Bioinformatics; Learn Docking & Mol Dynamics Simulation


Bioinformatics; Learn Docking & Mol Dynamics SimulationBest Bioinformatics Course To Learn Advance Bioinformatics Techniques Like Docking & Molecular Dynamics Simulations

What you’ll learn

  • You will learn basics of Structural Bioinformatics Including Protein Structure Prediction
  • You will learn Basic Theory of Molecular Dynamics Simulations and Docking
  • You will Get Basic Introduction of Linux Operating Systems and Its Commands
  • You will have Practical Demonstration of Protein Molecular Dynamics Simulations in GROMACS
  • You will Learn Analysis of MD Trajectory Including RMSD, RMSF, Radius of Gyration, Solvent Accessible Surface Area, Total Number of Hydrogen Bonds etc
  • You will have Practical Demonstration of AutoDock, Vina, CB-Dock and PatchDock for Ligand Protein Docking
  • You will have Practical Demonstration of MD Simulation of Ligand-Protein Complex in GROMACS


  • In online teaching, it’s always hard to engage the students. Therefore we have designed this course keeping the psychology of students in view. Usually, students start to lose their interest when they are stuck in a complex concept that’s why We tried to move from simple to complex easily and understandably.
  • You need to be familiar with very basics of protein structures. This will be more then enough for you to take start of this course. We have tried our level best to take start from scratch in every module by assuming it that our students know nothing.
  • Although, its not mandatory but we will encourage you to take our course “Learn Bioinformatics From Scratch (Theory and Practical)” on udemy. This course may also help you to grab the concepts in better way.


Currently, there is high use of bioinformatics tools in biological studies. This Advance Bioinformatics course includes theory and practical aspects of molecular docking and molecular dynamics simulation for you. In this course, we have tried to explain the theory and practical steps which are required to perform the above-mentioned bioinformatics techniques. We strongly believe that after having this course, you will be well versed in ligand-protein docking and molecular dynamics simulations.

This course is designed to keep the need of biologists in view. We tried to explain every step in a simple and elegant way. Like our previous course, “Learn Bioinformatics From Scratch (Theory & Practical)” in this course, we took start from scratch. So, if you are new in this field then it will be easy for you to move with the flow. There is a total of seven modules with 104 lectures.  In this course, you will learn

(1)  Protein Structural Bioinformatics

(2) Theory of Molecular Dynamics Simulation

(3) Introduction of Linux Environment

(4) Practical Demonstration of Protein Molecular Dynamics Simulation

(5) Ligand-Protein Docking (Theory & Practical)

(6) Practical Demonstration of Ligand-Protein Complex Molecular Dynamics Simulation

(7) Virtual Screening of Ligands with Protein Using Vina

This course is a unique blend of theory and practical. We assure you that after having this course, performing molecular docking and molecular dynamics will be easy for you. We have used open-source software in this course so that you do not need to purchase any expensive software. The tools which are demonstrated in this course are Modeller, I-TASSER, Alpha-Fold (Colab), Auto-dock4, Vina, Patch-Dock, GROMACS, LigPlot, ChemSketch, OpenBabel, Pymol, and a lot more.

So what are you waiting for? Click the enroll button and start this amazing journey. We hope that the content of this course will be worth your money. We assure every possible assistance throughout your learning process. We always respond to Questions and Queries which you will forward to us. We believe that we will grow with you.

Your growth is our growth.

Who this course is for:

  • This course is for those who are interested to drug discovery.
  • This course is also suitable for those who want to be protein engineers and interested in denovo protein design.

Created by Muhammad Dujana
Last updated 9/2022
English [Auto]

Size : 2.70 GB

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