Improving the Understanding of Human Genetic Diseases Through Predictions of Protein Structures and Protein-Protein Interaction Sites

Huan-Xiang      Zhou

doi:10.2174/0929867043455800

Abstract

Over 1,500 human disease genes have been identified,of which only a small fraction have experimental structural information on the protein products.To better understand the mechanisms of these hereditary diseases,we undertook a systematic study to predict the structures of disease proteins and characterize their interactions with other proteins.This study was facilitated by two tools developed previously:(1) COBLATH,a structure-prediction method that exploits the complementarity of PSI-Blast and sequence-structure threading and PPISP,a method that predicts the residues involved in protein-protein interactions.In this initial study of human disease proteins, we were able to build structural models for 60 proteins involved in human diseases.For a number of proteins, new structural domains were identified.In the case of ABCD1,a protein responsible for adrenoleukodystrophy, the disease mutation P484R was positioned at the homodimer interface.This positioning is consistent with experimental observation that the P484R mutation impairs ABCD1 self-interaction and suggests that that the disease mechanism of this mutation lies in the impaired ABCD1 dimerization.This initial study illustrates the value of the predicted structure models and may serve as an example for expanded studies of other disease proteins.

Keywords: disease gene, disease mechanism, protein structure, structure prediction, protein-protein, interaction

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