PBmapclust: Mapping and Clustering the Protein Conformational Space Using a Structural Alphabet
| dc.contributor.author | Vetrivel, Iyanar | en_US |
| dc.contributor.author | Hoffmann, Lionel | en_US |
| dc.contributor.author | Guegan, Sean | en_US |
| dc.contributor.author | Offmann, Bernard | en_US |
| dc.contributor.author | Laurent, Adele D. | en_US |
| dc.contributor.editor | Byska, Jan and Krone, Michael and Sommer, Björn | en_US |
| dc.date.accessioned | 2019-06-02T18:25:27Z | |
| dc.date.available | 2019-06-02T18:25:27Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | Analyzing the data from molecular dynamics simulation of biological macromolecules like proteins is challenging. We propose a simple tool called PBmapclust that is based on a well established structural alphabet called Protein blocks (PB). PBs help in tracing the trajectory of the protein backbone by categorizing it into 16 distinct structural states. PBmapclust provides a time vs. amino acid residue plot that is color coded to match each of the PBs. Color changes correspond to structural changes, giving a visual overview of the simulation. Further, PBmapclust enables the user to "map" the conformational space sampled by the protein during the MD simulation by clustering the conformations. The ability to generate sub-maps for specific residues and specific time intervals allows the user to focus on residues of interest like for active sites or disordered regions. We have included an illustrative case study to demonstrate the utility of the tool. It describes the effect of the disordered domain of a HSP90 co-chaperone on the conformation of its active site residues. The scripts required to perform PBmapclust are made freely available under the GNU general public license. | en_US |
| dc.description.sectionheaders | Session 2 | |
| dc.description.seriesinformation | Workshop on Molecular Graphics and Visual Analysis of Molecular Data | |
| dc.identifier.doi | 10.2312/molva.20191097 | |
| dc.identifier.isbn | 978-3-03868-085-7 | |
| dc.identifier.pages | 23-27 | |
| dc.identifier.uri | https://doi.org/10.2312/molva.20191097 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/molva20191097 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | Applied computing | |
| dc.subject | Molecular structural biology | |
| dc.subject | Bioinformatics | |
| dc.subject | Computational proteomics | |
| dc.title | PBmapclust: Mapping and Clustering the Protein Conformational Space Using a Structural Alphabet | en_US |