Local Interaction Signal Analysis Predicts Protein-Protein Binding Affinity

Raffaele Raucci (1, 2) , Elodie Laine (1) , Alessandra Carbone (1, 3)

1 LCQB-AG - Analytical Genomics [LCQB]
2 ISCD - Institut des Sciences du Calcul et des Données
3 IUF - Institut universitaire de France

Several models estimating the strength of the interaction between proteins in a complex have been proposed. By exploring the geometry of contact distribution at protein-protein interfaces, we provide an improved model of binding energy. Local interaction signal analysis (LISA) is a radial function based on terms describing favorable and non-favorable contacts obtained by density functional theory, the support-core-rim interface residue distribution, non-interacting charged residues and secondary structures contribution. The three-dimensional organization of the contacts and their contribution on localized hot-sites over the entire interaction surface were numerically evaluated. LISA achieves a correlation of 0.81 (and a root-mean-square error of 2.35 ± 0.38 kcal/mol) when tested on 125 complexes for which experimental measurements were realized. LISA's performance is stable for subsets defined by functional composition and extent of conformational changes upon complex formation. A large-scale comparison with 17 other functions demonstrated the power of the geometrical model in the understanding of complex binding.

Domaines: Biologie cellulaire

Raffaele Raucci, Elodie Laine, Alessandra Carbone. Local Interaction Signal Analysis Predicts Protein-Protein Binding Affinity. Structure, 2018, 26 (6), pp.905 - 915.e4. ⟨10.1016/j.str.2018.04.006⟩. ⟨hal-01844368⟩