Protein Sectors: Statistical Coupling Analysis versus Conservation

Teşileanu, Tiberiu; Colwell, Lucy; Leibler, Stanislas

doi:10.1371/journal.pcbi.1004091

Cited by 83 publications

(100 citation statements)

References 37 publications

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“…Another route, statistical coupling analysis (12), considers correlations within sequences of proteins of the same family to infer allosteric pathways (4,7). The generality of this elegant approach is, however, debated (13).…”

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confidence: 99%

Architecture and coevolution of allosteric materials

Yan

Ravasio

Brito

et al. 2017

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

120

138

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We introduce a numerical scheme to evolve functional elastic materials that can accomplish a specified mechanical task. In this scheme, the number of solutions, their spatial architectures, and the correlations among them can be computed. As an example, we consider an "allosteric" task, which requires the material to respond specifically to a stimulus at a distant active site. We find that functioning materials evolve a less-constrained trumpetshaped region connecting the stimulus and active sites, and that the amplitude of the elastic response varies nonmonotonically along the trumpet. As previously shown for some proteins, we find that correlations appearing during evolution alone are sufficient to identify key aspects of this design. Finally, we show that the success of this architecture stems from the emergence of soft edge modes recently found to appear near the surface of marginally connected materials. Overall, our in silico evolution experiment offers a window to study the relationship between structure, function, and correlations emerging during evolution. disordered materials | proteins | evolution P roteins are long polymers that can fold in a reproducible way and achieve a specific function. Often, the activity of the main functional site depends on the binding of an effector on a distant site (1, 2). Such an allosteric behavior can occur over large distances, such as 20 residues or more (3), and often involves only a sparse subset of residues in the protein (3, 4). Allosteric regulation offers an appealing target for drug design (5), and there is considerable interest in predicting allosteric pathways (6, 7). One central difficulty is that the physical mechanisms allowing such an "action at a distance" remain elusive. In some cases, allostery can be understood as the modulation of a hinge connecting two extended rigid parts of the protein (8, 9), but, often, the displacement field induced by the binding of the effector cannot be described in these terms (4, 10, 11). Another route, statistical coupling analysis (12), considers correlations within sequences of proteins of the same family to infer allosteric pathways (4, 7). The generality of this elegant approach is, however, debated (13).From a physical viewpoint, specific response at a distance is surprising. The structure of proteins is similar to randomly packed spheres (14). Generically, the response of such systems is nonspecific and decays rapidly in space (in a manner similar to a continuum medium) at distances larger than the particle size; this is true, except close to a critical point where the number of constraints coming from strongly interacting particles is just sufficient to match the number of degrees of freedom of the particles (15). There, the elastic response becomes heterogeneous on all scales (16,17). This point is illustrated in Fig. 1A, showing the rapidly decaying response of a random spring network to a stimulus. However, as shown in Fig. 1B (and independently found in ref. 18 using a different algorithm), springs can be move...

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mentioning

confidence: 99%

Architecture and coevolution of allosteric materials

Yan

Ravasio

Brito

et al. 2017

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

120

138

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“…Nonproximal thermodynamic coupling between correlated residue pairs was noted in 274 PDZ domains (14), but the relationship to allostery is still debated (19,20). It may be that distinctive allosteric mechanisms, even among close homologs, limit the extraction of allosteric couplings from sequences (13).…”

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confidence: 99%

Intramolecular allosteric communication in dopamine D2 receptor revealed by evolutionary amino acid covariation

Sung

Wilkins

Rodríguez

et al. 2016

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

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The structural basis of allosteric signaling in G protein-coupled receptors (GPCRs) is important in guiding design of therapeutics and understanding phenotypic consequences of genetic variation. The Evolutionary Trace (ET) algorithm previously proved effective in redesigning receptors to mimic the ligand specificities of functionally distinct homologs. We now expand ET to consider mutual information, with validation in GPCR structure and dopamine D2 receptor (D2R) function. The new algorithm, called ET-MIp, identifies evolutionarily relevant patterns of amino acid covariations. The improved predictions of structural proximity and D2R mutagenesis demonstrate that ET-MIp predicts functional interactions between residue pairs, particularly potency and efficacy of activation by dopamine. Remarkably, although most of the residue pairs chosen for mutagenesis are neither in the binding pocket nor in contact with each other, many exhibited functional interactions, implying at-a-distance coupling. The functional interaction between the coupled pairs correlated best with the evolutionary coupling potential derived from dopamine receptor sequences rather than with broader sets of GPCR sequences. These data suggest that the allosteric communication responsible for dopamine responses is resolved by ET-MIp and best discerned within a short evolutionary distance. Most double mutants restored dopamine response to wild-type levels, also suggesting that tight regulation of the response to dopamine drove the coevolution and intramolecular communications between coupled residues. Our approach provides a general tool to identify evolutionary covariation patterns in small sets of close sequence homologs and to translate them into functional linkages between residues.allostery | G protein-coupled receptors | residue covariation | Evolutionary Trace I dentifying residues that coevolved to maintain or acquire fitness properties is critical for understanding protein structure, function, and evolution (1). Previous studies have shown that covarying residue pairs, those that exhibit correlated amino acid changes in large multiple sequence alignments, tend to form structural contacts (2-7), enhancing predictions of protein 3D structures (8-11). Covariation can also involve distal residues, but the function of these at-a-distance couplings is elusive and has been attributed to background noise, alternative protein conformations, or subunit interactions of protein homooligomers (5,7,12). Alternately, distal covarying residue pairs could indicate allosteric couplings (6,(13)(14)(15)(16)(17)(18).The possibility of capturing intramolecular allosteric communication by amino acid covariation analysis of protein family sequences has not been extensively explored. Nonproximal thermodynamic coupling between correlated residue pairs was noted in 274 PDZ domains (14), but the relationship to allostery is still debated (19,20). It may be that distinctive allosteric mechanisms, even among close homologs, limit the extraction of allosteric couplings from ...

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“…The sodium allosteric site, the allosteric pocket, only accommodates small molecules, such as amiloride, due to its limited size (53). Although this allosteric site for sodium seems conserved, the allostery of sodium or amiloride is only found in few receptors (55), indicating that this allosteric site may result in high selectivity of related ligands. All three allosteric sites can be used to construct allosteric pharmacophores for bitopic ligands with the fragment-based method, which is to apply orthosteric features and the allosteric pharmacophore separately, as shown in Fig.…”

Section: Bitopic Ligandsmentioning

confidence: 99%

Computational Advances for the Development of Allosteric Modulators and Bitopic Ligands in G Protein-Coupled Receptors

Feng

et al. 2015

AAPS J

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Abstract. Allosteric modulators of G protein-coupled receptors (GPCRs), which target at allosteric sites, have significant advantages against the corresponding orthosteric compounds including higher selectivity, improved chemical tractability or physicochemical properties, and reduced risk of receptor oversensitization. Bitopic ligands of GPCRs target both orthosteric and allosteric sites. Bitopic ligands can improve binding affinity, enhance subtype selectivity, stabilize receptors, and reduce side effects. Discovering allosteric modulators or bitopic ligands for GPCRs has become an emerging research area, in which the design of allosteric modulators is a key step in the detection of bitopic ligands. Radioligand binding and functional assays ([ 35 S]GTPγS and ERK1/2 phosphorylation) are used to test the effects for potential modulators or bitopic ligands. High-throughput screening (HTS) in combination with disulfide trapping and fragment-based screening are used to aid the discovery of the allosteric modulators or bitopic ligands of GPCRs. When used alone, these methods are costly and can often result in too many potential drug targets, including false positives. Alternatively, low-cost and efficient computational approaches are useful in drug discovery of novel allosteric modulators and bitopic ligands to help refine the number of targets and reduce the false-positive rates. This review summarizes the state-of-the-art computational methods for the discovery of modulators and bitopic ligands. The challenges and opportunities for future drug discovery are also discussed.

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Protein Sectors: Statistical Coupling Analysis versus Conservation

Cited by 83 publications

References 37 publications

Architecture and coevolution of allosteric materials

Architecture and coevolution of allosteric materials

Intramolecular allosteric communication in dopamine D2 receptor revealed by evolutionary amino acid covariation

Computational Advances for the Development of Allosteric Modulators and Bitopic Ligands in G Protein-Coupled Receptors

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