Dynamical networks in tRNA:protein complexes

Sethi, Anurag; Eargle, John M.; Black, Alexis A.; Luthey‐Schulten, Zaida

doi:10.1073/pnas.0810961106

Cited by 738 publications

(1,133 citation statements)

References 30 publications

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“…Global reorientation and intradomain configurational dynamics of TM4 are strongly coupled to both the global and intradomain dynamics of TM5. The importance of several of the most highly cross-correlated TM residues in these regions was previously characterized in an NMR study, which found that backbone dynamics of Tyr358 and Gln359 are correlated with anticoagulant activity and that backbone dynamics of Tyr413 and Ile414 are inversely correlated with thrombin binding (24). This tight coupling between TM4 and TM5 was previously shown experimentally to depend on M388 in the TM4-TM5 linker (25,26).…”

Section: Discussionmentioning

confidence: 84%

“…Allosteric networks were characterized using a community network analysis approach previously applied to investigate allostery in tRNA-protein complexes and other protein systems (24,31,32). This approach constructs a dynamic contact map consisting of a network graph in which each residue is treated as a "node" connected by edges to other nodes when two residues are deemed to be "in contact."…”

Section: Methodsmentioning

confidence: 99%

“…AMD has already been used with great success to study the dynamics and conformational behavior of a variety of biomolecular systems, including polypeptides and both natively unstructured and folded proteins (23). Community network models (24) have been used to identify potential allosteric pathways. This information is supplemented by both a generalized correlated motion analysis (25) and the calculation of backbone amino-nitrogen-amino-proton, NH N order parameters to compare the dynamic behavior of thrombin in the three different systems across a variety of time scales.…”

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confidence: 99%

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Allosteric networks in thrombin distinguish procoagulant vs. anticoagulant activities

Gasper¹,

Fuglestad²,

Komives³

et al. 2012

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

145

169

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The serine protease α-thrombin is a dual-action protein that mediates the blood-clotting cascade. Thrombin alone is a procoagulant, cleaving fibrinogen to make the fibrin clot, but the thrombinthrombomodulin (TM) complex initiates the anticoagulant pathway by cleaving protein C. A TM fragment consisting of only the fifth and sixth EGF-like domains (TM56) is sufficient to bind thrombin, but the presence of the fourth EGF-like domain (TM456) is critical to induce the anticoagulant activity of thrombin. Crystallography of the thrombin-TM456 complex revealed no significant structural changes in thrombin, suggesting that TM4 may only provide a scaffold for optimal alignment of protein C for its cleavage by thrombin. However, a variety of experimental data have suggested that the presence of TM4 may affect the dynamic properties of the active site loops. In the present work, we have used both conventional and accelerated molecular dynamics simulation to study the structural dynamic properties of thrombin, thrombin: TM56, and thrombin:TM456 across a broad range of time scales.Two distinct yet interrelated allosteric pathways are identified that mediate both the pro-and anticoagulant activities of thrombin. One allosteric pathway, which is present in both thrombin: TM56 and thrombin:TM456, directly links the TM5 domain to the thrombin active site. The other allosteric pathway, which is only present on slow time scales in the presence of the TM4 domain, involves an extended network of correlated motions linking the TM4 and TM5 domains and the active site loops of thrombin.allostery | thrombosis

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Section: Discussionmentioning

confidence: 84%

Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Allosteric networks in thrombin distinguish procoagulant vs. anticoagulant activities

Gasper¹,

Fuglestad²,

Komives³

et al. 2012

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

145

169

View full text Add to dashboard Cite

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“…Community analysis can also be applied to correlated motions in proteins and nucleic acids (18,19). In such studies, MD simulations are performed and correlations among residues are evaluated.…”

mentioning

confidence: 99%

“…Community analysis of such correlation networks identifies relatively independent communities of residues that behave as semirigid bodies. Initial applications of this method to study protein dynamics provided insight into the propagation of allosteric signals in bacterial tRNA-synthetases (18) and in a sortase enzyme from Staphylococcus aureus (19).…”

mentioning

confidence: 99%

Dynamic architecture of a protein kinase

McClendon

Kornev

Gilson

et al. 2014

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

234

273

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To better understand the mechanism of long distance allosteric signaling inside the protein kinase core using protein kinase A (PKA) as a prototype, we obtained 5μs molecular dynamics trajectories in different liganded and conformational states using the Anton supercomputer, providing for the first time an opportunity to observe intermediate‐timescale conformational transitions in the study of the dynamics of this stable kinase. We used community analysis to identify structurally‐contiguous groups of residues exhibiting correlated motions in the kinase catalytic domain. This dynamic partitioning of the kinase into communities provides a framework for analyzing the local vs. long‐range effects of mutations, binding, phosphorylation, etc. We hypothesize that perturbations will be readily felt within these communities and then propagated possibly to a lesser extent to other elements through correlated motions. Moreover, using a wealth of published mutational data, we can annotate these communities with functions. Our functional annotation of kinase communities provides an extremely valuable framework for viewing a signaling enzyme in terms of functional substructures rather than isolated linear motifs such as secondary structure elements and short three or four residue motifs. Figure 1. Functional annotation of the kinase communitiy map. Each community is shown in red on the structure of PKA. Grant Funding Source: Supported by NIH F32 GM099197, R01 GM19301

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Methods Applied for the Allosteric Site Revelation

Zhang

2018

Encyclopedia of Analytical Chemistry

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Allostery is the functional change at one site on a protein due to alterations at a distant site. Allosteric modulators by targeting allosteric site can fine‐tune protein's activity. Drugging allosteric sites has therefore been regarded as a novel direction in drug discovery. However, identification of allosteric sites by experimental approaches is serendipitous. Since bioinformatics and structural biology develop rapidly, protein dynamics and structures can be better understood and allosteric drug discovery is on the cusp of a novel era of rational computational methodologies. Various computational allosteric site prediction models have therefore been put forward. Computational prediction is helpful for exploration of potential allosteric sites due to its higher accuracy and relatively shorter timescale. Here, we review the state‐of‐the‐art computational allosteric sites prediction methods. We first classify different approaches according to their underlying theoretical models, then algorithms and fundamental theories behind them are revealed, and finally successful examples are presented. We put forward the current challenges faced by these approaches. Possible solutions are provided with the latest advances in the field of computational biology, and tactics to resolve these demanding tasks are also discussed.

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Dynamical networks in tRNA:protein complexes

Cited by 738 publications

References 30 publications

Allosteric networks in thrombin distinguish procoagulant vs. anticoagulant activities

Allosteric networks in thrombin distinguish procoagulant vs. anticoagulant activities

Dynamic architecture of a protein kinase

Methods Applied for the Allosteric Site Revelation

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