Tutorial

Homology Modelling

A Brief Introduction to Homology Modeling

Sequence-Structure-Function Relationships

● Proteins of similar sequences fold into similar

structures and perform similar biological

functions.

● The protein sequence has the intrinsic information

to encode the protein structure.

The Noble Prize in Chemistry 1972

Christian B Anfinsen

"for his work on ribonuclease,

especially concerning the

connection between the amino

acid sequence and the

biologically active conformation"

From Nobel Lecture, December 11, 1972, by Christian Anfinsen

The protein sequence is sufficient to specify its 3D structure

Sequence->Structure->Function

● Widespread Automated DNA sequencing => more sequence data than structure data

● Semi-Automated pipeline of structure determination is still not widespread.

● Nevertheless, structure is more conserved than sequence.

● Sequence homologs => structural homologs

● See Chapter 9, Baxevanis and Ouellette 3rd edn.

Protein Structure Prediction vs Experimental Determination

From Chapter 9, Bryan Bergeron, Bioinformatics Computing, 2003 Pearson Education, Inc.

Structure Prediction from sequence

1.Homology (or comparative) modelling

2.Threading

3.Ab initio calculations

Homology modelling is most accurate and powerful

What is Homology Modeling?

● Homology modeling also known as comparative

modeling uses homologous sequences with known 3D

structures for the modelling and prediction of the

structure of a target sequence.

● Homology modeling is one of the most best

performing prediction methods that gives “accurate”

predicted models.

How is Homology Modeling done● Multistep process involves many steps such as:

– Sequence alignment of target/query/unknown protein sequence to homologous sequence with a known structure

– structure modification of backbone– side chain replacements– Energy minimisation for refinement of structural

model – Validation of model with visual inspection and etc

Why Homology Modeling?● The number of protein structures solved so far are fewer than

the number of genes known.

● Proteins of biological interest with their orthologous proteins

solved by X-ray crystallography or NMR can be modeled.

● Homology modeling is an important method used to predict

the structures of membrane proteins, ion channels,

transporters that are large and difficult to crystallize.

● Examples: GPCR (G Protein-coupled receptor), cytochrome

P450 etc.

Overview of the process of Homology Modeling

● A target sequence (the structure to be predicted)

● Identify the homologous sequence with known 3D as

template

● Using homology modeling software such as Modeller for

structure prediction (from the Sali Lab)

● Model evaluation and refinement

Pre-Modeling Stage: Template Identification

● Target sequence in FASTA format as input

● Blastp against PDB

● Identify proteins with “good” hit

● Pairwise or multiple sequence alignment

● Further editing the alignment results

● Realign and identify the “good” structural template

Pre-Modeling Stage: Preparing the Input Files for Modeller

● PDB files for structural templates is required

● The PIR file from the alignment results

● The script file model.top to execute the Modeller program

(latest versions use Python scripts)

In the Heart of Modeller

From the Modeller manual

Evaluation of Predicted ModelGarbage in-Garbage out

● The predicted model can be superimposed with known structure determined by experiment

http://wishart.biology.ualberta.ca/SuperPose/

● The predicted model is normally evaluated by root mean square deviation (RMSD)

From http://swissmodel.expasy.org//course/text/chapter6.htm

Calculating RMSD

• N = number of atoms, d = the distance in Angstrom between corresponding atoms in the experimental and predicted protein structures.

From Chapter 9, Bryan Bergeron, Bioinformatics Computing, 2003 Pearson Education, Inc.

● Some Rule of Thumb for Structural Modelling

● Proteins that share 35 to 50% sequence identity with their

templates, will generally deviate by 1.0 to 1.5 Å from their

experimental counter parts.

● Crystallographic structures of identical proteins can vary

not only because of experimental errors and differences in

data collection conditions and refinement, but also because

of different crystal lattice contacts and the presence or

absence of ligands.

Quality of Model

● The correctness of a model is essentially determined by the quality

of the sequence alignment used to identify the template.

● If the sequence alignment is wrong in some regions, then the

spatial arrangement of the residues in this portion of the model will

be incorrect.

Viewing the Model

● The predicted model is saved in PDB format that can be

viewed by molecular visualizing software such as

Rasmol, PyMol, MolMol, Sybyl etc.

● Viewing is an essential step to validate the quality of the

predicted model.

● In this practical, Rasmol is used to view the predicted

structure.

Model Refinement● Gaps in sequence alignment represent insertion/deletion

regions of target. Loop modeling is used to refine these

regions (not cover in this practical)

● The predicted model can be further refined by energy

minimization to remove unfavourable non-bonded

contacts with force fields such as CHARMM, AMBER

or GROMOS etc (not covered in this practical)

Web-Based Homology Modeling: The SWISS-MODEL Server

● The aim of the Internet-based SWISS-MODEL

server is to provide a comparative protein modelling

tool independent from expensive computer

hardware and software.

http://www.expasy.ch/swissmod/SWISS-MODEL.html

Steps involved in SwissModel http://swissmodel.expasy.org/

1.Take target sequence of unknown structure

2.Using BLAST to select closest homolog with known structure as structural template http://swissmodel.expasy.org/SM_Blast.html

3.Insert target sequence and homologous sequence to Web service http://swissmodel.expasy.org/SM_FIRST.html

4.Results will be emailed back to you.

5.Warning: Structure needs to be analysed and validated

Simple Homology Modelling using Modeller

1. Take target sequence of unknown structure

2. Using BLAST to select closest homolog with known structure.

3. Using Clustalx or Jalview to do pairwise alignment between target sequence and structural homolog and manual adjustment

4. Inspection of missing structural features in structural homolog

5. Preparation of alignment file align.pir

6. Use Modeller7v7 software (http://salilab.org/modeller/) to do the homology modelling

Structure Validation

● Visual inspection– Minimise torsion angles in disallowed regions of

Ramachandran plots– Maximised hydrogen bonding– Minimised exposed hydrophobic residues– Packing etc.

● Analysis – e.g. run Procheck (http://www.biochem.ucl.ac.uk/~roman/procheck/procheck.html), VADAR, Verify3D etc