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Homology modelling of the human eIF-5A protein has been performed by using a multiple predictions strategy. As the sequence identity between the target and the template proteins is nearly 30%, which is lower than the commonly used threshold to apply with confidence the homology modelling method, we developed a specific predictive scheme by combining different sequence analyses and predictions, as well as model validation by comparison to structural experimental information. The target sequence has been used to find homologues within sequence databases and a multiple alignment has been created. Secondary structure for each single protein has been predicted and compared on the basis of the multiple sequence alignment, in order to evaluate and adjust carefully any gap. Therefore, comparative modelling has been applied to create the model of the protein on the basis of the optimized sequence alignment. The quality of the model has been checked by computational methods and the structural features have been compared to experimental information, giving us a good validation of the reliability of the model and its correspondence to the protein structure in solution. Last, the model was deposited in the Protein Data Bank to be accessible for studies on the structure-function relationships of the human eIF-5A.

Homology modelling of the human eukaryotic initiation factor 5A (eIF-5A)