In drug discovery, understanding the Structure-Activity Relationships (SAR) for large sets of compounds in a clear and concise manner can be both difficult and time-consuming.
Qualitative SAR methods such as Activity Atlas™, Activity Miner™ and R-Group Analysis are invaluable in analyzing and condensing information from large data sets, and are also applicable whenever there is insufficient SAR data for a traditional quantitative SAR approach.
Activity Atlas
Activity Atlas analyzes the SAR of a set of aligned compounds as a function of their 3D electrostatic and shape properties, modeled with the Cresset XED force field. Complex SAR from small or large datasets is summarized into visual 3D maps useful to inform design decisions and to prioritize molecules for synthesis.
Activity Atlas 3D maps tell you what active molecules have in common, which regions you have explored, pinpoint critical regions of SAR and enable you quickly understand complex selectivity data. They are also very useful to decipher relationships among your active molecules and understand how they bind to the active site of the protein of interest, even when you don’t have structural information about your biological target.
Activity Miner
Another powerful qualitative technique to understand activity and selectivity cliffs in your SAR is Activity Miner. This method quickly highlights the activity cliffs in your data set, i.e., pairs of molecules which are highly similar in structure but with a large activity difference. You can explore your data by visualizing the differences in the activity cliff pairs in terms of 2D similarity or 3D similarity based on electrostatic and shape properties, which could translate into changes in the interaction of the ligands with the protein. This can flag up subtle effects that are otherwise easy to overlook.
Activity Miner quickly identifies the most important changes that have been made within a series, by looking at isolated pairs of compounds, following which the entire data set can be examined in Activity Atlas.
Activity Miner offers multiple views of the data to help you find key molecule pairs in your SAR. The different views enable you to focus on different aspects of your SAR.
R-Group Analysis
R-group Analysis can be used to rapidly analyze the substitution pattern of a chemical series to identify all R-group variations around a common core. Tools such as the R-Group Analysis results table, boxplots and heatmaps are useful to investigate the influence on key compound properties such as biological activity or lipophilicity of changing the R-groups at a certain attachment point. They also enable you to quickly identify gaps in the chemical exploration for your compound series, by finding the combinations of most promising substituents you haven’t tried yet.
