrics (from Marze et al.) and per-residue Rosetta scores. Caveat: the &ldquo;RMS&rdquo; values reported within the decoy files were calculated against the input homology model and not the crystal structures (whereas the model_rmsds.txt file contains the H3 rmsds w.r.t. crystal).</strong></p>