Summary
A single platform that connects scientific rationale, compound design and computational resources.
This is Chemaxon’s Design Hub for medicinal chemistry from analysis to prioritizing ideas.
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Switch from powerpoint files to graphical and chemically searchable hypotheses that are an integral part of the compound design process
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Easily work with your trusted phys-chem properties, computational models, novelty issues or purchasable compound catalogs in a rich visual environment
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Involve your CROs in the compound progression process using this secure online service.
Features
Follow the DMTA cycle
Analyze collected evidence from biological assays or experimental structural information, extract SAR and make new hypotheses for the next optimization iteration. Store your scientific hypotheses in a “designers ELN” (chemically aware drawing canvases). Create virtual compounds by de novo design or automated solutions and prioritize the best ones based on team opinion and informatics filters. Track progression of the design sets and assign tasks to the team. Communicate and share results with the team and management.
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Features
Optimize compound ideas
Generate virtual compounds by de novo design, importing from external workflows, structure based searches in internal or external databases, enumerating or via MMP tools and characterize them based on synthetic feasibility, predictive models for 3D-protein interactions, physchem- and ADMET properties, as well as novelty searches in literature and commercial databases.
Benefits
Function across teams
Design Hub also facilitates teamwork for the 21st century with dedicated systems that allow integrating external synthesis collaborators into your workflow, without disclosing project details or sacrificing the time of team members by dealing with files or copies of information.
Trainer Engine: Translate data to prediction
Trainer Engine makes chemical, physical and biological activity predictions available by streamlining learning from input data with high accuracy, reliability and confidence at scale. The framework simplifies sharing models, and managing the machine learning lifecycle.
Design HUB for Drug Discovery
This application study will put Design Hub, our design and idea management platform in the focus.
Design Hub End User View
The talk covers the implementation of Design Hub in the scope of BI’s eDesign landscape.
Patent application management using ChemCurator and Design Hub at Sprint Bioscience
Sprint Bioscience develops small molecule medicines, focusing on cancer and tumor metabolism.
Key Properties in Drug Design | Predicting Lipophilicity, pKa and Solubility
Lipophilicity, pKa and solubility are key descriptors in drug design. Their importance to both pharmacokinetic exposure (ADME) and pharmacodynamic response (effect on target and off-targets) have been thoroughly studied and described in the literature.
