Ohio Collaborative Conference on Bioinformatics (OCCBIO)
Connecting Ohio's Bioinformatics and Bioscience Research Leaders

Tutorial Abstract

Tutorial 3: Homology Modeling

Title: Prediction of the Tertiary Structures of Proteins via Homology Modeling
Presenter: Xiche Hu, Associate Professor, University of Toledo

Abstract: Reliable prediction of the tertiary structure of a protein from its primary sequence represents an important goal of modern theory, but remains an outstanding problem in the field of biology.  Although the principle of sequence determines structure is firmly established, the underlying physics is not fully understood to the extent of an ab initio prediction, yet.  However, one practical method that can be applied to generate models of protein structures with a great degree of success is homology modeling.  In homology modeling, we are attempting to predict a three-dimensional model of a target protein for which only the sequence is available, provided an empirical 3D "template" structure is available with >30% sequence identity.  It is based on an important observation that for a set of proteins that are hypothesized to be homologous, their three-dimensional structures are conserved to a greater extent than are their primary structures.

In this tutorial, participants will study principles and techniques of homology modeling, including

1. identify homologous proteins and determine the extent of their sequence similarity with one another and the unknown
2. align the sequences
3. identify structurally conserved and structurally variable regions
4. generate coordinates for core (structurally conserved) residues of the unknown structure from those of the known structure(s)
5. generate conformations for the loops (structurally variable) in the unknown structure
6. build the side-chain conformations
7. refine and evaluate the unknown structure

and gain practical experience doing homology modeling with a webserver such as SWISS-MODELLER , 3D-Jigsaw homology or What-IF.

Back to schedule