Computational Drug Design
( 30 Modules )

Module #1
Introduction to Computational Drug Design
Overview of the field, importance, and basics of computational drug design

Module #2
Pharmacology and Drug Development
Understanding pharmacology, drug development process, and the role of computational methods

Module #3
Computational Chemistry Fundamentals
Basic principles of computational chemistry, molecular mechanics, and quantum mechanics

Module #4
Molecular Modeling and Visualization
Introduction to molecular modeling, visualization tools, and molecular structure representation

Module #5
Molecular Dynamics Simulation
Principles and applications of molecular dynamics simulation in drug design

Module #6
Free Energy Calculations and QSAR
Free energy calculations, QSAR, and their applications in drug design

Module #7
Protein-Ligand Interactions and Binding Free Energy
Understanding protein-ligand interactions, binding free energy, and its calculation methods

Module #8
Virtual Screening and Hit Identification
Virtual screening methods, hit identification, and optimization strategies

Module #9
Structure-Based Design Case Studies
Real-world examples of structure-based drug design and its success stories

Module #10
Pharmacophore Modeling and Ligand-Based Design
Pharmacophore modeling, ligand-based design, and its applications

Module #11
Quantitative Structure-Activity Relationships (QSAR) Modeling
QSAR modeling, its limitations, and applications in drug design

Module #12
Ligand-Based Design Case Studies
Real-world examples of ligand-based drug design and its success stories

Module #13
Fragment-Based Drug Design
Fragment-based drug design, fragment screening, and its applications

Module #14
Pharmacokinetics and ADME-Tox
Pharmacokinetics, ADME-Tox, and its importance in drug design

Module #15
Integrating Pharmacokinetics and Pharmacodynamics
Integrating pharmacokinetics and pharmacodynamics in drug design

Module #16
Machine Learning Fundamentals in Drug Design
Introduction to machine learning, its applications, and importance in drug design

Module #17
Deep Learning in Drug Design
Deep learning methods, its applications, and limitations in drug design

Module #18
AI-Driven Drug Design Case Studies
Real-world examples of AI-driven drug design and its success stories

Module #19
High-Throughput Screening and Data Analysis
High-throughput screening, data analysis, and interpretation

Module #20
Data Mining and Visualization in Drug Design
Data mining, visualization, and its applications in drug design

Module #21
Big Data and Analytics in Drug Design
Big data, analytics, and its importance in drug design

Module #22
Computational Design of Antimicrobial Peptides
Computational design of antimicrobial peptides, its challenges, and opportunities

Module #23
Computational Design of PROTACs
Computational design of PROTACs, its principles, and applications

Module #24
Computational Design of Gene Therapies
Computational design of gene therapies, its challenges, and opportunities

Module #25
Case Studies in Cancer Drug Design
Computational drug design case studies in cancer research

Module #26
Case Studies in Infectious Disease Drug Design
Computational drug design case studies in infectious disease research

Module #27
Case Studies in Neurological Disorder Drug Design
Computational drug design case studies in neurological disorder research

Module #28
Emerging Trends in Computational Drug Design
Emerging trends, challenges, and opportunities in computational drug design

Module #29
Integrating Multi-Omics Data in Drug Design
Integrating multi-omics data in drug design, its challenges, and opportunities

Module #30
Course Wrap-Up & Conclusion
Planning next steps in Computational Drug Design career

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Computational Drug Design ( 30 Modules )

Computational Drug Design
( 30 Modules )