Optibrium, developer of software solutions for drug discovery, announces an updated version of its StarDrop platform. Version 5.3 introduces features focused on the design of virtual libraries, guided by StarDrop’s unique multi-parameter optimization capabilities to prioritize compounds with the best balance of properties for synthesis and testing.
Version 5.3 introduces its virtual library design capability as part of StarDrop’s Nova module, providing flexible and easy scaffold-based enumeration of a virtual library to allow drug discovery teams to rapidly explore new chemistry ideas. After drawing the scaffold on which the library will be based, users can select multiple functional groups, atoms, or fragments to vary at each point of modification. These lists may be selected from a user-defined or centrally managed library, or sketched on an individual basis. A fully combinatorial library may be generated for detailed investigation or, alternatively, a subset of compounds can be automatically selected based on a predicted property or StarDrop’s unique Probabilistic Scoring algorithm for multi-parameter optimization.
These capabilities are supported by further enhancements to StarDrop’s core features, including easy-to-use tools for clustering, filtering based on substructure or properties and extensions to its interactive data visualization. StarDrop offers a comprehensive desktop environment that saves time and reduces costs in drug discovery by guiding compound design and selection to quickly target high quality chemistry. These include plug-in modules providing: rigorously validated ADME QSAR models; quantum mechanical prediction of P450 metabolism; automatic generation of robust QSAR models; compound idea generation; application of 3D SAR based on Cresset’s Field technology; and the ability to integrate seamlessly with other informatics and modelling platforms.
StarDrop allows users to go from design and enumeration of a virtual library, through property prediction to prioritizing the resulting compounds against the profile of properties they require for their project objective. Supported by interactive visualizations in StarDrop’s intuitive user interface, chemistry teams can quickly identify novel compounds with a high chance of success.