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Drug Discovery Masterclass: Molecular Docking from Scratch- recorded courses

Master computer-aided drug design (CADD) pipelines to simulate and analyze complex ligand-protein interactions. Deploy computational modeling workflows from the ground up to identify high-affinity therapeutic compounds.

  • 5.0/5
  • English
  • Updated Aug 2026
Drug Discovery Masterclass: Molecular Docking from Scratch- recorded courses

About this course

Welcome to an advanced self-paced masterclass designed to launch your career in computational pharmacology and structural bioinformatics. Modern pharmaceutical innovation relies heavily on computational simulation to accelerate preclinical development timelines and minimize wet-lab trial costs. This comprehensive recorded course equips you with the foundational skills to execute modern computer-aided drug design protocols from scratch. Throughout this training, you will learn to retrieve, clean, and prepare raw protein target structures and small-molecule chemical libraries. You will explore the biophysical principles behind molecular docking algorithms, scoring functions, and active site identification. Furthermore, the curriculum focuses on evaluating molecular binding affinities, predicting drug-likeness parameters, and assessing toxicological profiles online. By blending structural biology principles with modern AI-driven virtual screening methods, you will understand how machine learning models optimize hit-to-lead selection. Step directly into the world of rational drug design, gain a competitive edge in translational research, and revolutionize your approach to biomedical discovery.

What you will learn

Navigate structural biology databases to retrieve and prepare 3D macro-molecular target receptors.
Curate, optimize, and generate structural conformations for small-molecule ligand libraries.
Execute target-blind and site-specific molecular docking protocols using industry-standard open-source software.
Interpret thermodynamic scoring functions, binding energies, and non-covalent intermolecular bonds.

Skills you will gain

Docking Bioinformatics Ligands Modeling Simulation Screening Pharmo-Genomics Visualization Scoring Analytics
Certification

Available

Issued by Dr. Omics

Course curriculum

2 modules

  • Module 1: Principles of Structural Biology, Protein Data Bank (PDB) Curation, and Target Preparation.
  • Module 2: Small-Molecule Chemistry, 3D Geometry Optimization, and Ligand Library Formatting.
  • Module 3: Active Site Identification, Grid Box Configuration, and Molecular Docking Execution.
  • Module 4: Evaluating Thermodynamic Scoring Functions, Binding Energies, and 2D/3D Interaction Visualizations.
  • Module 5: Virtual Screening Implementations and ADMET Profiling Foundations for AI-Driven Lead Prioritization.

  • 1: Intro to Computer-Aided Drug Discovery (CADD) and the 2026 AI shift.
  • 2: Receptor Preparation: Cleaning and optimizing structures from the PDB.
  • 3: Ligand Engineering: 2D-to-3D conversion and geometry optimization.
  • 4: Defining the Search Space: Grid box generation and active site prediction.
  • 5: Running the Docking Simulation: Hands-on with AutoDock Vina.
  • 6: Post-Docking Analysis: Pose clustering, visualization, and interaction profiling.
  • 7: Integrating Machine Learning: Using AI to refine scoring and filter ADMET properties.

What you need to start

  • A foundational understanding of general biochemistry concepts (including protein structures, amino acids, and chemical bonds).
  • General familiarity with basic operating system mechanics; no prior advanced programming or coding background is mandatory.
  • A standard computer capable of running molecular visualization and structural docking packages.

Who this course is for

  • Medicinal Chemists and Pharmacologists eager to add computational screening and structural modeling to their research toolkits.
  • Biotechnology and Life Science Postgraduates transitioning into high-demand dry-lab structural bioinformatics careers.
  • Cancer and Pathology Researchers focused on studying molecular mutations and designing targeted small-molecule inhibitors.
  • Data Scientists and AI Engineers seeking to deeply master the chemical and physical data formats that feed modern structural predictive machine learning models.
INR

₹2999

₹5000 40% off
USD

$35

$50 30% off

Indian learners pay in INR; international learners are billed in USD.

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This course includes
  • Format Self Paced
  • Level All Levels
  • Language English
  • Modules 2
  • Access 3 months
  • Certificate Yes
  • Provider Dr. Omics
  • Certificate
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