A Step-by-Step Guide to Homology Modelling Using Modeller
Understanding protein structures is crucial in modern biology and drug discovery. The three-dimensional (3D) structures of proteins play a vital role in determining their functions and interactions with other molecules. One powerful technique for predicting protein structures is homology modelling, which utilizes known structures of related proteins as templates to predict the structure of a target protein. In this article, we will provide a step-by-step guide to homology modelling using Modeller, a widely-used software tool for this purpose.
Proteins are fundamental building blocks of living organisms and are responsible for various biological functions. A protein's function is directly linked to its 3D structure, which is determined by the arrangement of its constituent amino acids. Homology modelling, also known as comparative modelling, is a computational method that predicts the 3D structure of a target protein based on the known structures of related proteins, called templates.
2. Getting Started with Modeller
Modeller is a versatile software package that aids researchers in creating accurate homology models. Before starting, ensure you have installed Modeller on your system. The input requirements include the target protein sequence and one or more template sequences. The better the template resembles the target, the more accurate the model will be.
3. Template Selection and Alignment
Selecting suitable templates is critical to the success of homology modelling. Templates should share high sequence identity with the target protein and have known experimental structures. Sequence alignment is the process of matching target and template sequences to identify corresponding amino acids.
Software: BLAST search
Alignment will be done using align2d.py (modeller script) program of modeller. The alignment was written in two formats namely ‘PIR’ and ‘PAP’.
4. Model Building and Optimization
Once the alignment is complete, Modeller constructs an initial 3D model of the target protein based on the aligned template's coordinates. The model is then optimized using molecular dynamics simulations and energy minimization techniques to relieve any steric clashes and improve its stability. By using model_single.py (Modeller script) the model will be generated.
5. Validating the Homology Model
The quality of the homology model is essential for reliable results. Several validation tools, such as Ramachandran plot analysis, VERIFY3D, ERRAT, ProSA-web, and MolProbity, can assess the model's stereochemistry, energy distribution, and overall quality.
6. Homology Modelling in Drug Discovery
Homology modelling plays a vital role in drug discovery by providing insights into protein-ligand interactions and aiding structure-based drug design. Several successful drug design case studies have utilized homology models to identify potential drug candidates.
Tips and Best Practices for Successful Homology Modelling
Ensuring the quality of the homology model requires attention to various factors, such as the choice of templates, sequence alignment parameters, and refinement techniques.
Future Perspectives in Protein Structure Prediction
The field of protein structure prediction continues to advance rapidly. Integrating experimental data and adopting deep learning approaches hold promise for further improving the accuracy of homology models.
FAQs
1. What is homology modelling?
Homology modelling is a computational technique used to predict the 3D structure of a protein based on the structures of related proteins.
2. How important are protein 3D structures?
Protein 3D structures are crucial as they directly relate to their functions and interactions with other molecules.
3. Why is template selection critical in homology modelling?
Template selection determines the accuracy of the resulting homology model; better templates lead to more reliable predictions.
4. What validation tools are used for homology models?
Validation tools such as Ramachandran plot analysis, VERIFY3D, ERRAT, ProSA-web, and MolProbity assess the quality of homology models.
5. How does homology modelling contribute to drug discovery?
Homology modelling helps identify potential drug candidates and aids in understanding protein-ligand interactions in drug discovery.
Author
Ajithkumar.B M.Sc.,