ACD/LogP is designed to predict the partition coefficient (logP), a crucial measure of a molecule's hydrophobicity, directly from its chemical structure. This software assists researchers in understanding how a compound distributes itself between octanol and water, providing insights into its behavior in biological systems and environmental contexts. It allows users to calculate logP values for neutral molecules and identify hydrophilic and hydrophobic fragments within a structure. A key feature is the ability to train the algorithm using experimental measurements, enhancing prediction accuracy for specific chemical spaces. ACD/LogP offers three distinct calculation algorithms: Classic, GALAS (Global, Adjusted Locally According to Similarity), and a Consensus model that leverages the strengths of the other two. The Classic algorithm provides a detailed calculation protocol, while GALAS incorporates a reliability index and displays similar structures from its extensive training database. The Consensus model combines the results from Classic and GALAS to provide a more robust prediction. Users can input structures by drawing them within the application, copying and pasting from third-party drawing packages, using SMILES strings or InChI codes, or importing MOL, SK2, SKC, or CDX files. The software also includes a built-in dictionary for searching structures by name. For batch processing, ACD/LogP is compatible with Microsoft Windows and Linux, and can be integrated into corporate intranets or workflow tools like Pipeline Pilot. A browser-based application is also available for thin client deployment, with KNIME integration components.

Features & Benefits

• Accurate, Reliable Results
  • Provides a reliability index, displays similar structures, and includes literature references for original experimental data. Leverages a training database of over 22,000 compounds.
• Deeper Insights
  • Enables the creation of scatter plots and facilitates browsing, filtering, sorting, ranking, and prioritizing compound libraries.
• 3 LogP Calculators-in-One
  • Offers three algorithms: Classic, GALAS, and Consensus.
• Customizable with In-House Data
  • Allows users to train the algorithm with experimental logP values to improve accuracy for proprietary chemical space.
• Partition Coefficient (LogP) Calculator Features
  • Predicts logP from structure using various input methods.
• Estimates of prediction accuracy in the different models
  • Provides 95% confidence intervals for final logP value and incremental contributions (Classic).