<p>This is a data repository for a large study that involved the analysis and prediction of homotypic (self-self) transmembrane domain interactions.</p>
<p>Publication:
- Yao Xiao, Bo Zeng, Nicola Berner, Dmitrij Frishman, Dieter Langosch, Mark George Teese
- Experimental determination and data-driven prediction of homotypic transmembrane domain interfaces
- Computational and Structural Biotechnology Journal
- Volume 18, 2020, Pages 3230-3242
- ISSN 2001-0370
- <a href="https://doi.org/10.1016/j.csbj.2020.09.035" rel="nofollow">https://doi.org/10.1016/j.csbj.2020.09.035</a></p>
<p>Contributors:
- Yao Xiao
- Bo Zeng
- Mark Teese
- Dieter Langosch
- Dmitrij Frishman</p>
<p>Contact:</p>
<ul>
<li>Mark Teese</li>
</ul>
<p>Affiliation:</p>
<ul>
<li><a href="https://www.tum.de/en/" rel="nofollow">Technical University of Munich</a></li>
<li><a href="https://www.tngtech.com/en/index.html" rel="nofollow">TNG Technology Consulting GmbH</a></li>
</ul>
<p>Related website with machine-learning tool:
- <a href="http://www.thoipa.org" rel="nofollow">www.thoipa.org</a></p>
<p>Related open-source software repositories:</p>
<ul>
<li><a href="https://github.com/bojigu/thoipapy" rel="nofollow">THOIPApy code repository</a></li>
<li><a href="https://bitbucket.org/yaoxiaorepos/datoxr" rel="nofollow">datoxr code repository</a></li>
<li><a href="https://github.com/teese/pytoxr" rel="nofollow">pytoxr code repository</a></li>
</ul>
<p>Open Science Foundation Repository Contents:</p>
<ul>
<li>data</li>
<li>THOIPA_data.7zip<ul>
<li>homologues (BLAST data files and alignments)</li>
<li>interface_predictions (predictions from THOIPA, PREDDIMER, TMDOCK used for validation)</li>
<li>interface_residues (experimental data on TM homodimer interfaces from NMR, ETRA, and crystal structure experiments)</li>
<li>residue_properties (data on conservation, polarity, coevolution etc calculated for each residue of each TMD in each dataset)</li>
<li>THOIPA_validation (raw validation data (ROC AUC, etc) for the THOIPA machine learning predictor. Also contains the machine-learning model, training_data, and feature importances)</li>
</ul>
</li>
<li>protein_lists<ul>
<li>[list of proteins in homotypic TM dataset, and also individual datasets. includes sequences in fastA format]</li>
</ul>
</li>
<li>figures</li>
<li>DDR2 results and other scanning mutagenesis data</li>
<li>methods</li>
<li>hydrophobicity scales and other data related to methods</li>
</ul>
<p>Data notes:</p>
<ul>
<li>The following sets of proteins are included in the protein_lists folder</li>
<li>set05 : homotypic TMD dataset (combined ETRA, NMR, X-ray)</li>
<li>set07 : test data for machine learning</li>
<li>set08 : train data for machine learning</li>
<li>folders labelled "old, deprecated data" refer to an older machine-learning model, trained on a slightly modified set05.</li>
<li>the hierarchical data structure in THOIPA_data.7zip should in most cases be self-explanatory. Also, references and code for the processing of each file can be found in <a href="https://github.com/bojigu/thoipapy" rel="nofollow">thoipapy software</a> version 1.1.3. Most data can be recreated using the open-source thoipapy software.</li>
</ul>
