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Molecular docking is one of the most frequently used methods in structure-based drug design, due to its ability to predict the binding conformation of small-molecule ligands to the appropriate target binding site.

Ratings:

4.8
4.8

Number of Students:

471

Created By:

999.00

Offer Expires In

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This Course Includes

What You'll Learn

Who Is This For

This course is suitable for currently enrolled students or pass-out students.

About This Course

 This course will teach you the fundamentals of molecular docking, which is one of the most frequently used methods in structure-based drug design. Learn how to build and simulate a ligand binding pocket and apply these skills to structure-docking simulations of novel drugs and lead compounds.

This course will start from the basics and will turn you into an expert. If you have no prior knowledge on bioinformatics, then that’s OK. You will be trained from the very basic to understand the application of molecular docking techniques.

Why Take This Course

 This course will teach you all you need to know about molecular docking, including the essential concepts and specific skills needed to perform successful docking studies. You’ll learn how to quickly rack out molecules to and from their most likely binding site in order to guide the development of new therapeutic agents.

The training course has been designed to provide the theoretical background as well as a hands-on approach to Molecular Docking and Virtual screening.

How Will I Learn

Joining and taking the Molecular Docking Course will help you advance your career in research by providing you with access to a variety of valuable and instructive pre-recorded lectures on molecular docking.

Certification

All the participants will receive certificates on successful completion of training.

Curriculum

    • 1.1 Introduction to moleuclar docking 00:13:00
    • 1.2 Understanding the structure of protein 00:07:00
    • 1.3 Understanding the active site of a protein 00:08:00
    • 1.4 Understanding the ligand structure 00:06:00
    • 1.5 Protein ligand interactions 00:06:00
    • 2.1 Drug design 00:14:00
    • 2.2 Shift from traditional to computational biology 00:07:00
    • 2.3 Computer aided design and drafting 00:14:00
    • 2.4 Structure based drug design 00:15:00
    • 2.5 Virtual screening 00:17:00
    • 2.6 Structure based virtual screening 00:08:00
    • 2.7 Work-flow of multi-stage drug designing 00:16:00
    • 3.1 Workflow of molecular docking 00:14:00
    • 3.2 Molecular docking theory 00:21:00
    • 3.3 Ligand induced conformation 00:19:00
    • 3.4 Ligand poses 00:08:00
    • 3.5 Binding affinity 00:04:00
    • 3.6 Molecular docking task 00:06:00
    • 3.7 Molecular docking programs 00:07:00
    • 4.1 Types of biomolecular reactions 00:07:00
    • 4.2 Protein ligand docking 00:19:00
    • 4.3 Protein ligand docking example 00:05:00
    • 4.4 Protein-Protein docking 00:20:00
    • 4.5 Protein-Protein docking examples 00:26:00
    • 4.6 Protein-Peptide docking 00:15:00
    • 4.7 Protein-Peptide docking example 00:03:00
    • 4.8 Protein-DNA docking 00:24:00
    • 4.9 Protein-RNA docking 00:25:00
    • 4.10 Example 00:04:00
    • 4.11 HADDOCK 00:05:00
    • 5.1 Modes of molecular docking 00:05:00
    • 5.2 Rigid docking 00:16:00
    • 5.3 Illustration of rigid docking and its process 00:15:00
    • 5.4 Shifting towards flexible mode of docking 00:14:00
    • 5.5 Semi-Flexible docking 00:08:00
    • 5.6 Flexible Ligand, Rigid Protein 00:06:00
    • 5.7 Flexible docking – explanation 00:11:00
    • 5.8 Flexible docking-concept 00:14:00
    • 5.9 Flexibility of protein in drug discovery 00:08:00
    • 5.10 Example 1- CABS Dock 00:13:00
    • 5.11 Example 2 00:06:00
    • 5.12 Challenges of protein ligand docking 00:07:00
    • 5.13 Example 3 00:06:00
    • 6.1 Sampling algorithms – Introduction 00:03:00
    • 6.2 Semi-flexible docking- types 00:04:00
    • 6.3 Systematic search techniques 00:14:00
    • 6.4 Fragmentation search 00:14:00
    • 6.5 Conformational Ensemble 00:17:00
    • 6.6 Monte Carlo method 00:13:00
    • 6.7 Genetic algorithms 00:21:00
    • 6.8 Tabu search method 00:08:00
    • 6.9 Swarm optimization method 00:06:00
    • 6.10 Simulation method- molecular dynamics (example) 00:21:00
    • 6.11 Sampling Algorithms for flexible docking 00:10:00
    • 6.12 Soft Docking (examples) 00:15:00
    • 6.13 Side chain flexibility 00:17:00
    • 6.14 Multiple protein conformations 00:00:16
    • 6.15 Average grid method 00:05:00
    • 6.16 United description of the protein 00:13:00
    • 6.17 Individual conformations 00:15:00
    • 7.1 Pose selection (scoring functions) 00:13:00
    • 7.2 Scoring function components 00:09:00
    • 7.3 Classification of scoring function 00:21:00
    • 7.4 Empirical scoring fuctions 00:12:00
    • 7.5 Descriptors used in empirical scoring function 00:23:00
    • 7.6 Knowledge based scoring fuctions 00:17:00
    • 7.7 Evaluation scoring functions 00:12:00
    • 7.8 Databases for evaluating scoring functions 00:14:00
    • 7.19 Practical Session 1 01:00:00
    • 8.1 Understanding the structure file format- introduction 00:18:00
    • 8.2 Types of records in PDB 00:10:00
    • 8.3 Practical Session 2 01:00:00
    • 8.4 Docking target – handling the protein structure 00:28:00
    • 8.5 Prediction of active site & missing residues 00:15:00
    • 8.6 Practical Session 3- Prediction of active site & modeling missing residues 00:49:00
    • 8.7 Practical Session 4-Molecular Visualization Tool- Chimera 00:01:00
    • 9.1 Selecting the traget molecule 00:26:00
    • Practical Session – 5 00:15:00
    • 9.3 Practical session – 6 UniProtDB for receptor protein 00:28:00
    • 10.1 Practical Session 7 00:10:00
    • 10.2 Practical Session – 8 PubChem 01:00:00
    • AutoDoc Practical Session – 9 02:00:00
    • 12.1 Preparing the Protein – Practical Session 10 01:00:00
    • 12.2 Generating the grid parameter file – Practical Session 12 00:50:00
    • 12.3 Ligand molecule preparation – Practical Session 13 00:30:00
    • 12.4 Docking – Practical Session 14 00:51:00
    • 12.5 Analysis – Practical Session 15 00:53:00
    • 12.6 Analysis of the docked complex – Practical Session 16 00:55:00
    • 12.7 Molecular docking softwares 01:00:00
    • Applications of Molecular Docking 00:01:00

Reviews

  1. Molecular Docking

    5

    Very informative for my UG project work

  2. ANGARAG KASHYAPJuly 30, 2022 at 6:52 PM

    AUTODOCK

    5

    It’s very helpful

  3. MUTAZ MOHAMMED ABDALLAH ADAMJuly 24, 2022 at 7:56 PM

    Molecular docking certificate course

    5

    very informative course

  4. Excellent course

    5

    The course was excellent. the course has given the idea about CADD and its future scope. this is very helpful for me always. thank you for such good work.

  5. Tahreen Rafi

    5

    Slides are amazing and the classes are all good with great examples

  6. Impressive course content

    5

    The course content seems very comprehensive.

  7. Helpful

    5

    The course was interesting and also helpful

  8. Dr.BINAYAK BIBEK DASApril 12, 2022 at 5:16 AM

    Moleculars

    5

    Grt, superb

  9. SANDRA ELIZA SAJIApril 11, 2022 at 2:07 PM

    Good course

    5

    It was a very informational experience. I have learned a lot about molecular docking.

  10. Bushan Kumar ParameswaraMarch 31, 2022 at 9:13 AM

    Informative and well done

    5

    Very nice slides and explanation done for every topic. Very Good course.

  11. Jaime Andrés Úsuga RestrepoFebruary 21, 2022 at 10:31 PM

    Review

    5

    Great course!

  12. Rishi Nandan GargJanuary 8, 2022 at 3:03 PM

    Great learning

    5

    Very informative sessions

  13. Molecular docking

    4

    It was a great experience with this course. The content was very much informative and the pace of teaching was optimum.

  14. SHIFRA SARA SAJIApril 11, 2022 at 8:04 AM

    Molecular Docking Review

    4

    Good course. The course was helpful and informative. Thank you…

  15. Keerthi ChikmathJanuary 28, 2022 at 7:33 PM

    Molecular docking

    4

    Very detailed explanation was provided and the concepts were easy and understandable

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