All-Atom Monte Carlo Approach to Protein–Peptide Binding

Staneva, Iskra; Wallin, Stefan

doi:10.1016/j.jmb.2009.08.063

Cited by 20 publications

(31 citation statements)

References 44 publications

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“…The charge-charge interactions involving upstream residues Asp(-4) and Arg(-6) in the crystal structure vanished during the simulation and the N-terminal tail of the peptide was frequently sampling diverse conformations. Structure diversity of the peptide bound to PDZ domain was also found in previous Monte Carlo simulations [36]. The peptide conformation in the crystal structure of ZO-1 PDZ2/Cx43 coincides with the structures in the second cluster of our MD simulations.…”

Section: Discussionsupporting

confidence: 87%

Detailed Regulatory Mechanism of the Interaction between ZO-1 PDZ2 and Connexin43 Revealed by MD Simulations

et al. 2011

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The gap junction protein connexin43 (Cx43) binds to the second PDZ domain of Zonula occludens-1 (ZO-1) through its C-terminal tail, mediating the regulation of gap junction plaque size and dynamics. Biochemical study demonstrated that the very C-terminal 12 residues of Cx43 are necessary and sufficient for ZO-1 PDZ2 binding and phosphorylation at residues Ser (-9) and Ser (-10) of the peptide can disrupt the association. However, only a crystal structure of ZO-1 PDZ2 in complex with a shorter 9 aa peptide of connexin43 was solved experimentally. Here, the interactions between ZO-1 PDZ2 and the short, long and phosphorylated Cx43 peptides were studied using molecular dynamics (MD) simulations and free energy calculation. The short peptide bound to PDZ2 exhibits large structural variations, while the extension of three upstream residues stabilizes the peptide conformation and enhanced the interaction. Phosphorylation at Ser(-9) significantly weakens the binding and results in conformational flexibility of the peptide. Glu210 of ZO-1 PDZ2 was found to be a key regulatory point in Cx43 binding and phosphorylation induced dissociation.

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Section: Discussionsupporting

confidence: 87%

Detailed Regulatory Mechanism of the Interaction between ZO-1 PDZ2 and Connexin43 Revealed by MD Simulations

et al. 2011

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“…In other words, such an approach should predict both the peptide binding site (global search of the protein surface) and the bound peptide conformation to high precision simultaneously. A number of peptide-protein docking and binding site prediction tools have been developed to date (Antes, 2010;Bordner and Abagyan, 2006;Dagliyan et al, 2011;Donsky and Wolfson, 2011;Dundas et al, 2006;Heté nyi and van der Spoel, 2002;Lavi et al, 2013;Luitz and Zacharias, 2014;Niv and Weinstein, 2005;Petsalaki et al, 2009;Raveh et al, 2011;Rosenfeld et al, 1995;Saladin et al, 2014;Staneva and Wallin, 2009;Trabuco et al, 2012;Unal et al, 2010;Verschueren et al, 2013). Global docking and binding site prediction methods (Ben-Shimon and Eisenstein, 2010;Dagliyan et al, 2011;Dundas et al, 2006;Lavi et al, 2013;Petsalaki et al, 2009;Saladin et al, 2014;Trabuco et al, 2012;Verschueren et al, 2013) often identify the correct binding site but do not yield high-quality models for the peptide conformation (London et al, 2013b).…”

Section: Introductionmentioning

confidence: 99%

“…Local docking approaches can often yield high-quality models when tested on peptide-protein docking benchmarks (London et al, 2013b). Local methods include ligand docking based approaches (Tubert-Brohman et al, 2013) and several target-specific approaches (e.g., for MHC and PDZ domains) (Antes et al, 2006;Bordner and Abagyan, 2006;Niv and Weinstein, 2005;Rosenfeld et al, 1995;Staneva and Wallin, 2009). Several protocols are based on protein-protein docking, which is also reflected by the recent addition of peptide-protein targets to the community-wide docking challenge CAPRI (Lensink et al, 2007;Wodak, 2010b, 2013).…”

Section: Introductionmentioning

confidence: 99%

Fully Blind Peptide-Protein Docking with pepATTRACT

2015

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Peptide-protein interactions are ubiquitous in the cell and form an important part of the interactome. Computational docking methods can complement experimental characterization of these complexes, but current protocols are not applicable on the proteome scale. Here, we present a new fully blind flexible peptide-protein docking protocol, pepATTRACT, which combines a rapid coarse-grained global peptide docking search of the entire protein surface with a two-stage atomistic flexible refinement. Global unbound-unbound docking yielded near-native models for 70% of the docking cases when testing the protocol on the largest benchmark of peptide-protein complexes available to date. This performance is similar to that of state-of-the-art local docking protocols that rely on information about the binding site. Upon restricting the search to the peptide binding region, the resulting pepATTRACT-local approach outperformed existing methods. Docking scripts for pepATTRACT and pepATTRACT-local can be generated via a web interface at www.attract.ph.tum.de/peptide.html.

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“…It is therefore of importance to understand the detailed molecular underpinnings of protein-peptide recognition. To this end, simulation methods at the atomic level have recently been employed, including different variants of docking [23]–[29], implicit- and explicit-water molecular dynamics [30]–[34], and Monte Carlo-based approaches [35]–[37].…”

Section: Introductionmentioning

confidence: 99%

Exploring Protein-Peptide Binding Specificity through Computational Peptide Screening

Bhattacherjee

Wallin

2013

PLoS Comput Biol

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The binding of short disordered peptide stretches to globular protein domains is important for a wide range of cellular processes, including signal transduction, protein transport, and immune response. The often promiscuous nature of these interactions and the conformational flexibility of the peptide chain, sometimes even when bound, make the binding specificity of this type of protein interaction a challenge to understand. Here we develop and test a Monte Carlo-based procedure for calculating protein-peptide binding thermodynamics for many sequences in a single run. The method explores both peptide sequence and conformational space simultaneously by simulating a joint probability distribution which, in particular, makes searching through peptide sequence space computationally efficient. To test our method, we apply it to 3 different peptide-binding protein domains and test its ability to capture the experimentally determined specificity profiles. Insight into the molecular underpinnings of the observed specificities is obtained by analyzing the peptide conformational ensembles of a large number of binding-competent sequences. We also explore the possibility of using our method to discover new peptide-binding pockets on protein structures.

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All-Atom Monte Carlo Approach to Protein–Peptide Binding

Cited by 20 publications

References 44 publications

Detailed Regulatory Mechanism of the Interaction between ZO-1 PDZ2 and Connexin43 Revealed by MD Simulations

Detailed Regulatory Mechanism of the Interaction between ZO-1 PDZ2 and Connexin43 Revealed by MD Simulations

Fully Blind Peptide-Protein Docking with pepATTRACT

Exploring Protein-Peptide Binding Specificity through Computational Peptide Screening

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