Atomic-level evolutionary information improves protein-protein interface scoring

Chloé Quignot (1, 2) , Pierre Granger (1, 2) , Pablo Chacón (3) , Raphael Guerois (1, 2) , Jessica Andreani (1, 2)

1 I2BC - Institut de Biologie Intégrative de la Cellule
2 JOLIOT - Institut des Sciences du Vivant Frédéric JOLIOT
3 IQFR - Instituto de Química Física Rocasolano

The crucial role of protein interactions and the difficulty in characterising them experimentally strongly motivates the development of computational approaches for structural prediction. Even when protein-protein docking samples correct models, current scoring functions struggle to discriminate them from incorrect decoys. The previous incorporation of conservation and coevolution information has shown promise for improving protein-protein scoring. Here, we present a novel strategy to integrate atomic-level evolutionary information into different types of scoring functions to improve their docking discrimination. We applied this general strategy to our residue-level statistical potential from InterEvScore and to two atomic-level scores, SOAP-PP and Rosetta interface score (ISC). Including evolutionary information from as few as ten homologous sequences improves the top 10 success rates of these individual scores by respectively 6.5, 6 and 13.5 percentage points, on a large benchmark of 752 docking cases. The best individual homology-enriched score reaches a top 10 success rate of 34.4%. A consensus approach based on the complementarity between different homology-enriched scores further increases the top 10 success rate to 40%. All data used for benchmarking and scoring results, as well as pipelining scripts, are available at http://biodev.cea.fr/interevol/interevdata/

Mots clés: protein-protein interactions; protein docking; protein scoring; protein evolution; protein structure; structural bioinformatics

Domaines: Bio-informatique [q-bio.QM]; Biochimie [q-bio.BM]; Biochimie, Biologie Moléculaire; Biophysique

Chloé Quignot, Pierre Granger, Pablo Chacón, Raphael Guerois, Jessica Andreani. Atomic-level evolutionary information improves protein-protein interface scoring. 2020. ⟨cea-02978447v1⟩