Instantly understand and explore the structure-activity relationships in your chemical series
Analysing structure-activity relationships (SAR) using R-group analysis or computational methods such as clustering, matched pair and activity landscape analyses produces valuable information to guide compound optimisation. StarDrop displays these results in a visually intuitive way, making it easy for everyone to interpret the results and quickly draw conclusions.
StarDrop includes a flexible tool to automatically perform R-group decompositions.
- Analyse chemical series: visualise the impact of variations to R-groups, fragments or linkers on compound properties.
- Analyse SAR simultaneously across multiple scaffolds: identify consistent patterns or the impact of scaffold hopping.
- Link to data visualisations and chemical spaces: enabling you to easily explore the relationships between structural variations and property distributions or instantly create SAR tables.
- Enumerate a full, combinatorial library: explore the properties of compounds that have not yet been synthesised and identify potential missed opportunities.
- Perform matched pair analysis: within a chemical series to identify key substitutions that have a significant impact on a compound’s properties.
Matched Molecular Pairs
StarDrop provides a generalised matched molecular pair analysis tool, integrated with Card View. The matched pairs method identifies pairs of molecules that differ only by replacement of a single, small contiguous fragment. The analysis provides a simple way to identify and assess transformations based on your data. You can identify which transformations have been made, how common these are and what affect they have on properties.
Investigate all pair-wise comparisons for a full data set, or focus on exploring the neighbourhood around a reference compound by highlighting all the matched molecular pairs for this compound.
Matched pair analysis, for example, helps you to identify strategies for lead optimisation by identifying transformations that provide a consistent, significant improvement in a property of interest.
Activity Landscapes and Neighbourhoods
StarDrop provides tools to identify a compound’s nearest neighbours or analyse the activity landscape across a whole data set. Fully integrated with Card View, these analyses construct a network of similar compounds and highlight large variations in properties.
- Identify activity cliffs
- Find regions of high variation in activity with interesting SAR
- Spot regions of ‘flat’ SAR which may limit the potential to optimise activity or present opportunities to optimise other properties without negatively impacting activity
Cluster groups of ‘similar’ compounds together, for example to identify chemical series within a data set of diverse compounds, analyse SAR around hits for triaging results from high throughput screening or to identify ‘regions’ of chemistry that may yield good properties or scores.
StarDrop provides three different approaches to defining clusters:
- Maximum common substructure
- Compound similarity
With StarDrop you can easily search for compounds based on flexible substructure criteria, including the unique ability to specify variable linkers of defined length and cyclicity, as well as:
Variable atom criteria
- Number of hydrogens
- Arbitrary SMARTS
Variable bond criteria
- Bond order
With its comprehensive suite of integrated software, StarDrop™ delivers best-in-class in silico technologies within a highly visual and user-friendly interface. StarDrop™ enables a seamless flow from the latest data through predictive modelling to decision-making regarding the next round of synthesis and research, improving the speed, efficiency, and productivity of the discovery process.