New Year Offer End Date: 30th April 2024
biomedical 4
Program

Insilico Macromolecular Modeling & Docking

Exploring the World of Insilico: Macromolecular Modeling & Docking Made Easy

About Program:

The “Insilico Macromolecular Modeling & Docking” program offers a comprehensive learning experience in macromolecular modeling and docking. Participants will gain insights into various macromolecules and the principles of molecular docking. The program covers topics such as visualization, homology modeling, ligand-based and structure-based drug design, and model validation. Practical hands-on sessions using software tools enhance participants’ proficiency. By the end of the program, participants will have practical skills and knowledge applicable to research, drug discovery, and molecular design projects.

Aim: The aim of this program is to provide participants with a comprehensive understanding of insilico macromolecular modeling and docking techniques. Through hands-on exercises and theoretical sessions, participants will learn the principles, methodologies, and tools used in the field of computational biology for studying macromolecules and their interactions. By the end of the program, participants will be equipped with the necessary skills to perform macromolecular modeling and docking studies, enabling them to explore and analyze molecular interactions in silico.

Program Objectives:

  1. To provide participants with a comprehensive understanding of the principles and concepts of macromolecular modeling.
  2. To introduce participants to different docking techniques and their applications in drug discovery and molecular design.
  3. To familiarize participants with software tools for molecular visualization and analysis of macromolecular structures.
  4. To equip participants with the knowledge and skills necessary for homology modeling to predict protein structures.
  5. To enable participants to understand and apply ligand-based drug design techniques, including virtual screening.
  6. To explore structure-based drug design methods, focusing on protein-ligand docking and interaction analysis.
  7. To emphasize the importance of model validation and evaluation in ensuring the quality and reliability of macromolecular models.
  8. To provide practical hands-on sessions where participants can apply the learned concepts using software tools commonly used in macromolecular modeling and docking.

What you will learn?

Day 1:

  1. Introduction to Insilico Macromolecular Modeling & Docking:
    • Overview of insilico methods for studying macromolecules and their interactions.
    • Introduction to molecular modeling and docking techniques and their applications.
  2. Molecular Visualization and Analysis:
    • Introduction to software tools for visualizing macromolecular structures.
    • Hands-on exercises on visualizing and analyzing protein and nucleic acid structures.
  3. Homology Modeling:
    • Understanding the concept of homology modeling.
    • Selection of template structures and building homology models using bioinformatics tools.
  4. Introduction to Docking:
    • Basics of molecular docking and its role in drug discovery.
    • Exploring different docking algorithms and scoring functions.

Day 2:

  1. Ligand-Based Drug Design:
    • Principles of ligand-based drug design and virtual screening.
    • Hands-on exercises on using molecular descriptors and similarity-based approaches.
  2. Protein-Ligand Docking:
    • Introduction to protein-ligand docking techniques.
    • Hands-on exercises on performing protein-ligand docking using software tools.
  3. Analysis of Docking Results:
    • Evaluation and interpretation of docking results.
    • Visualizing and analyzing protein-ligand interactions.
  4. Structure-Based Drug Design:
    • Concepts and techniques of structure-based drug design.
    • Applying docking data to optimize protein-ligand interactions.

Day 3:

  1. Model Validation and Evaluation:
    • Importance of model validation and evaluation in macromolecular modeling.
    • Techniques for assessing the quality and reliability of models.
  2. Advanced Topics in Docking:
    • Exploring advanced concepts in molecular docking, such as induced fit and scoring function optimization.
    • Hands-on exercises on advanced docking techniques.
  3. Case Studies and Applications:
    • Presenting real-world case studies showcasing the applications of insilico macromolecular modeling and docking.
    • Discussion on the impact of computational methods in drug discovery and molecular design.
  4. Practical Applications and Future Directions:
    • Exploring emerging trends and future directions in insilico macromolecular modeling and docking.
    • Discussion on the practical applications and potential challenges in the field.

Fee Plan

INR 1999 /- OR USD 50

Intended For : Graduates, Post Graduates, Researchers, Professionals, Educators, Academicians from Life Sciences, Chemistry, or Computational Biology, Professionals from Pharmaceutical and Biotechnology industries involved in drug development and molecular design.

Career Supporting Skills

Computational Drug Designer Computational Biologist Bioinformatics Scientist Drug Discovery Researcher Structural Bioinformatics Specialist

Program Outcomes

  1. Comprehensive understanding of the principles and concepts of macromolecular modeling and docking.
  2. Proficiency in using software tools for molecular visualization, analysis, and modeling.
  3. Knowledge and skills to perform homology modeling and predict protein structures.
  4. Ability to apply ligand-based and structure-based drug design techniques in virtual screening and protein-ligand docking.
  5. Familiarity with model validation and evaluation techniques to ensure the quality and reliability of macromolecular models.
  6. Hands-on experience through practical sessions, enhancing proficiency in software tools and applying learned concepts.
  7. Improved capability to contribute to research, drug discovery, and molecular design projects.
  8. Networking opportunities and interaction with experts and peers in the field.