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Lecture Notes on RDKit
Jul 30, 2024
Introduction to RDKit
Overview of RDKit
Python library useful for chemical data manipulation.
Installation in Google Colab:
Not pre-installed; use specific installation commands.
Follow installation guide linked in video description.
Getting Started
Make a copy of the provided notebook for your own use.
Rename the notebook (e.g.,
rdkit intro
).
Run the installation; this takes 2-3 minutes.
Patience is key as installation completes.
Key Features of RDKit
RDKit can perform various tasks with molecular data:
SMILES Conversion
Converts SMILES strings (text-based representation of molecules) into molecular structures and vice versa.
Example SMILES:
Methane:
C
Ethane:
CC
Propane:
CCC
Normal Butane:
CCCC
Use cheminfo.org to draw molecules and generate SMILES strings interactively.
Molecular Representation
Convert SMILES to molecule object using
MolFromSmiles
Get SMILES from molecule object using
MolToSmiles
Calculating Properties
Compute molecular attributes such as molecular weight, e.g., for normal butane.
Substructure Searches
RDKit allows for searching molecules for specific patterns:
Example using amino acids:
Glycine, Phenylalanine, Histidine, Cysteine (search using their SMILES strings).
Displaying molecules:
Create a list of molecule objects and display them visually.
Substructure Search Examples
Searching for specific substructures, like sulfur and carboxyl groups:
Example code to identify which molecules contain specific elements or groups in their structure.
Substructure Patterns:
Use SMILES notation to define the search pattern.
Example: Search using sulfur’s SMILES string to find matching molecules.
General substructure search using SMARTS:
SMARTS is a more flexible version of SMILES.
Example: Identifying the presence of rings in the structure, where not all SMILES can easily represent this.
Conclusion
RDKit is a powerful tool for chemists and researchers dealing with molecular data.
Explore more by looking for resources on getting started with RDKit.
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