Abstract
Protein‐protein interactions are critical to protein function, but three‐dimensional (3D) arrangements of interacting proteins have proven hard to predict, even given the identities and 3D structures of the interacting partners. Specifically, identifying the relevant pairwise interaction surfaces remains difficult, often relying on shape complementarity with molecular docking while accounting for molecular motions to optimize rigid 3D translations and rotations. However, such approaches can be computationally expensive, and faster, less accurate approximations may prove useful for large‐scale prediction and assembly of 3D structures of multi‐protein complexes. We asked if a reduced representation of protein geometry retains enough information about molecular properties to predict pairwise protein interaction interfaces that are tolerant of limited structural rearrangements. Here, we describe a reduced representation of 3D protein accessible surfaces on which molecular properties such as charge, hydrophobicity, and evolutionary rate can be easily mapped, implemented in the MorphProt package. Pairs of surfaces are compared to rapidly assess partner‐specific potential surface complementarity. On two available benchmarks of 185 overall known protein complexes, we observe predictions comparable to other structure‐based tools at correctly identifying protein interaction surfaces. Furthermore, we examined the effect of molecular motion through normal mode simulation on a benchmark receptor‐ligand pair and observed no marked loss of predictive accuracy for distortions of up to 6 Å Cα‐RMSD. Thus, a shape reduction of protein surfaces retains considerable information about surface complementarity, offers enhanced speed of comparison relative to more complex geometric representations, and exhibits tolerance to conformational changes.
Highlights
IntroductionProteins often assemble into multi-protein complexes as their native forms, mediated by pairwise (or higher-order) protein-protein interactions
Proteins often assemble into multi-protein complexes as their native forms, mediated by pairwise protein-protein interactions
We wished to test if a highly simplified geometric representation of a 3D protein surface embedded with properties was sufficient to predict protein-protein interaction interfaces
Summary
Proteins often assemble into multi-protein complexes as their native forms, mediated by pairwise (or higher-order) protein-protein interactions. More indirect experimental techniques, including mutagenesis[3, 4], mass spectrometry[5], and cross-linking analysis[6], can illuminate the specific residues that participate in these interaction interfaces. These techniques give partial information about the three-dimensional (3D) information on the assembly of complexes, and new integrative computational modeling strategies are increasingly able to consider such data as distance restraints to infer 3D structures[7,8,9,10]. To complement such experimentally-led approaches, there has been a strong push to develop better computational approaches for predicting protein interaction interfaces directly from protein amino acid sequences and 3D structures
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