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Training modules:

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Basics of Computer Aided Drug Discovery Part-I:

A perfect course for Bachelors / Masters / PhD students who are getting started into Drug Discovery research. This course is specially designed keeping in view of beginner level knowledge on computational drug discovery applications for science students. By the end of this course participants will be equipped with the basic knowledge required to navigate their drug discovery project making use of the biological databases and computational tools.

Here's what you'll learn from this course:

  • Introduction to Computer Aided Drug Discovery

  • Introduction to databases like PDB, PubChem and ZINC database

  • How to visualize protein and ligands in Biovia Discovery Studio and MGLtools

  • How to prepare files for docking studies.

  • How to execute molecular docking.

  • How to analyze the docking output results.

  • How to generate publication quality figures from the docking output.

Click here to enroll in the course now !

Introduction to Applications of Artificial Intelligence & Machine Learning techniques in Drug Discovery, Designing & Development process:

A perfect course for Bachelors / Masters / PhD students who are getting started into Drug Discovery research. This course is specially designed keeping in view of beginner level knowledge on Artificial Intelligence, Machine learning and computational drug discovery applications for science students. By the end of this course participants will be equipped with the basic knowledge required to navigate their drug discovery project making use of the Artificial Intelligence and Machine learning based tools.

Here's what you'll learn from this course:

  • Introduction to drug discovery and applications of AI & ML techniques at different stages.

  • ABCDs of AI & ML terminology.

  • Introduction to types of Artificial Intelligence & Machine learning.

  • Introduction to Neural networks and Natural Language processing.

  • Introduction to potential of AI & ML in Drug Discovery.

  • Introduction to advantages and limitations of applying AI in drug discovery.

  • Current Solution 1: AI based information aggregation from vast literature.

  • Current Solution 2: AI based systems modelling to understand disease mechanisms.