Publication details
ValTrendsDB: Enabling comparison of quality and features of biomacromolecular complexes to the global trend
| Authors | |
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| Year of publication | 2019 |
| Type | Conference abstract |
| MU Faculty or unit | |
| Citation | |
| Description | Models of biomacromolecules are assembled from experimentally measured data, which can invite errors. Some structure models were found to be erroneous to the point of retracting articles with conclusions based on these models. The community began developing and using methodologies for validation of structure models. This focus of quality had us wondering whether it has any impact on quality of newer structures. To provide food for thought regarding this inquiry (and several others), we have carried out a wide range exploratory analysis of trends in relationships of pairs of factors that represent quality and features of biomacromolecules and ligands. Data from the PDB database, as well as our own ValidatorDB database that contains ligand validation information, have been transformed into 88 factors for the analysis. We expected some of the discovered trends (e.g., newer structures have better quality), while others surprised us (e.g., ligand quality is stagnant at best). Complete results of our analysis are available in the weekly updated ValTrendsDB database (ncbr.muni.cz/ValTrendsDB). Users of the database can view factor-pair plots of all explored relationships, including those that provided us with interesting trends. An important functionality of ValTrendsDB is visualization of data points, which represent one or more PDB entries, into factor-pair plots served by the database as results of the exploratory analysis. This way, users can compare quality and features of their structure(s) of interest to the trends across the whole PDB database |
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