On the Role of Electrostatic Interactions in the Design of Protein–Protein Interfaces

Sheinerman, Felix B.; Honig, Barry

doi:10.1016/s0022-2836(02)00030-x

Cited by 234 publications

(252 citation statements)

References 47 publications

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“…Given the simplicity of the complementarity rules used here, there is probably room for improving the description of the complementarity classes. For instance, the charged-residues complementarity class restricts to short-range interactions that are only a fraction of the global electrostatic contribution to the binding selectivity and affinity (7,39,40). More sophisticated treatment of the electrostatic contribution in the light of the evolutionary principles used in SCOTCH may therefore improve further the performance of the method (41).…”

Section: Discussionmentioning

confidence: 99%

Coevolution at protein complex interfaces can be detected by the complementarity trace with important impact for predictive docking

Madaoui

Guérois

2008

Proc. Natl. Acad. Sci. U.S.A.

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Protein surfaces are under significant selection pressure to maintain interactions with their partners throughout evolution. Capturing how selection pressure acts at the interfaces of proteinprotein complexes is a fundamental issue with high interest for the structural prediction of macromolecular assemblies. We tackled this issue under the assumption that, throughout evolution, mutations should minimally disrupt the physicochemical compatibility between specific clusters of interacting residues. This constraint drove the development of the so-called Surface COmplementarity Trace in Complex History score (SCOTCH), which was found to discriminate with high efficiency the structure of biological complexes. SCOTCH performances were assessed not only with respect to other evolution-based approaches, such as conservation and coevolution analyses, but also with respect to statistically based scoring methods. Validated on a set of 129 complexes of known structure exhibiting both permanent and transient intermolecular interactions, SCOTCH appears as a robust strategy to guide the prediction of protein-protein complex structures. Of particular interest, it also provides a basic framework to efficiently track how protein surfaces could evolve while keeping their partners in contact.evolution ͉ prediction ͉ protein-protein interaction T he modular assembly of proteins is a key determinant in the regulation of biological systems. Combinations of inter-and intramolecular interactions hold the cell machineries and govern the flow of information transmitted through cell signaling pathways. To unravel the complexity of cell organization, atlases of the physical interactome have been obtained for several model organisms (1, 2). To further elucidate the competitions and synergies ruling the molecular logic of these protein-protein interaction networks, a critical step relies on the structural characterization of the protein complexes. However, there is still a huge gap between the proteome-wide data accumulating and the available structural details of macromolecular complexes.A number of studies have tackled the large-scale analysis of protein-protein complexes from a structural perspective (3-7). They have emphasized that size, shape, and the physicochemical complementarities at the interfaces are key descriptors that could be used to develop computational methods able to predict protein-binding sites from sequences or structures (8)(9)(10)(11)(12)(13)(14). In the context of evolution, seminal studies compared the binding modes of domain-domain interactions between homologous proteins and concluded that they tend to interact similarly, even if sequence identity has been maintained as low as 30% (15, 16). Such a low conservation threshold suggests that interaction surfaces can evolve significantly while maintaining sufficient specificity between the binding partners. The paradox between sequence divergence and structural conservation of macromolecular assemblies has been recently related to the notion of superfamily, and the exis...

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Section: Discussionmentioning

confidence: 99%

Coevolution at protein complex interfaces can be detected by the complementarity trace with important impact for predictive docking

Madaoui

Guérois

2008

Proc. Natl. Acad. Sci. U.S.A.

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“…Desolvation and electrostatic interaction energies for Arg65 and Lys66 of HLA-A2 were performed using finite-difference Poisson-Boltzmann methods as previously described (32), with minor modifications as listed below. Methods of computing energies followed those of Sheinerman and Honig (43). Briefly, TCR structures were imported into Accelrys Discovery Studio.…”

Section: Methodsmentioning

confidence: 99%

“…We computed this desolvation penalty for Arg65 and Lys66 in each TCR interface with A2, using a continuum electrostatics approach that yields the desolvation and coulombic energies associated with charge burial (27,43). We used this approach previously in studying TCR recognition of pMHC, validating it with mutational and binding studies (32).…”

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confidence: 99%

How structural adaptability exists alongside HLA-A2 bias in the human αβ TCR repertoire

Blevins

Pierce

Singh

et al. 2016

Proc. Natl. Acad. Sci. U.S.A.

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How T-cell receptors (TCRs) can be intrinsically biased toward MHC proteins while simultaneously display the structural adaptability required to engage diverse ligands remains a controversial puzzle. We addressed this by examining αβ TCR sequences and structures for evidence of physicochemical compatibility with MHC proteins. We found that human TCRs are enriched in the capacity to engage a polymorphic, positively charged "hot-spot" region that is almost exclusive to the α1-helix of the common human class I MHC protein, HLA-A*0201 (HLA-A2). TCR binding necessitates hot-spot burial, yielding high energetic penalties that must be offset via complementary electrostatic interactions. Enrichment of negative charges in TCR binding loops, particularly the germ-line loops encoded by the TCR Vα and Vβ genes, provides this capacity and is correlated with restricted positioning of TCRs over HLA-A2. Notably, this enrichment is absent from antibody genes. The data suggest a built-in TCR compatibility with HLA-A2 that biases receptors toward, but does not compel, particular binding modes. Our findings provide an instructional example for how structurally pliant MHC biases can be encoded within TCRs.T-cell receptor | peptide/MHC | structure | binding | MHC bias

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“…This loss of water, or desolvation, is generally energetically unfavorable and offsets the favorable interactions formed upon binding. The binding affinities, from an electrostatic point of view, are determined by balance of these two energetic contributions (Xu et al, 1997;Lee and Tidor, 2001;Sheinerman and Honig, 2002;Russell et al, 2004;del Álamo and Mateu, 2005). Systematic studies of protein pairs, such as barnase and barstar Fersht, 1993, 1995;Frisch et al, 1997;Dong et al, 2003), and fasciculin-2 (Radic et al, 1997), as well as protein kinase A and balanol (Wong et al, 2001), have shown that charged and polar residues at the protein-protein interfaces play important roles in binding energetics.…”

Section: Iib Biomolecule-ligand and -Biomolecule Interactionsmentioning

confidence: 99%

“…As specific examples, binding free energy calculations have been performed to investigate the roles of charged residues at the interface of the barnase (and extracellular ribonuclease) and barstar (a protein inhibitor), which have been a popular test case for both computational (Gabdoulline and Wade, 1997, 1998Lee and Tidor, 2001;Sheinerman and Honig, 2002;Dong et al, 2003;Wang and Wade, 2003;Spaar and Helms, 2005;Spaar et al, 2006) and experimental studies of protein-protein interactions Fersht, 1993, 1995;Frisch et al, 1997). In particular, PB calculations successfully reproduced the experimental result Fersht, 1993, 1995;Frisch et al, 1997) that crossinterface salt-bridges and hydrogen bonds dominate the binding affinities of barnase and barstar .…”

Section: Ivd Binding Free Energiesmentioning

confidence: 99%

Computational Methods for Biomolecular Electrostatics

Dong

Olsen

Baker

2008

Methods in Cell Biology

116

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An understanding of intermolecular interactions is essential for insight into how cells develop, operate, communicate and control their activities. Such interactions include several components: contributions from linear, angular, and torsional forces in covalent bonds, van der Waals forces, as well as electrostatics. Among the various components of molecular interactions, electrostatics are of special importance because of their long range and their influence on polar or charged molecules, including water, aqueous ions, and amino or nucleic acids, which are some of the primary components of living systems. Electrostatics, therefore, play important roles in determining the structure, motion and function of a wide range of biological molecules. This chapter presents a brief overview of electrostatic interactions in cellular systems with a particular focus on how computational tools can be used to investigate these types of interactions.

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On the Role of Electrostatic Interactions in the Design of Protein–Protein Interfaces

Cited by 234 publications

References 47 publications

Coevolution at protein complex interfaces can be detected by the complementarity trace with important impact for predictive docking

Coevolution at protein complex interfaces can be detected by the complementarity trace with important impact for predictive docking

How structural adaptability exists alongside HLA-A2 bias in the human αβ TCR repertoire

Computational Methods for Biomolecular Electrostatics

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