Modeling Conformational Ensembles of Slow Functional Motions in Pin1-WW

Morcos, Faruck; Chatterjee, Santanu; McClendon, Christopher L.; Brenner, Paul; López-Rendón, Roberto; Zintsmaster, John S.; Ercsey-Ravasz, Mária; Sweet, Christopher; Jacobson, Matthew P.; Peng, Jeffrey W.; Izaguirre, Jesús A.

doi:10.1371/journal.pcbi.1001015

Cited by 85 publications

(75 citation statements)

References 53 publications

(72 reference statements)

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“…Protein sectors were identified using the statistical coupling analysis (SCA) approach, whereas a different approach, direct coupling analysis (DCA), yielded a partially different set of co-evolving residues (dashed lines). Residue pairs from DCA have successfully been used in combination with structure-based models to predict native structure, protein-protein interactions and conformational changes [28,29]. These examples illustrate how the fields of biophysics and molecular evolution can benefit from each other.…”

Section: Biophysical Consequences Of Protein Mutations 21 Mutationamentioning

confidence: 99%

Biophysics of protein evolution and evolutionary protein biophysics

Sikosek

Chan

2014

J. R. Soc. Interface.

220

207

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The study of molecular evolution at the level of protein-coding genes often entails comparing large datasets of sequences to infer their evolutionary relationships. Despite the importance of a protein's structure and conformational dynamics to its function and thus its fitness, common phylogenetic methods embody minimal biophysical knowledge of proteins. To underscore the biophysical constraints on natural selection, we survey effects of protein mutations, highlighting the physical basis for marginal stability of natural globular proteins and how requirement for kinetic stability and avoidance of misfolding and misinteractions might have affected protein evolution. The biophysical underpinnings of these effects have been addressed by models with an explicit coarse-grained spatial representation of the polypeptide chain. Sequence-structure mappings based on such models are powerful conceptual tools that rationalize mutational robustness, evolvability, epistasis, promiscuous function performed by 'hidden' conformational states, resolution of adaptive conflicts and conformational switches in the evolution from one protein fold to another. Recently, protein biophysics has been applied to derive more accurate evolutionary accounts of sequence data. Methods have also been developed to exploit sequence-based evolutionary information to predict biophysical behaviours of proteins. The success of these approaches demonstrates a deep synergy between the fields of protein biophysics and protein evolution.

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Section: Biophysical Consequences Of Protein Mutations 21 Mutationamentioning

confidence: 99%

Biophysics of protein evolution and evolutionary protein biophysics

Sikosek

Chan

2014

J. R. Soc. Interface.

220

207

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“…For our community analysis, we computed Cartesian mutual information values instead of dihedral mutual information values, as the former better capture correlated motions involving semirigid regions, such as secondary structure elements (93), whereas the latter are more suitable for analyzing couplings between surface sites where binding and posttranslational modification often occur (30,94). We calculated the Cartesian mutual information for backbone Cα atoms, as well as for a representative side-chain atom (SI Appendix, Table S2) of each residue.…”

Section: Methodsmentioning

confidence: 99%

Dynamic architecture of a protein kinase

McClendon

Kornev

Gilson

et al. 2014

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

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227

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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“…MSMs serve as maps of the free energy landscapes that ultimately control a protein's structure and dynamics (10,24). They have been successfully employed to understand processes like protein folding (25,26), ligand binding (27)(28)(29), and functional dynamics (30)(31)(32). One powerful feature of these models is that they can combine many simulations to capture processes occurring on much longer timescales than a single simulation could ever address.…”

Section: Resultsmentioning

confidence: 99%

Equilibrium fluctuations of a single folded protein reveal a multitude of potential cryptic allosteric sites

Bowman

Geissler²

2012

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

246

357

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Cryptic allosteric sites-transient pockets in a folded protein that are invisible to conventional experiments but can alter enzymatic activity via allosteric communication with the active site-are a promising opportunity for facilitating drug design by greatly expanding the repertoire of available drug targets. Unfortunately, identifying these sites is difficult, typically requiring resourceintensive screening of large libraries of small molecules. Here, we demonstrate that Markov state models built from extensive computer simulations (totaling hundreds of microseconds of dynamics) can identify prospective cryptic sites from the equilibrium fluctuations of three medically relevant proteins-β-lactamase, interleukin-2, and RNase H-even in the absence of any ligand. As in previous studies, our methods reveal a surprising variety of conformations-including bound-like configurations-that implies a role for conformational selection in ligand binding. Moreover, our analyses lead to a number of unique insights. First, direct comparison of simulations with and without the ligand reveals that there is still an important role for an induced fit during ligand binding to cryptic sites and suggests new conformations for docking. Second, correlations between amino acid sidechains can convey allosteric signals even in the absence of substantial backbone motions. Most importantly, our extensive sampling reveals a multitude of potential cryptic sites-consisting of transient pockets coupled to the active site-even in a single protein. Based on these observations, we propose that cryptic allosteric sites may be even more ubiquitous than previously thought and that our methods should be a valuable means of guiding the search for such sites. molecular dynamics | native state dynamics T he degree to which standard, rational drug design protocols ignore protein-conformational changes is a potentially major flaw. Most assume that proteins are frozen in their crystallographic structures because we do not understand the intrinsic dynamics of proteins well enough to include them. Once this assumption is made, the only way to manipulate a protein's activity is with inhibitors that bind more tightly to the protein's active site than the molecule's natural ligand. Unfortunately, only approximately 15% of proteins have a sufficiently deep pocket coinciding with their active site to make this strategy feasible (1).Accounting for conformational heterogeneity could greatly expand the repertoire of available drug targets by revealing cryptic sites-transient pockets that are not readily visible in experimental structures, yet can inhibit enzymatic activity via allostery or block protein-protein interactions (2-5). For example, they may provide previously undescribed druggable pockets on proteins that are already considered viable targets, or even make it possible to target proteins that are currently considered undruggable. Targeting these sites may be easier than targeting the active site if there is no natural ligand to outcompete. Finally, crypt...

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Modeling Conformational Ensembles of Slow Functional Motions in Pin1-WW

Cited by 85 publications

References 53 publications

Biophysics of protein evolution and evolutionary protein biophysics

Biophysics of protein evolution and evolutionary protein biophysics

Dynamic architecture of a protein kinase

Equilibrium fluctuations of a single folded protein reveal a multitude of potential cryptic allosteric sites

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