CDPL Python Cookbook

This ‘cookbook’ provides a set of scripts that demonstrate how often occurring tasks in cheminformatics can be accomplished with Python code that utilizes functionality offered by the CDPL. To be able to understand the CDPL-specific parts of the code it is highly recommended to first have an in-depth look at the CDPL Python Tutorial which imparts valuable knowledge regarding basic concepts and the work with fundamental data structures.

All scripts are ready-to-run and have been designed to be executed on the command line. Most of the scripts require arguments to be specified (e.g. path to input/output files). Information on required/supported arguments can be obtained by running the scripts without arguments.

The source code provided by this cookbook may be used without restrictions for any purpose under the terms of the Zero-Clause BSD License (0BSD).

Note

The scripts require a properly set up installation of the CDPL Python bindings. Please visit section Installing CDPKit for further information.

Tip

To quickly find cookbook scripts that cover a certain topic or utilize a particular package/class/method/function it is advisable to use the built-in search functionality and/or consult the page index.

• 1. Basic Processing of Molecules and Reactions
  • 1.1. Molecules
    • 1.1.1. Input and Output
      • 1.1.1.1. Sequential Input
      • 1.1.1.2. Retrieval and Processing of MDL SD-File Structure Data
    • 1.1.2. Fragmentation and Extraction of Substructures
      • 1.1.2.1. Extraction of Atom Environments
      • 1.1.2.2. Rule-based Fragmentation
      • 1.1.2.3. Bemis-Murcko Framework Analysis
    • 1.1.3. Structure Standardization, Curation and Database Preparation
      • 1.1.3.1. ChEMBL Structure Curation Pipeline
      • 1.1.3.2. Generating Protonation States at Physiological pH
      • 1.1.3.3. Database Cleaning
      • 1.1.3.4. Atom/Bond Order Canonicalization
    • 1.1.4. Miscellaneous
      • 1.1.4.1. Testing for the Presence of Substructures
      • 1.1.4.2. Editing of Substructures
      • 1.1.4.3. Enumeration of Stereoisomers
      • 1.1.4.4. 2D Structure Generation
• 2. Pharmacophore Generation and Processing
  • 2.1. Input and Output
    • 2.1.1. Sequential Input
  • 2.2. Generation
    • 2.2.1. Plain Molecule Pharmacophores
    • 2.2.2. Ligand-receptor Interaction Pharmacophores
  • 2.3. Processing
    • 2.3.1. Retrieving Feature Properties
    • 2.3.2. Molecule to Reference Pharmacophore Alignment
    • 2.3.3. Pharmacophore to Pharmacophore Alignment
    • 2.3.4. Pharmacophore Feature Mapping Analysis
• 3. Calculation of Molecule, Atom and Bond Properties
  • 3.1. Atomic Properties
    • 3.1.1. Connectivity Properties
    • 3.1.2. Chemical Element Properties
    • 3.1.3. Classification Properties
    • 3.1.4. Partial Charges And Other Electronic Properties
    • 3.1.5. Physicochemical Properties
  • 3.2. Molecular Properties
    • 3.2.1. Functional Groups
• 4. Calculation of Molecule and Pharmacophore Descriptors
  • 4.1. Fingerprints
    • 4.1.1. Extended Connectivity Fingerprint (ECFP)
    • 4.1.2. PubChem Fingerprint
    • 4.1.3. MDL MACCS Key
    • 4.1.4. Bond-Path Fingerprint
    • 4.1.5. 2D and 3D Pharmacophore Fingerprints
  • 4.2. Miscellaneous Descriptors
    • 4.2.1. FAME Atom Environment Fingerprint
    • 4.2.2. Receptor Binding Pocket Descriptor
• 5. 3D Structure and Conformer Generation
  • 5.1. Single Low-energy 3D Structures
  • 5.2. Conformer Ensembles
  • 5.3. Torsion Driving
• 6. Force Field Calculations
  • 6.1. MMFF94 Atom Charges
• 7. Molecular Shape Analysis and Alignment
  • 7.1. Gaussian Shape-based Molecule Alignment
• 8. Visualization
  • 8.1. Pharmacophore 3D Visualization