Mapping protein?protein interactions by bioinformatics and cross-linking

Abstract

Protein–protein interactions play a key role in many cellular processes. Determining the protein interaction network is one of the major tasks of functional proteomics. Databases of protein interactions integrate the large amounts of information available on protein– protein interactions, ranging from functional interactions (such as which proteins are involved in a common metabolic pathway) to physical interactions (like which proteins form a complex) [1]. Whereas the amount of information regarding protein structures and protein– protein interactions is steadily increasing, structural determination of protein–protein complexes using experimental methods such as X-ray crystallography, NMR spectroscopy and electron microscopy is lagging behind [2]. Hence, bioinformatic methods for predicting protein interactions sites and structures of protein complexes are becoming increasingly important. The predictive power of these methods is measured at regular intervals using critical assessment of predicted interactions (CAPRI) [3]. One lesson from these studies is that great benefit can be obtained by combining protein–protein docking with data from other predictive methods and the results of experimental approaches yielding low resolution structural information. Experimental data can be obtained by a variety of methods [2]; here the focus will be on chemical cross-linking, a classical method which has gained renewed attention due to advances in molecular biology, chemical synthesis and mass spectrometric analysis. Bioinformatic methods for predicting protein interaction sites