| Attribute | Detail |
|---|---|
| Format | Recorded Lectures |
| Level | Intermediate |
| Duration | 3 Days (60-90 minutes) |
| Certification | e-Certification + e-Marksheet |
| Fee | Free |
| Tools | AutoDock Vina PyRx Schrödinger Suite GROMACS ChemDraw Discovery Studio ADMET Predictor |
About the AI-Assisted Protein Structure Prediction, Molecular Docking and Virtual Screening Course
This 3‑day hands‑on course introduces participants to the practical workflow of computational drug discovery using AI‑assisted protein structure prediction, molecular docking, and virtual screening.
You will learn to select disease‑related targets, retrieve sequences and structures, prepare ligands, run docking analyses, and interpret protein‑ligand interactions with beginner‑friendly tools.
Program Highlights
• Comprehensive coverage of Assisted Protein Structure Prediction from fundamentals to advanced applications
• Hands-on projects and real-world case studies in Drug Discovery & Design
• Expert-curated curriculum aligned with current industry standards
• Access to recorded lectures and e-LMS platform for flexible, self-paced learning
• e-Certification and e-Marksheet upon successful completion
• Dedicated mentor support and interactive doubt-clearing sessions
• Exposure to industry-standard tools and platforms used in Drug Discovery & Design
• Career-oriented training for academic and professional growth in Drug Discovery & Design
Course Curriculum
Module 1: Day 1 – Protein Target Selection & Structure Prediction
- Explore computational drug discovery fundamentals
- Retrieve protein sequences from UniProt and structures from RCSB PDB
- Generate AI‑based models with AlphaFold and perform quality checks
Module 2: Day 2 – Ligand Selection, Protein & Ligand Preparation, Docking
- Retrieve drug‑like compounds from PubChem
- Prepare proteins and ligands for docking
- Execute docking using SwissDock/CB‑Dock2/AutoDock Vina workflows
Module 3: Day 3 – Result Visualization, Interaction Analysis & Virtual Screening
- Visualize binding poses with PyMOL or Discovery Studio
- Analyze hydrogen bonds, hydrophobic and van der Waals interactions
- Conduct mini virtual‑screening and generate AI‑assisted reports
Tools, Techniques, or Platforms Covered
AutoDock Vina PyRx Schrödinger Suite GROMACS ChemDraw Discovery Studio ADMET Predictor
Real-World Applications
- Apply Assisted Protein Structure Prediction skills directly to academic research, thesis work, and publications
- Build a professional portfolio showcasing practical Drug Discovery & Design competencies
- Solve industry-relevant problems using Assisted Protein Structure Prediction methodologies and tools
- Contribute to open-source projects and collaborative research in Drug Discovery & Design
- Prepare for competitive examinations, interviews, and professional certifications in Drug Discovery & Design
Who Should Attend & Prerequisites
- Industry‑recognized e‑Certification + e‑Marksheet from NSTC
- Hands‑on training with practical projects and real‑world datasets
- Dedicated expert mentorship and doubt‑resolution support
Certification
