Junes is an intuitive chemoinformatics tool that simplifies chemical data visualisation, analysis and processing to accelerate innovation in molecular design, drug discovery, materials science and property prediction without coding.
Designed to process chemical data, Junes offers a fast and reliable engine to support your R&D projects, with Chemoinformatics Tools, Toxicity Prediction Models and intuitive plotting tools to access and visually analyse chemical data, features and relationships.
Junes supports your R&D process in a variety of applications. When analysing Chemical properties, Junes performs advanced chemoinformatics evaluations, including QSAR modelling, molecular similarity, and descriptor calculations. In Early-Stage Drug Discovery, it supports the design of safe and effective molecules. Besides, thanks to embedded in-silico tools compliant with the REACH Regulation, Junes can be used to avoid in-vivo testing for the registration of chemicals in Europe.
Junes integrates advanced chemoinformatics and toxicity prediction tools enabling faster innovation, better decision-making, and safer compound development:
- Easy to Use: simplifies complex analyses with a user-friendly interface and seamless integration into organizational workflows.
- Time and cost efficiency: accelerates R&D, chemical data exploration and toxical regulatory workflows.
- Comprehensive capabilities: supports a wide range of R&D activities, from molecular descriptors calculation to chemical property analysis and innovative compound development.
Discover all the features inlcuded in Junes in the tab below and request your one-month free trial.
Junes includes a wide variety of features covering chemical data processing in a pharma, nutraceutical, industrial chemistry R&D project
Macro area |
micro area |
features |
|---|---|---|
| Chemical Structure Processing | Chemical Data Representation and Conversion |
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| Chemical Structure Processing | Data Curation |
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| Molecular Representations and Features | Molecular Fingerprints |
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| Molecular Representations and Features | Molecular Descriptors |
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| Molecular Representations and Features | Molecular Graphs Generation |
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| Predictive Modeling | Eco-Toxicity prediction | 96 VEGA Models ToxRead and ToxTree rule-based models |
| Cheminformatics Analysis and Visualization | Cheminformatics Analysis | Similarity Searching |
| Cheminformatics Analysis and Visualization | Data Visualization | Statistical Plots Correlation Analysis Chemical Space Visualization |
Molecular descriptors provide numerical representations of chemical properties, structural characteristics, and molecular behavior.
Type of Descriptor |
Category |
Function |
|---|---|---|
| 2D Descriptors | Autocorrelation-Based | Capture spatial relationships of molecular properties in 2D |
| 2D Descriptors | 8 Matrix-Based | Use adjacency, distance, or Laplacian matrices for molecular analysis |
| 2D Descriptors | Burden Eigenvalues | Represent atomic contributions to molecular propertie |
| 2D Descriptors | 8 ETA Indices and P_VSA Descriptors | Combine electronic and steric properties |
| 3D-Based Descriptors | Autocorrelation 3D | Extend autocorrelation calculations into 3D space |
| 3D-Based Descriptors | 8 WHIM (Weighted Holistic Invariant Molecular) | Capture 3D shape and symmetry |
| 3D-Based Descriptors | 8 RDF (Radial Distribution Function) | Quantify atomic distributions in 3D |
| 3D-Based Descriptors | 8 MORSE (Molecular Representations of Structures based on Electron diffraction) | Encode 3D molecular properties |
| 3D-Based Descriptors | 8 GATEWAY Descriptors | Use geometrical and electronic properties for advanced analysis |
| Functional Groups and Fragment Counts | Quantify specific chemical groups or fragments in molecules | |
| Topological and Geometrical Descriptors | 8 Walk and Path Counts | Describe molecular connectivity patterns |
| Topological and Geometrical Descriptors | 8 Connectivity and Information Indices | Quantify molecular complexity and diversity |