Programme Parameters
Graduate / Intermediate
4 Weeks (40 Hrs)
Online (e-LMS)
• A basic understanding of the subject area and fundamental programming or scientific concepts.
• A laptop or desktop with a stable internet connection.
• Willingness to complete assignments and the capstone project.
About This Course
Molecular Dynamics Simulation in Bioscience Research teaches how to watch biomolecules move on a computer. You learn the principles of molecular dynamics — force fields, integration and ensembles — and the practical workflow of setting up, running and analysing simulations of proteins and other biomolecules. The course connects simulation to real research questions: conformational change, stability, and molecular interactions. You finish able to reason about running and interpreting a molecular-dynamics simulation. A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
🎯 Program Aim
This course covers molecular dynamics simulation in bioscience — simulating the motion of proteins and biomolecules to understand structure, dynamics and interactions.
📋 Course Objectives
1. Explain force fields and MD principles.
2. Set up biomolecular simulations.
3. Run and manage MD trajectories.
4. Analyse conformational change and stability.
5. Interpret molecular interactions.
👥 Who Should Enroll?
• Structural and computational biologists
• Biophysics and biochemistry researchers
• Drug-discovery scientists
• Students of molecular simulation
🚀 Key Learning Outcomes
• An understanding of molecular dynamics.
• A simulation-workflow perspective.
• A computational-biophysics foundation.
• A verified e-Certificate of competency and e-Marksheet from the Deep Science & Technology Consortium.
💎 What You'll Gain
Live & Recorded Sessions
Lifetime access to class recordingse-Certificate on Completion
Cryptographically verified credentialPost-Programme Support
Direct access to mentors & councilHands-On Experience
Notebooks, real-world code & datasetsCurriculum Outline
Foundations of Molecular Dynamics Simulation and Core Biological Principles
Apply Newtonian mechanics and statistical mechanics principles to derive the equations of motion governing molecular dynamics simulations in biological systems • Differentiate among force fields including AMBER, CHARMM, and OPLS to select appropriate parameter sets for proteins, nucleic acids, and lipid bilayer systems • Construct three-dimensional molecular models using PDB structures and topology files to prepare simulation-ready biological systems
Laboratory Techniques, Protocols, and Data Collection
Execute energy minimization protocols using steepest descent and conjugate gradient algorithms to eliminate steric clashes in solvated systems • Calibrate temperature and pressure coupling methods (Berendsen, Nose-Hoover, Parrinello-Rahman) to maintain thermodynamic ensemble stability during extended simulations • Validate simulation trajectories by monitoring RMSD, RMSF, and potential energy convergence to ensure data integrity for downstream analysis
Bioinformatics Tools and Computational Analysis
Deploy GROMACS, NAMD, or AMBER simulation engines to execute parallelized molecular dynamics runs on CPU and GPU architectures • Program Python scripts utilizing MDAnalysis and MDTraj libraries to automate trajectory processing, atom selection, and geometric property calculations • Integrate sequence alignment tools (Clustal Omega, MUSCLE) with structural databases (PDB, UniProt) to inform homology modeling and mutant system construction
Research Methodology and Experimental Design
Design replicated simulation experiments with appropriate sampling strategies (replica exchange, umbrella sampling, metadynamics) to enhance conformational space exploration • Calculate binding free energies using alchemical methods (FEP, TI) and end-state approaches (MM-PBSA, MM-GBSA) to quantify ligand-protein interaction strengths • Construct Markov state models from simulation trajectories to identify metastable conformational states and extract kinetic rate constants
Advanced Molecular Dynamics Applications and Translational Research
Simulate membrane protein systems embedded in explicit lipid bilayers to investigate gating mechanisms, ion transport, and allosteric modulation • Apply enhanced sampling techniques (steered molecular dynamics, targeted molecular dynamics) to characterize rare biological events including protein folding and large conformational transitions • Evaluate drug-target residence times and binding kinetics through molecular dynamics-guided rational design for therapeutic optimization
Regulatory Compliance, Bioethics, and Safety Standards
Assess computational research practices against FAIR data principles to ensure reproducibility, transparency, and proper attribution in molecular simulation studies • Implement data management plans compliant with institutional review board requirements for research involving pathogen-related molecular structures • Evaluate dual-use research of concern (DURC) implications when simulating toxins, virulence factors, or gain-of-function mutations in biological systems
Industry Applications, Career Pathways, and Case Studies
Analyze pharmaceutical case studies where molecular dynamics accelerated hit-to-lead optimization, resistance mutation prediction, or biologics formulation development • Compare career trajectories across academic, biotechnology, pharmaceutical, and software vendor sectors for computational molecular scientists • Appraise emerging industry trends including AI-accelerated molecular dynamics, cloud-based simulation platforms, and quantum mechanics/molecular mechanics hybrid approaches
Technical Specifications
| Parameter | Requirement |
|---|---|
| Covered Tool / Platform | GROMACS |
| Covered Tool / Platform | NAMD |
| Covered Tool / Platform | AMBER |
| Covered Tool / Platform | VMD |
| Covered Tool / Platform | PyMOL |
| Covered Tool / Platform | MDAnalysis |
| Covered Tool / Platform | MDTraj |
| Covered Tool / Platform | Python |
| Covered Tool / Platform | CUDA |
| Covered Tool / Platform | Gaussian |
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