Homology modeling, also known as comparative modeling of protein, refers to constructing an atomic-resolution model of the "target" protein from its amino acid sequence and an experimental three-dimensional structure of a related homologous protein.

1. Homology
Modeling of
Proteins

2. Agenda

3. Introduction

4. Why
Computational
Approach?

5. Why?
Goal
Characterize and identify the
large number of protein
sequences that are being
discovered.
3D structure
Design of drugs, design of site-
directed mutations, to
understand how proteins
function and interact with each
other.
Experimental
structure
Developing a
structural model for a protein for
which there is no solved
experimental structure
available.
Homology
modeling
3D structure of a target protein
based on the similarity between
template and target sequences.
Predicts the 3D structure of
a protein through the sequence
alignment of template proteins.
Significance
To studying membrane
proteins that are hard to
crystallize like GPCR as it
provides a higher degree of
understanding of receptor-
ligand interaction.

6. What is Homology Modeling?

7. Accuracy and Application of Protein Structure

8. Does the sequence similarity implies
structural similarity?

9. Homology
Modeling

10. Structure
prediction
by Homology
Modeling
Identify related
structures
Select template
Align target
sequence with
template sequence
Build a model for the
target (Using
information from the
template structures)
Evaluate the Model
Model OK? END
YES
NO

11. Homology
Modeling Steps
YES
1.
• Template recognition and initial alignment
2.
• Alignment correction
3.
• Backbone generation
4.
• Loop modeling
5.
• Side-chain modeling
6.
• Model optimization
7.
• Model validation

12. 1. Template Recognition

13. BLAST

14. To obtain the list of hits-the modeling
templates & corresponding alignments
COMPARES QUERY SEQUENCE TO ALL THE SEQUENCES OF KNOWN STRUCTURES IN PDB
USING TWO MATRICES: A RESIDUE EXCHANGE MATRIX, AN ALIGNMENT MATRIX.

15. 2. Alignment Correction

17. 3. Backbone generation

18. 4. Loop optimization
The red loop is modeled with the green
residues as anchor residues. The insertion
of 2 residues results in a longer loop.

19. 5. Side-Chain Modeling
rotamer
libraries

20. 6. Model Optimization

21. 7. Model Validation
rotamer
libraries

22. Evaluation servers
http://genesilico.pl/
https://player.slideplayer.com/24/7086252/#
https://player.slideplayer.com/24/7086252/#
https://player.slideplayer.com/24/7086252/#
https://player.slideplayer.com/24/7086252/#
Evaluate
the model
Model
OK?
• YES

23. ADVANTAGES AND DISADVANTAGES

24. Example
https://docs.google.com/document/d/1BbQIA7165
Z-
uidB1ojgZEgUfijAcpwic4XuMZbsznic/edit?usp=sh

25. References
• Insight II manual http://www.csc.fi/chem/progs/insightII.phtml.en#manual
• Structural Bioinformatics, Philip E Bourne, Helge Weissig
• Bioinformatics Sequence and Genome Analysis, David W Mount
http://ncisgi.ncifcrf.gov/~ravichas/HomMod/
http://www.biochem.vt.edu/modeling/homology.html
http://www.cmbi.kun.nl/gv/articles/text/gambling0.html

26. Summary

27. Thank You