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Course Highlights

This course covers fundamentals of bioinformatics, protein structure modeling, molecular docking, ligand design, ADME/Toxicity prediction, and machine learning applications in CADD. Learners gain practical exposure with hands-on demos using tools like NCBI, UniProt, AutoDock, PyMOL, SwissADME, GROMACS, and Weka, along with case studies from real-world drug discovery projects.

  • Skill Type

  • Course Duration

  • Domain

  • GOI Incentive applicable

  • Course Category

  • Nasscom Assessment

  • Placement Assistance

  • Certificate Earned

  • Content Alignment Type

  • NOS Details

  • Mode of Delivery

Course Details

Learning Objectives

What will you learn in Computer Aided Drug Designing (CADD)?

  • Understand fundamentals of CADD and bioinformatics databases
  • Perform sequence analysis, protein modeling, and ligand preparation
  • Conduct molecular docking and interpret binding interactions
  • Evaluate ADME/Toxicity of drug candidates
  • Apply machine learning in CADD for predictions
  • Work with case studies in drug discovery
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Reasons to enrol

Why should you take Computer Aided Drug Designing (CADD)?

  • Learn practical skills with demos on leading bioinformatics and CADD tools
  • Gain expertise in molecular docking, ligand design, and ADME/Toxicity analysis
  • Understand integration of machine learning in drug discovery
  • Enhance employability in pharmaceutical research and development, and computational biology
  • Earn an industry-recognised certification in CADD
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Ideal Participants

Who should take Computer Aided Drug Designing (CADD)?

  • Students of bioinformatics, pharmacy, biotechnology, or chemistry
  • Professionals in pharma and life sciences seeking to upskill
  • Researchers in drug discovery and computational biology
  • Academicians looking to integrate CADD into their curriculum
  • Entrepreneurs in biotech and healthcare domains
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Curriculum

Curriculum

Level 1 - Bioinformatics and Sequence Analysis

  • Introduction to Bioinformatics and Databases (NCBI, UniProt, PDB, dbSNP)
  • Sequence Analysis and Phylogenetics (Clustal, BLAST, MEGA)
  • Introduction to CADD and Drug Discovery Pipeline
  • Protein Structure Modeling (SWISS-MODEL, Phyre2, I-TASSER, AlphaFold)

Level 2 - Protein and Ligand Preparation, Docking

  • Protein Preparation (Maestro, SPDBV)
  • Ligand Collection and Preparation (PubChem, ChEMBL, DrugBank, MarvinSketch, OpenBabel)
  • Molecular Docking (AutoDock, Vina, CastP, PyMOL)
  • Ligand-based Drug Design (Pharmacophore Modeling, SwissSimilarity)

Level 3 - ADME, Dynamics and Machine Learning in CADD

  • Toxicity and ADME Prediction (SwissADME, ProTox-II)
  • Protein Structure and Dynamics (JPred, DSSP, GROMACS)
  • CADD using Machine Learning (Bioassay datasets, PaDEL, Weka, ML models, performance evaluation)
  • Final Applications: Case Studies and Simulations
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skills and tools

Tools you will learn in Computer Aided Drug Designing (CADD):

Skills

  • Bioinformatics and Sequence Analysis
  • Protein Modeling and Docking
  • Ligand Preparation and Pharmacophore Modeling
  • ADME/Toxicity Prediction
  • Machine Learning in CADD
  • Drug Discovery Pipeline Understanding

Tools

  • NCBI, UniProt, PDB, dbSNP
  • SWISS-MODEL, Phyre2, I-TASSER, AlphaFold
  • Maestro, SPDBV, PubChem, ChEMBL, DrugBank
  • AutoDock, Vina, PyMOL, SwissADME, GROMACS, Weka
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