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Computational prediction methods play an essential role to provide us with structural information of a sequence whose structure has not been experimentally determined.Homology based or comparative modeling  is the most detailed and accurate of all current protein structure prediction techniques .In this process a variety of programs and web servers can be used (Table 1).
All current comparative modeling methods consist of four sequential steps: template selection, target-template alignment, model building and model evaluation.
Essentially, this is an iterative procedure until a satisfactory model is obtained (Figure 1).
On the last two decades the development of recombinant DNA techniques has extended the use of microbial organisms to produce target proteins.
The enteric bacterium Escherichia coli is one of the most extensively used prokaryotic organisms for genetic manipulations and for industrial production of proteins of therapeutic or commercial interest [1, 2].
Microbial cell factories play a key role in this context.
This review is intended to give a primer addressed to scientists of disciplines related to microbial cell factories who has no expertise in comparative modeling.
Our goal is to provide the seeding background to understand concepts, opportunities and challenges of comparative modeling.
We will describe each step in the comparative modeling process, discuss the most common errors and how to solve them, as well as outlining the applications of comparative modeling in the field of microbial cell factories.
Its aim is to build a three-dimensional model for a protein of unknown structure on the basis of sequence similarity to proteins of known structure .
Comparative modeling relies on the fact that structure is more conserved than sequence during evolution.