Computational Drug Discovery: A Practical Research Approach (duration- 6 months)
Bridge chemical intuition with deep learning to accelerate therapeutic innovation.
Course Description
This intensive 6-month research-oriented program provides an end-to-end framework for computer-aided drug design (CADD) and AI-integrated discovery. In an era where "in silico" exploration is mandatory, this course teaches you how to leverage Machine Learning (ML) and Deep Learning to navigate the vast chemical space. You will transition from foundational molecular modeling to advanced Generative AI techniques for de novo molecule design. Through a hands-on research project, you will apply molecular docking, QSAR modeling, and ADMET prediction to real-world disease targets. By the end of the program, you will be proficient in using industry-standard tools to identify "hits," optimize "leads," and predict clinical success, making you an asset to the global biopharmaceutical industry.
What You'll Learn
Target Identification: Use genomics and proteomics to identify and validate druggable targets.
Molecular Modeling: Master protein structure preparation and ligand optimization techniques.
Virtual Screening: Conduct high-throughput screening of millions of compounds using AI-accelerated workflows.
Binding Affinity: Predict and analyze protein-ligand interactions and binding energies.
Generative Chemistry: Design novel molecules using Variational Autoencoders (VAEs) and Diffusion Models.
Pharmacokinetics: Predict Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) properties.
Curriculum
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Module 1: Basics of Bioinformatics & Introduction to CADD
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Module 2: Linux, Cloud Computing and Its Application in CADD
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Module 3: Python Programming for CADD
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Module 4: R for Data Analysis in Drug Discovery
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Module 5: Computer-Aided Drug Designing Techniques (Docking, QSAR, Pharmacophore Modeling)
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Module 6: HR Session – Career Mentoring & Industry Preparedness
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Module 7: Machine Learning in Drug Discovery
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Final Project: Research Project in CADD (2-Month Guided Research with Report)
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