Structure-Based In Silico Drug Design

This advanced internship provides a comprehensive understanding of how computational tools are used in the discovery and design of new drug candidates. Participants will learn how to identify biological targets, retrieve protein structures, design ligands, and perform molecular docking simulations using state-of-the-art software. The program combines theory with real-world case studies and hands-on projects.

🎯 Learning Objectives

By the end of the internship, participants will:

• Understand the principles of structure-based drug design (SBDD)

• Identify therapeutic targets and analyze 3D structures of proteins

• Design ligands using cheminformatics tools

• Perform molecular docking using AutoDock and visualize interactions

• Evaluate docking results and predict drug-likeness properties (ADMET)

🧩 Program Structure

Introduction to Drug Discovery

• Drug development pipeline: from target identification to lead optimization

• Overview of structure-based vs ligand-based design

• Types of targets: enzymes, receptors, DNA/RNA, etc.

Protein Structure and Target Identification

• Understanding PDB files and protein domains

• Tools: RCSB PDB, UniProt, SWISS-MODEL

• Practice: Retrieving and analyzing protein targets

Ligand Design & Chemical Libraries

• Introduction to small molecules and ligands

• Tools: PubChem, ZINC database, ChemSpider

• Drawing ligands: MarvinSketch, ChemDraw basics

Molecular Docking Theory

• Basics of docking algorithms (rigid vs flexible docking)

• Docking parameters and scoring functions

• Introduction to AutoDock and AutoDock Vina

Docking Practical – Part I

• Preparing protein and ligand structures

• Grid box setting and configuration files

• Running docking simulations in AutoDock Vina

Docking Practical – Part II

• Analyzing docking results: binding affinities and interaction sites

• Visualizing docking output in PyMOL / Discovery Studio

Drug-Likeness and ADMET Screening

• Lipinski’s Rule of Five

• Tools: SwissADME, pkCSM

• Toxicity and bioavailability prediction

Case Study and Literature Discussion

• Case Study: EGFR kinase inhibitor or HIV protease inhibitor

• Paper discussion: Recent trends in in silico drug discovery

Project Presentation and Feedback

• Mini-project presentation: Target-ligand docking + result analysis

• Faculty/mentor feedback

• Certificate distribution

Tools & Software

• AutoDock Vina – Molecular docking

• PyMOL / Chimera – Protein-ligand interaction visualization

• SwissADME / pkCSM – Drug-likeness and ADMET screening

• ZINC / PubChem – Ligand libraries

• SWISS-MODEL – Protein modeling

📂 Assignments & Capstone Project

• Retrieve protein & ligand data

• Perform docking and generate result reports

• Screen molecules using ADMET tools

• Present a final report on drug-likeness and binding prediction

📜 Certification

Participants receive a verifiable Certificate of Completion and a Project Experience Letter on successful submission of their final project.

👥 Target Audience

• Postgraduate students and PhD scholars in Life Sciences, Pharmacy, Bioinformatics

• Research interns and academicians

• Industry professionals exploring computational drug discovery