Introduction to In-Silico Drug Discovery
Unlock the Power of Computational Drug Discovery
For Biomedical, Biological, and Medical Science Students and Researchers
Join the Waitlist NowCourse Overview
Learn how computational tools accelerate drug discovery and improve precision. This course introduces the fundamentals of drug discovery, medicinal chemistry, protein targets, ligands, and chemical databases, with interactive demonstrations and guided exercises to build practical understanding.
By completing this course, you will:
- Understand the stages of modern drug discovery and development.
- Explore how proteins serve as drug targets and how ligands interact with them.
- Use real scientific databases to search and analyze chemical structures.
- Apply foundational medicinal chemistry concepts to real-world research contexts.
Coming Soon!
This course is currently in its final development stage.
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Course Modules
Module 1 — Introduction to Drug Discovery and Development
- Historical milestones in drug discovery.
- Overview of the drug development pipeline.
- Challenges in conventional discovery.
- Emergence and benefits of in-silico approaches.
- Interdisciplinary nature of modern drug discovery.
Module 2 — Fundamentals of Medicinal Chemistry
- Chemical properties of drugs and structure–activity relationships (SAR).
- Types of molecular interactions: covalent, hydrogen bonding, hydrophobic, ionic.
- Drug-likeness and ADME principles (Lipinski's Rule of Five).
- Stereochemistry and pharmacophore concepts.
Module 3 — Understanding Drug Targets and Protein Structures
- Biological targets: enzymes, receptors, ion channels, nucleic acids.
- Protein structure hierarchy and functional roles.
- Active sites, binding pockets, and cofactors.
- Key structural databases: PDB, UniProt, AlphaFold.
Module 4 — Ligands and Chemical Databases
- Ligand types: small molecules, peptides, ions; agonists, antagonists, inhibitors.
- Major databases: PubChem, ChEMBL, ZINC, DrugBank.
- Molecular representations: SMILES, InChI, 2D vs. 3D structures.
- Chemical file formats and compound similarity search.
Why Take This Course
- Hands-On Learning: Guided exercises using real biological and chemical data.
- Beginner-Friendly: No pharmacology background required.
- Career-Oriented Skills: Build a foundation for future bioinformatics or computational biology study.
- Expert-Led: Designed and taught by Dr. Musab Mohamed Ibrahim Ali, PhD.
Who Should Join the Waitlist
- Undergraduate or postgraduate students in biomedical sciences, biotechnology, biology, or medicine.
- Graduate researchers seeking to explore computational drug discovery methods.
- Learners aiming to bridge experimental biology and computational analysis.
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