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Review
. 2014 Nov-Dec;116(2-3):194-202.
doi: 10.1016/j.pbiomolbio.2014.05.004. Epub 2014 May 27.

Prediction and redesign of protein-protein interactions

Rhonald C Lua  1 , David C Marciano  1 , Panagiotis Katsonis  1 , Anbu K Adikesavan  1 , Angela D Wilkins  2 , Olivier Lichtarge  3
Affiliations
Review

Prediction and redesign of protein-protein interactions

Rhonald C Lua et al. Prog Biophys Mol Biol. 2014 Nov-Dec.

Abstract

Understanding the molecular basis of protein function remains a central goal of biology, with the hope to elucidate the role of human genes in health and in disease, and to rationally design therapies through targeted molecular perturbations. We review here some of the computational techniques and resources available for characterizing a critical aspect of protein function - those mediated by protein-protein interactions (PPI). We describe several applications and recent successes of the Evolutionary Trace (ET) in identifying molecular events and shapes that underlie protein function and specificity in both eukaryotes and prokaryotes. ET is a part of analytical approaches based on the successes and failures of evolution that enable the rational control of PPI.

Keywords: Evolutionary trace; Functional annotation; Functional sites; Molecular evolution; Protein design; Protein–protein interaction networks.

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Figures

Fig. 1
Fig. 1
Computational characterization of PPI that also serves as an outline for much of this article. A. Databases of PPI networks allow us to answer the question “Which proteins interact?” directly or functionally. B. Computational predictions of interacting/binding sites on one protein surface from sequence analysis using ET (yellow circles) can complement experimental data such as alanine scanning mutagenesis. C. Coevolution from simultaneous analysis of two protein partners known to directly interact can complement biochemical and cross-linking data. Dashed lines indicate coevolving or significantly correlated residues. D. Prediction of PPI interfaces by docking. E. Knowledge of the protein–protein complex enables refinement of computational predictions of key residues (red circles). F. Design of peptide to mimic and inhibit native interaction. Key binding and specificity determinants (yellow circles) are built into a scaffold that enhances other desirable features such as solubility or helical propensity. Note that characterization of PPI is not necessarily followed in the sequential order A–F.
Fig. 2
Fig. 2
ET-guided mutagenesis leads to a protein–protein interaction model. A. The helical oligomerization of RecA (alternating green and yellow monomers) around DNA. The positions of RecA mutations that alter LexA cleavage (Adikesavan et al., 2011; McGrew and Knight, 2003) are colored in magenta. B. ET shows the RecA phylogenetic variation pattern as a color spectrum ranging from violet (most variation) to red (least variation). C. Overlapping docking solutions for the LexA–RecA interaction are shown for a LexA C-terminal dimer (dark blue (Adikesavan et al., 2011)) and a LexA monomer (light blue (Kovacic et al., 2013)). The positions used to guide docking in Adikesavan et al. (G22 & G108) are shown in red.
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