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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]
LCQB - Biologie Computationnelle et Quantitative = Laboratory of Computational and Quantitative Biology
Abstract : 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.
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Submitted on : Thursday, July 19, 2018 - 12:10:31 PM
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Raffaele Raucci, Elodie Laine, Alessandra Carbone. Local Interaction Signal Analysis Predicts Protein-Protein Binding Affinity. Structure, Elsevier (Cell Press), 2018, 26 (6), pp.905 - 915.e4. ⟨10.1016/j.str.2018.04.006⟩. ⟨hal-01844368⟩



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