Programme Parameters
Advanced Postgrad
4 Weeks (40 Hrs)
Online (e-LMS)
• Prior working knowledge of the field and comfort with core tools and quantitative reasoning.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
The Introduction to Computational Drug Discovery course is a free, beginner-friendly self-paced program designed to introduce learners to the field of computational drug discovery, focusing on how computational tools and techniques are used to discover and design new drugs. Every participant receives a verified e-Certificate and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
The Introduction to Computational Drug Discovery course is a free, beginner-friendly self-paced program designed to introduce learners to the field of computational drug discovery, focusing on how computational tools and techniques are used to discover and design new drugs.
📋 Course Objectives
1. Put Artificial Intelligence techniques to work on real datasets and case studies.
2. Produce a reproducible, portfolio-ready project you can cite in a thesis, paper, or job application.
👥 Who Should Enroll?
• Master's and senior undergraduate students specializing in Artificial Intelligence
• R&D engineers and working professionals applying Artificial Intelligence in industry
• Academics and educators building research or teaching capacity in Artificial Intelligence
🚀 Key Learning Outcomes
• A demonstrable Artificial Intelligence project for your research or industry portfolio.
• 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
Introduction to Computational Drug Discovery
What is Computational Drug Discovery? • Role of Computational Approaches in Modern Drug Development • Applications in Pharmaceutical and Biomedical Research • Overview of the Drug Discovery Process (Target Identification to Clinical Trials)
Understanding Drug Targets and Bioinformatics Tools
Introduction to Drug Targets (Proteins, Enzymes, Receptors) • Bioinformatics Tools for Target Identification • Databases for Drug Discovery (e.g., Protein Data Bank, DrugBank) • Basic Concepts of Protein-Ligand Interactions
Virtual Screening and Molecular Docking
What is Virtual Screening? • Introduction to Molecular Docking Simulations • Screening Chemical Libraries for Potential Drug Candidates • Docking Algorithms and Scoring Functions
Drug Design and Optimization
Hit Identification and Lead Optimization • Structure-Based Drug Design (SBDD) vs Ligand-Based Drug Design (LBDD) • Computational Methods in Drug Optimization • Case Studies of Drug Design in Practice
Future Scope and Learning Path
Emerging Trends in Computational Drug Discovery • Artificial Intelligence and Machine Learning in Drug Design • Career Opportunities in Computational Biology, Drug Discovery, and Bioinformatics • Mini Learning Activity / Concept-Based Practice
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | Computational Drug Discovery |
| Covered Tool / Platform | Molecular Docking |
| Covered Tool / Platform | Virtual Screening |
| Covered Tool / Platform | Drug Design |
| Covered Tool / Platform | Protein-Ligand Interactions |
Frequently Asked Questions
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