Using desolvation energies of structural domains to predict stability of protein complexes

Abstract

Employing domain knowledge for prediction of particular types of protein-protein interactions (PPIs) is a problem that has become increasingly important in the past few years, due to the fundamental role of domains in protein function. We propose a model to predict obligate and non-obligate protein interaction types using desolvation energies of structural domains that are present in the interfaces of protein complexes, which are extracted from the CATH database. The prediction is performed using several state-of-the-art classification techniques, including linear dimensionality reduction, a support vector machine based on sequential minimal optimization, naive Bayes, and k-nearest neighbour. Our results on two well-known datasets demonstrate that (a) domain-based features of higher levels of CATH, especially level 2, are more powerful and discriminative than features of other levels, and (b) properties taken from different levels of the CATH hierarchy yield higher accuracies than properties taken from each level of the hierarchy separately. Furthermore, analysis of structural properties suggests that domaindomain interactions that have at least a mainly-beta secondary structure in one sub-unit are more informative for predicting obligate and non-obligate PPIs.

Competition-cooperation relationship networks characterize the competition and cooperation between proteins

“…However, if the interactions between the competing proteins and the common protein are weak, they may not cause strong functional implications. Indeed, a number of studies have demonstrated that on the basis of interaction strength, PPIs could be classified into transient or permanent ones 4 36 37 . If two proteins permanently interact with a common protein on the same interface, they may compete more intensively and should be more strictly regulated in vivo .…”

Computational analysis of the stability of SCF ligases employing domain information

“…As a consequence, recent studies focus on employing domain knowledge to predict protein-protein interactions (PPIs) [4]. There are few domain family resources that can be applied for this purpose such as Pfam and CATH -Class, Architecture, Topology and Homologous superfamily -databases.…”