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Take your bioinformatics knowledge beyond sequences and step into the fascinating world of 3D biomolecular structures, protein modelling, molecular docking, structural analysis and AI-based structure prediction.

The Structural Bioinformatics Certification Course by BioTecNika is a self-learning program designed to help students, researchers and life science professionals understand how the three-dimensional structure of biomolecules can be analysed and used in biological research, disease studies and drug discovery.

From exploring protein structures in the Protein Data Bank to working with PyMOL, molecular docking, homology modelling and AlphaFold, this course takes you through the essential concepts and practical applications of modern structural bioinformatics.

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Course Highlights

✓ Self-Learning Certification Course

✓ 30 Days Course Access

✓ Learn Anytime, Anywhere, at Your Own Pace

✓ Beginner-Friendly, Easy-to-Follow Lectures

✓ Practical Demonstrations of Structural Bioinformatics Tools & Software

✓ Learn Protein Structure Visualization Using PyMOL

✓ Understand Molecular Docking & Protein-Ligand Interactions

✓ Explore Homology Modelling & Protein Structure Prediction

✓ Learn the Fundamentals of Molecular Dynamics

✓ Understand AlphaFold & AI-Based Protein Structure Prediction

✓ Learn Applications in Drug Discovery & Life Science Research

✓ Earn a BioTecNika Course Completion Certificate - Soft Copy

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What Will You Learn?

By the end of this course, you will develop an understanding of how structural information can be used to investigate biological molecules and their functions.

You will learn how to:

• Understand the different levels of protein structure

• Retrieve and analyse structures from the Protein Data Bank – PDB

• Understand X-ray crystallography, NMR and Cryo-EM

• Visualize and analyse biomolecular structures using PyMOL

• Select residues, chains and ligands within protein structures

• Measure molecular distances, angles and interactions

• Align and superimpose protein structures

• Understand RMSD and structural similarity

• Explore structural classification databases such as SCOP and CATH

• Understand the fundamentals of Molecular Dynamics simulations

• Study protein-ligand interactions

• Understand the principles of Molecular Docking

• Explore tools such as AutoDock Vina and SwissDock

• Build protein structures using Homology Modelling

• Work with resources such as SWISS-MODEL

• Understand AlphaFold2 and RoseTTAFold

• Evaluate predicted protein structures

• Understand Ramachandran plots, clashscores and model-quality parameters

• Explore applications of structural bioinformatics in drug discovery, disease biology and structure-based drug design

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Detailed Course Curriculum

Session 1: Introduction to 3D Biomolecules and the Protein Data Bank – PDB

Understand why the three-dimensional structure of biological molecules is so important for understanding their function.

Topics Covered

• Central Dogma and the structure-function paradigm

• Primary, secondary, tertiary and quaternary protein structures

• Introduction to nucleic acid structures

• Introduction to carbohydrate structures

• Worldwide Protein Data Bank – wwPDB

• Understanding the anatomy of a PDB file

• Header and coordinate sections of PDB files

Practical Demonstration

Learn how to retrieve PDB entries for proteins such as Insulin and Hemoglobin, explore RCSB PDB entry pages and download structural files.

Faculty: Mr. Prodyot

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Session 2: Methods for Structure Determination

Learn how scientists experimentally determine three-dimensional biomolecular structures.

Topics Covered

• X-ray Crystallography

• Electron density maps

• Structural resolution

• Nuclear Magnetic Resonance – NMR Spectroscopy

• NMR ensembles

• Cryo-Electron Microscopy – Cryo-EM

• Cryo-EM map interpretation

• Comparison of structural determination techniques

• Resolution, throughput and molecular-size limitations

Practical Demonstration

Use the RCSB PDB database to filter structures based on experimental methods and resolution and understand important structure-quality parameters.

Faculty: Dr. Nilofer

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Session 3: Structural Visualization and Analysis With PyMOL – Part 1

Get introduced to one of the most widely used molecular visualization platforms in structural biology.

Topics Covered

• Introduction to the PyMOL interface

• Loading and saving structures

• Orienting and zooming molecules

• Structure representations

• Lines, sticks, cartoons and surfaces

• Selecting residues, chains and ligands

• Measuring distances

• Measuring angles and dihedral angles

Practical Demonstration

Visualize Lysozyme, colour the structure based on elements and structural features, examine the active site, perform molecular measurements and create a publication-quality structural image.

Faculty: Dr. Neeraj

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Session 4: Structural Visualization and Analysis With PyMOL – Part 2

Move beyond basic visualization and explore more advanced structural analysis using PyMOL.

Topics Covered

• Aligning protein structures

• Structural superposition

• Creating and managing PyMOL sessions

• In-silico mutation using the Mutagenesis Wizard

• Introduction to PyMOL scripting

• PyMOL command line

• Working with script files

Practical Demonstration

Superimpose homologous protein structures, analyse conserved and variable regions and create figures demonstrating structural alignment.

Faculty: Dr. Neeraj

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Session 5: Structure Comparison and Alignment

Learn how researchers quantitatively compare protein structures and investigate their evolutionary relationships.

Topics Covered

• Structural similarity versus sequence similarity

• Root Mean Square Deviation – RMSD

• Structural alignment algorithms

• DALI

• CE

• TM-align

• Structural protein classification

• SCOP database

• CATH database

Practical Demonstration

Use DALI to identify structural neighbours of a protein, interpret Z-scores and RMSD values and explore the structural classification of proteins using SCOP and CATH.

Faculty: Ms. Shubhi

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Session 6: Introduction to Molecular Simulation and Dynamics

Understand how computational methods are used to simulate molecular movements and protein flexibility.

Topics Covered

• Molecular mechanics

• Force fields

• Fundamentals of Molecular Dynamics – MD

• Energy minimization

• Equilibration

• Production runs

• Protein flexibility

• Conformational changes

• Binding energies

• Molecular trajectory visualization

Practical Demonstration

Observe and analyse a short molecular dynamics trajectory of a protein using molecular visualization tools such as PyMOL or VMD and identify flexible regions of the structure.

Faculty: Mr. Prodyot

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Session 7: Protein-Ligand Interactions and Molecular Docking

Understand one of the most important computational approaches used in modern drug discovery.

Topics Covered

• Protein-ligand interactions

• Hydrogen bonding

• Hydrophobic interactions

• Electrostatic interactions

• Principles of molecular docking

• Ligand flexibility

• Protein flexibility

• Docking scoring functions

• AutoDock Vina

• GOLD

Practical Demonstration

Learn how a known inhibitor can be docked into its protein target using tools such as SwissDock or AutoDock Vina and analyse the predicted binding pose.

Faculty: Dr. Nilofer

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Session 8: Homology Modelling

Learn how researchers predict the three-dimensional structure of a protein when an experimentally determined structure is unavailable.

Topics Covered

• Principles of homology modelling

• Template identification

• Target-template alignment

• Model building

• Loop modelling

• Side-chain placement

• Model optimization

• SWISS-MODEL

• MODELLER

Practical Demonstration

Build a protein structure model using the SWISS-MODEL server and evaluate the quality of the generated model.

Faculty: Ms. Shubhi

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Session 9: The AlphaFold Revolution and Model Validation

Discover how Artificial Intelligence and Deep Learning have transformed protein structure prediction.

Topics Covered

• Introduction to Deep Learning in structural bioinformatics

• AlphaFold2

• RoseTTAFold

• AI-based structure prediction

• AlphaFold Protein Structure Database

• Model-quality assessment

• Ramachandran plots

• Clashscores

• Z-scores

• MolProbity

Practical Demonstration

Retrieve an AlphaFold-predicted protein structure, compare it with an experimentally determined structure and understand the important parameters used for protein model validation.

Faculty: Dr. Elamathi

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Session 10: The Power of Structure – Applications in Life Sciences and Drug Discovery

Bring everything together and understand how structural bioinformatics is being applied across biological research and pharmaceutical development.

Topics Covered

• Moving from sequence to biological function

• Understanding enzymatic mechanisms

• Understanding metabolic pathways

• Studying diseases at the atomic level

• Viral entry mechanisms

• SARS-CoV-2 Spike Protein and ACE2 interaction

• Target identification and validation

• Structure-Based Drug Design – SBDD

• Protein structures in drug development

• HIV protease inhibitors as a historical example

• Lead optimization

• Structure-Activity Relationships – SAR

• Improving potency and selectivity

• Understanding structural approaches to reducing drug toxicity

• Role of AlphaFold2 and Cryo-EM in modern research

• Future applications of structural bioinformatics

Faculty: Dr. Elamathi

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Tools & Resources Introduced During the Course

Get exposure to important structural bioinformatics platforms, databases and computational tools, including:

• RCSB Protein Data Bank – PDB
• PyMOL
• VMD
• DALI
• TM-align
• SCOP
• CATH
• AutoDock Vina
• SwissDock
• GOLD
• SWISS-MODEL
• MODELLER
• AlphaFold Protein Structure Database
• AlphaFold2
• RoseTTAFold
• MolProbity

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Who Should Enrol?

This certification course is suitable for:

• BSc / MSc Life Science Students

• Biotechnology Students

• Bioinformatics Students

• Biochemistry Students

• Microbiology Students

• Molecular Biology Students

• Computational Biology Students

• BTech / MTech Biotechnology Students

• Pharmacy & Pharmaceutical Science Students

• PhD Scholars

• Research Scholars

• Research Assistants

• Life Science Professionals

• Researchers interested in structural biology

• Students interested in computational drug discovery

• Anyone looking to build skills in Structural Bioinformatics

New to Structural Bioinformatics?

No problem.

The course begins with fundamental concepts of biomolecular structures before progressing towards visualization, structural comparison, molecular dynamics, docking, homology modelling and AI-based structure prediction.

The lectures are designed to make the learning process easy to understand and practical to follow.

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Why Learn Structural Bioinformatics?

Knowing the sequence of a gene or protein tells us only part of the story.

Its 3D structure provides crucial information about how the molecule functions, how it interacts with other molecules, how mutations may affect its behaviour and how potential drugs can interact with it.

Structural bioinformatics therefore plays an important role in areas such as:

• Protein function analysis

• Molecular biology research

• Disease mechanism studies

• Computational biology

• Protein engineering

• Molecular modelling

• Drug-target interaction studies

• Molecular docking

• Structure-Based Drug Design

• Pharmaceutical research

• AI-based protein structure prediction

With technologies such as Cryo-EM and AlphaFold rapidly expanding the availability of structural information, understanding how to analyse and interpret biomolecular structures is becoming an increasingly valuable skill for life science researchers.

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Learn Through Practical Demonstrations

Structural bioinformatics cannot be understood through theory alone.

That is why this course includes practical demonstrations showing how important structural bioinformatics databases and software can actually be used.

Instead of simply learning definitions, you will see how researchers:

• Retrieve real protein structures

• Visualize proteins in 3D

• Analyse active sites

• Measure molecular interactions

• Compare protein structures

• Perform structural alignment

• Examine Molecular Dynamics trajectories

• Study protein-ligand binding

• Perform molecular docking

• Generate homology models

• Retrieve AlphaFold predictions

• Assess protein model quality

This practical exposure makes it easier to connect theoretical concepts with their real research applications.

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Learn Anytime, Anywhere

This is a self-learning certification course, allowing you to study according to your own schedule.

You receive 30 days of course access, giving you the flexibility to:

✓ Learn at your own pace

✓ Revisit important concepts

✓ Watch practical demonstrations carefully

✓ Study around your college, research or work schedule

✓ Access the training whenever it is convenient for you

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Earn a BioTecNika Certificate

Earn a BioTecNika Certificate — Trusted in the Biosciences Industry for Over Two Decades

After completing the Structural Bioinformatics Certification Course, you will receive a BioTecNika Course Completion Certificate showcasing your upskilling in Structural Bioinformatics.

Add it to your:

• Resume / CV

• LinkedIn Profile

• Academic Portfolio

• Research Profile

• Internship Applications

• Higher Education Applications

• Professional Skill Portfolio

A simple way to demonstrate that you have taken the initiative to develop skills beyond your regular academic curriculum.

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Build a Stronger Foundation for Modern Bioscience Research

Structural biology, computational biology, Artificial Intelligence and drug discovery are becoming increasingly interconnected.

Whether you want to understand protein structures, explore molecular modelling, enter computational research or simply add an important bioinformatics skill to your profile, this course gives you a structured starting point.

Enrol in the Structural Bioinformatics Certification Course Today

Self-Learning | 30 Days Access | Practical Software Demonstrations | BioTecNika Certificate

Start learning at your own pace and add Structural Bioinformatics to your scientific skill set.