Programme Parameters
Foundation
3 Days (4.5 Hrs)
Online (e-LMS)
• No prior experience required — basic computer literacy is sufficient.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
Analysis of Drug-like Small Molecule using ChemmineR is a practical cheminformatics course built around a powerful open-source R toolkit. You learn to represent and handle molecular structures, compute molecular descriptors and fingerprints, and perform the analyses that underpin computational drug discovery: similarity searching, clustering compound libraries, and screening for drug-like properties. Working hands-on in R with ChemmineR, you connect each step to real questions of finding and prioritising promising molecules. You finish able to run a small-molecule cheminformatics workflow end to end. A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
This hands-on course teaches small-molecule cheminformatics with the ChemmineR package in R — structure handling, descriptors, similarity searching and screening of drug-like compounds.
📋 Course Objectives
1. Handle molecular structures and formats in ChemmineR.
2. Compute descriptors and molecular fingerprints.
3. Perform similarity searching and clustering.
4. Screen compounds for drug-like properties.
5. Build a reproducible cheminformatics workflow in R.
👥 Who Should Enroll?
• Cheminformatics and medicinal-chemistry researchers
• Bioinformatics scientists in drug discovery
• Pharma and biotech R&D staff
• Students specialising in computational chemistry
🚀 Key Learning Outcomes
• The ability to analyse small molecules in R.
• A cheminformatics screening project.
• A foundation for computational drug discovery.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Handling Chemical Data in R
• SDF and SMILES formats, and importing them with ChemmineR
• SDFset objects, validity checking and removing malformed structures
• Standardisation: salts, tautomers and charge states before any comparison
Representing a Molecule Numerically
• Atom pair descriptors and fingerprints as implemented in ChemmineR
• Physicochemical properties, and Lipinski and drug-likeness filtering
• What a fingerprint captures and the structural information it discards
Comparing Compounds
• Tanimoto coefficient and the threshold conventions used in practice
• Similarity searching against a compound library
• The similarity property principle and the activity cliffs that violate it
Organising a Library
• Binning and hierarchical clustering of compound sets
• Maximum common substructure and scaffold-based grouping
• Visualising chemical space and the distortion any 2D projection introduces
Applying It to Discovery
• Virtual screening workflows and enrichment assessment
• Diversity selection and cherry-picking a subset for assay
• ChemMine Tools and integration with the wider R analysis workflow
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | RStudio |
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