02/03/2026

Registration closes 02/03/2026

Protein Structure Prediction Using MODELLER: From Sequence to Validated 3D Model

Transform Protein Sequences into Reliable 3D Structures.

  • Mode: Virtual / Online
  • Type: Mentor Based
  • Level:
  • Duration: 3 Days
  • Starts: 3 February 2026
  • Time: 8:00 PM IST

About This Course

Protein structure is essential for understanding biological function, molecular interactions, and disease mechanisms. When experimental structures are unavailable, homology modeling provides a reliable approach by leveraging known templates from the Protein Data Bank (PDB). Accurate modeling depends on selecting suitable templates, building high-quality alignments, generating multiple candidate models, and validating structural quality before use in docking or simulation studies.

In this workshop, participants will learn a complete MODELLER workflow: sequence retrieval, BLAST-based template search, alignment building, automated model generation, loop refinement, and model ranking using scoring functions (e.g., DOPE). Participants will also validate models using standard structural checks such as Ramachandran plots and quality scores, enabling confident selection of the best 3D model for research applications.

Aim

This workshop aims to train participants in protein structure prediction using comparative (homology) modeling with MODELLER. It guides learners through the complete workflow from protein sequence analysis to building, refining, and validating 3D structural models. Participants will understand how sequence similarity, template selection, and model assessment influence structural accuracy. The program emphasizes practical, dry-lab skills relevant to structural biology and drug discovery.

Workshop Objectives

  • Analyze protein sequences and identify suitable templates.
  • Perform accurate sequence–structure alignments.
  • Build 3D protein models using MODELLER.
  • Refine models and address structural gaps or loops.
  • Validate and interpret model quality using standard metrics.

Workshop Structure

Day 1: Homology Modeling Workflow & Building the First Model

  • Homology modeling (when to use MODELLER vs AlphaFold)
  • Inputs & concepts: target sequence, templates, alignment, loops
  • (PDB/BLAST) & choosing the best templates (identity, coverage, resolution)
  • Alignment preparation (common alignment mistakes)
  • MODELLER setup: installation, environment, file formats (PIR/ALI)
  • Hands-on: Build a basic homology model (single-template or multi-template)
  • Tools: MODELLER, BLAST/PDB, UniProt, PyMOL/ChimeraX

Day 2: Refinement, Validation & Reporting

  • Loop modeling (short loops vs difficult regions)
  • Refinement overview (energy minimization idea; restraints)
  • Model validation essentials:
  • Ramachandran (stereochemistry)
  • Verify3D / ERRAT / ProSA (quick quality checks)
  • Structural comparison to template (RMSD, superposition)
  • Hands-on: Loop refinement + validate and generate a “model quality report.”
  • Tools: MODELLER, PyMOL/ChimeraX, PROCHECK/RAMPAGE, ProSA, Verify3D, ERRAT

Who Should Enrol?

  • Doctoral Scholars & Researchers: PhD candidates seeking to integrate computational workflows into their molecular research.
  • Postdoctoral Fellows: Early-career scientists aiming to enhance their data-driven publication profile.
  • University Faculty: Professors and HODs interested in modern bioinformatics pedagogy and tool mastery.
  • Industry Scientists: R&D professionals from the Biotechnology and Pharmaceutical sectors transitioning to genomic-driven discovery.
  • Postgraduate Students: Final-year PG students looking for specialized research-grade exposure beyond standard curricula.

Important Dates

Registration Ends

01/12/2026
IST 7:00 PM

Workshop Dates

02/03/2026 – 02/05/2026
IST 8:00 PM

Workshop Outcomes

  • Build accurate 3D protein models using homology modeling.
  • Evaluate model quality using structural validation tools.
  • Understand strengths and limitations of comparative modeling.
  • Generate structures suitable for docking, MD simulations, or functional studies.
  • Apply protein modeling workflows in research or industry projects.

Fee Structure

Student Fee

₹1799 | $70

Ph.D. Scholar / Researcher Fee

₹2799 | $80

Academician / Faculty Fee

₹3799 | $95

Industry Professional Fee

₹4799 | $110

What You’ll Gain

  • Live & recorded sessions
  • e-Certificate upon completion
  • Post-workshop query support
  • Hands-on learning experience

Join Our Hall of Fame!

Take your research to the next level with NanoSchool.

Publication Opportunity

Get published in a prestigious open-access journal.

Centre of Excellence

Become part of an elite research community.

Networking & Learning

Connect with global researchers and mentors.

Global Recognition

Worth ₹20,000 / $1,000 in academic value.

Need Help?

We’re here for you!


(+91) 120-4781-217

★★★★★
Scientific Paper Writing: Tools and AI for Efficient and Effective Research Communication

excellent

Shabihul Sayed
★★★★★
AI for Environmental Monitoring and Sustainablility

Menthor was easy to follow

IVANA PILJEK MILETIĆ
★★★★★
Urban Metabolism Modeling with AI

Thank you for the workshop.

Paula Noya Vázquez
★★★★★
AI for Healthcare Applications

NA

Aimun A. E. Ahmed

View All Feedbacks →

Stay Updated


Join our mailing list for exclusive offers and course announcements

Ai Subscriber