A Review of Sentira
Sentira is a new chemical data visualisation tool from Optibrium. The focus is on ease of use data visualisation and as such is probably targeted at the bench scientist rather than a specialist computational scientist. Sentira cannot itself calculate any molecular properties however it does contain a calculator that would allow the user to generate algorithms using precalculated properties and then put them in a new column.
A range of file types can be imported including sdf, ski, txt, csv, and mol, in addition to the native Sentira files (skd) and Stardrop .add files, it should be noted that Autodesk Autosketch 2D files also use the skd file extension. Reading a 5700 structure file with 40 associated data fields took around 10 seconds. I also imported a file containing all the ChEMBL 19 molecules (1.4 million structures), the import was very slow. I waited for about 40 mins and then left the import overnight, by morning all structures had been imported, I then tried a few operations but even scrolling was rather jerky on such a large data set, looking in Activity Monitor it seems that there is not support for multiple processors. The datasets contained a wide variety of structures, some complex macrocyclic natural products, and all were laid out and rendered very nicely. As well as saving as a Sentira file you can also export as sdf, ski, txt, csv, and Stardrop files.
As far as I could tell there is no means to link directly to a SQL database (ODBC or JDBC).
Sentira is capable of displaying a variety of plot types, if you want to display multiple plots click on the button in the bottom right corner (highlighted in the image above) and the plot will reopen in a separate window but still maintain a live link to the table data and other plots.
- 2D and 3D scatter plots
- Pie charts
- Box plots
- Radar plots
- Receiver operating characteristic plots
You can display multiple plots simultaneously and if you make selections in any plot to see the corresponding compounds instantly highlighted in the data table and all other plots you have displayed. On datasets of several thousand structures the rotations of the 3D scatterplots were smooth and responsive. It is very easy to change the plot layout/colours/fonts/labels/axes etc, simply right-click on the element you want to modify. One nice feature is that you can annotate the plots allowing you identify specific compounds, the plots can be copied or exported as static images for incorporating into presentations. It is important to note they are exported as images, the underlying data is not exported with the image.
Structure Activity relationships can be investigated using an easy-to-use R-group analysis tool, first select the scaffold on a representative structure and the R-groups are identified automatically and displayed in the table. If all the R-group positions are not present in the selected structure you can manually add more.
You can then sort the tables and visualise the impact of variations to R-groups, linkers, atoms or fragments on compound properties using histograms, box plots
It is also possible to look at the influence of a pair of substituents by using the SAR plot shown below. This plot can also be modified to colour by another property of the molecule, in the example below I’ve chosen calculated LogP. This sort of plot is also useful for spotting missing examples in a series that you might want to make.
You can also use matched molecular pair analysis or the series to identify replacements with a consistent impact on compound properties or activity.
There are a number of videos giving demonstrations on the website.
This is an interesting and simple to use desktop tool for exploring a chemical dataset, it handles reasonably sized datasets easily and would be ideal for looking at project data but would struggle when trying to evaluate the result from a high-throughput screening campaign. The R-group analysis and matched pairs analysis are useful tools and would be sufficient for most needs. This tool would also be useful for organising project data for preparing presentations.
Last updated 12 August 2014