Generate & prioritise new, relevant compound ideas
Nova helps you to develop new compound optimisation strategies by opening up a world of opportunities in the hunt for those elusive, high-quality compounds you may have overlooked or simply not thought of.
With Nova you can perform de novo design using two different virtual library enumeration methods and two generative chemistry approaches.
Reaction-based Library Enumeration
Explore new chemistry ideas with a flexible and easy-to-use reaction-based library enumeration tool for the design of virtual libraries.
Select from approximately 100 pre-defined common reactions in the Reaction Manager or sketch and map your own and add them to centrally managed or personal reaction libraries. Define criteria for selection of reagents within available StarDrop data sets and specify the regioselectivity of enumeration for reagents with multiple reactive sites. Select products in the enumerated library biased for a property or score with a higher chance of success for your project objectives. Reagent meta-data such as inventory location and cost for each reagent, are linked with the enumerated compounds to facilitate ordering for synthesis of the best compounds. Products can be assigned to plates with the new Plate Layout tool, in preparation for automated synthesis.
Scaffold-based Library Enumeration
Explore new chemistry ideas with a flexible and easy-to-use scaffold-based library enumeration tool for the design of virtual libraries. After drawing the scaffold on which your library will be based, you can select multiple functional groups, atoms or fragments to vary at each point of variation.
StarDrop’s R-group clipping tool enables quick transformation of chemical building blocks into their corresponding substituents for enumeration of virtual libraries and the exploration of new compound ideas. Associated data, such as inventory and cost for each building block, are linked with the enumerated compounds to facilitate ordering for synthesis of the best compounds.
You can save R-groups and the data associated with the corresponding building blocks in a fragment library that can be easily shared with your colleagues. This provides a central location to conveniently access your most commonly-used R-groups for rapid enumeration of virtual libraries.
Exponentially broaden your search for new compound ideas by taking ‘parent’ molecules and creating new ‘generations’ of related compounds using a built-in collection of over 200 common transformations. The resulting compounds ‘make sense’ from a medicinal chemistry perspective because the transformations are derived from practical experience.
Nova can be extended with your own transformations or the optional BIOSTER database which contains a unique compilation of over 28,000 precedented transformations from the chemistry literature, complete with references.
For further information, take a look at our J. Chem. Inf. Model. paper ‘Applying Medicinal Chemistry Transformations and Multiparameter Optimization to Guide the Search for High-Quality Leads and Candidates’, where we discuss the methods underlying Chemistry Transformations.
Matched Series Analysis
The Matsy™ and SAR transfer algorithms for matched series analysis, from NextMove Software Ltd, predict new chemical substitutions that are likely to improve target activity for your projects. They help to answer the question, “What compound should I make next?”.
Matched series analysis goes beyond conventional ‘matched pair analysis’ by using data from longer series of matched compounds (and not just pairs) to make more relevant predictions for a particular chemical series. In addition, all predictions are backed by experimental results which you can view and assess when considering the suggestions.
To learn more about matched series analysis, watch Dr Noel O’Boyle’s webinar, ‘Beyond Matched Pairs’ or take a look at the J. Med. Chem paper ‘Using Matched Molecular Series as a Predictive Tool To Optimize Biological Activity’ where NextMove Software discuss how Matsy has been developed to generate and search in-house or public domain databases of matched series.
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.