Name
Abstract | ||
|---|---|---|
Protein-protein interactions can be characterized by high-resolution structures of complexes, from which diverse features of the interfaces can be derived. For the majority of protein- protein interactions identified, however, there is no information on the structure of the complex or the interface involved in the interaction. Understanding what surface properties drive certain interactions is crucial in the functional evaluation of protein complexes. Here we show that the local patterning of the physicochemical properties of amino acids within surface patches is characteristic of interfaces. To describe this feature in a quantitative manner, we have defined a statistical potential, iPat, as a measure of surface patterning. iPat, which does not take evolutionary conservation or knowledge of the interaction partner into consideration, represents a function principally different from algorithms that consider intermolecular contacts. We assess its suitability for characterizing protein and peptide interfaces, and we demonstrate that iPat is uniquely descriptive for interfaces of proteins that undergo large conformational changes or that are involved in the binding of intrinsically disordered protein (IDP) partners. We suggest that as a stand-alone propensity or in combination with other features, iPat represents a new feature in analyzing the functional binding specificity of protein-protein interactions that has better predictive potential than other simple ID features, such as hydrophobicity or stickiness. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1021/acs.jcim.8b00270 | JOURNAL OF CHEMICAL INFORMATION AND MODELING |
DocType | Volume | Issue |
Journal | 58 | 10 |
ISSN | Citations | PageRank |
1549-9596 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tamas Lazar | 1 | 0 | 0.34 |
| Mainak Guharoy | 2 | 24 | 2.42 |
| Eva Schad | 3 | 7 | 1.15 |
| Peter Tompa | 4 | 261 | 16.64 |