Abstract:We show that the phosphorylation of 4E-BP2 acts as a triggering event to shape its folding-function landscape that is delicately balanced between conflicting favorable energetics and intrinsically unfavorable topological connectivity. We further provide first evidence that the fitness landscapes of proteins at the threshold of disorder can differ considerably from ordered domains.
“…It should also be possible to capture the effect of DNA, RNA or even ligand binding on the conformational landscapes of larger proteins by extending a recently developed protocol that maps the protein-ligand interactions on to the protein ( Munshi et al., 2018b ). Similarly, post-translational modifications, particularly those that introduce or remove charges can be introduced in a straightforward manner as before ( Gopi et al., 2015 ). The bWSME model thus stands on the cusp of addressing and exploring numerous questions on the conformational behavior of large proteins.…”
Section: Discussionmentioning
confidence: 99%
“…The Wako-Saitô-Muñoz-Eaton (WSME) model is one such statistical mechanical model that was first developed by Wako and Saitô ( Wako and Saito, 1978a , Wako and Saito, 1978b ), discussed in detail by Gō and Abe ( Go and Abe, 1981 , Abe and Go, 1981 ), and then later independently developed by Muñoz and Eaton (1999) . Originally seen as a physical tool to predict the folding rates of proteins from three-dimensional structures ( Muñoz and Eaton, 1999 , Henry and Eaton, 2004 ), the model has expanded its scope to quantitatively analyze folding behaviors of folded globular domains ( Bruscolini and Naganathan, 2011 , Garcia-Mira et al., 2002 , Narayan and Naganathan, 2014 , Narayan and Naganathan, 2017 , Narayan and Naganathan, 2018 , Naganathan and Muñoz, 2014 , Naganathan et al., 2015 , Munshi and Naganathan, 2015 , Rajasekaran et al., 2016 , Narayan et al., 2017 , Itoh and Sasai, 2006 ), repeat proteins ( Faccin et al., 2011 , Sivanandan and Naganathan, 2013 , Hutton et al., 2015 ), disordered proteins (with appropriate controls) ( Naganathan and Orozco, 2013 , Gopi et al., 2015 , Munshi et al., 2018a ), predict and engineer thermodynamic stabilities of proteins via mutations ( Naganathan, 2012 , Naganathan, 2013b , Rajasekaran et al., 2017 ) and entropic effects ( Rajasekaran et al., 2016 ), model allosteric transitions ( Itoh and Sasai, 2011 , Sasai et al., 2016 ), protein-DNA binding ( Munshi et al., 2018b ), quantifying folding pathways at different levels of resolution ( Henry et al., 2013 , Kubelka et al., 2008 , Gopi et al., 2017 ), force-spectroscopic measurements ( Imparato et al., 2007 ) and even crowding effects ( Caraglio and Pelizzola, 2012 ). …”
Statistical mechanical models that afford an intermediate resolution between macroscopic chemical models and all-atom simulations have been successful in capturing folding behaviors of many small single-domain proteins. However, the applicability of one such successful approach, the Wako-Saitô-Muñoz-Eaton (WSME) model, is limited by the size of the protein as the number of conformations grows exponentially with protein length. In this work, we surmount this size limitation by introducing a novel approximation that treats stretches of 3 or 4 residues as blocks, thus reducing the phase space by nearly three orders of magnitude. The performance of the ‘bWSME’ model is validated by comparing the predictions for a globular enzyme (RNase H) and a repeat protein (IκBα), against experimental observables and the model without block approximation. Finally, as a proof of concept, we predict the free-energy surface of the 370-residue, multi-domain maltose binding protein and identify an intermediate in good agreement with single-molecule force-spectroscopy measurements. The bWSME model can thus be employed as a quantitative predictive tool to explore the conformational landscapes of large proteins, extract the structural features of putative intermediates, identify parallel folding paths, and thus aid in the interpretation of both ensemble and single-molecule experiments.
“…It should also be possible to capture the effect of DNA, RNA or even ligand binding on the conformational landscapes of larger proteins by extending a recently developed protocol that maps the protein-ligand interactions on to the protein ( Munshi et al., 2018b ). Similarly, post-translational modifications, particularly those that introduce or remove charges can be introduced in a straightforward manner as before ( Gopi et al., 2015 ). The bWSME model thus stands on the cusp of addressing and exploring numerous questions on the conformational behavior of large proteins.…”
Section: Discussionmentioning
confidence: 99%
“…The Wako-Saitô-Muñoz-Eaton (WSME) model is one such statistical mechanical model that was first developed by Wako and Saitô ( Wako and Saito, 1978a , Wako and Saito, 1978b ), discussed in detail by Gō and Abe ( Go and Abe, 1981 , Abe and Go, 1981 ), and then later independently developed by Muñoz and Eaton (1999) . Originally seen as a physical tool to predict the folding rates of proteins from three-dimensional structures ( Muñoz and Eaton, 1999 , Henry and Eaton, 2004 ), the model has expanded its scope to quantitatively analyze folding behaviors of folded globular domains ( Bruscolini and Naganathan, 2011 , Garcia-Mira et al., 2002 , Narayan and Naganathan, 2014 , Narayan and Naganathan, 2017 , Narayan and Naganathan, 2018 , Naganathan and Muñoz, 2014 , Naganathan et al., 2015 , Munshi and Naganathan, 2015 , Rajasekaran et al., 2016 , Narayan et al., 2017 , Itoh and Sasai, 2006 ), repeat proteins ( Faccin et al., 2011 , Sivanandan and Naganathan, 2013 , Hutton et al., 2015 ), disordered proteins (with appropriate controls) ( Naganathan and Orozco, 2013 , Gopi et al., 2015 , Munshi et al., 2018a ), predict and engineer thermodynamic stabilities of proteins via mutations ( Naganathan, 2012 , Naganathan, 2013b , Rajasekaran et al., 2017 ) and entropic effects ( Rajasekaran et al., 2016 ), model allosteric transitions ( Itoh and Sasai, 2011 , Sasai et al., 2016 ), protein-DNA binding ( Munshi et al., 2018b ), quantifying folding pathways at different levels of resolution ( Henry et al., 2013 , Kubelka et al., 2008 , Gopi et al., 2017 ), force-spectroscopic measurements ( Imparato et al., 2007 ) and even crowding effects ( Caraglio and Pelizzola, 2012 ). …”
Statistical mechanical models that afford an intermediate resolution between macroscopic chemical models and all-atom simulations have been successful in capturing folding behaviors of many small single-domain proteins. However, the applicability of one such successful approach, the Wako-Saitô-Muñoz-Eaton (WSME) model, is limited by the size of the protein as the number of conformations grows exponentially with protein length. In this work, we surmount this size limitation by introducing a novel approximation that treats stretches of 3 or 4 residues as blocks, thus reducing the phase space by nearly three orders of magnitude. The performance of the ‘bWSME’ model is validated by comparing the predictions for a globular enzyme (RNase H) and a repeat protein (IκBα), against experimental observables and the model without block approximation. Finally, as a proof of concept, we predict the free-energy surface of the 370-residue, multi-domain maltose binding protein and identify an intermediate in good agreement with single-molecule force-spectroscopy measurements. The bWSME model can thus be employed as a quantitative predictive tool to explore the conformational landscapes of large proteins, extract the structural features of putative intermediates, identify parallel folding paths, and thus aid in the interpretation of both ensemble and single-molecule experiments.
“…We also chose a state without any terminal helix and with both β1 and the long loop detached from the other three β-strands (3β) because it was frequently observed as a metastable intermediate during high-temperature unfolding and was also proposed as an important folding intermediate in a previous computational study. 29 Finally, we extracted a representative unfolded state (U) at 480 K. A clustering analysis based on the Cα RMSD of residues 37–46 was conducted for the trajectories after unfolding. From the most populated cluster, the structure with the lowest backbone RMSD to the folded state was extracted.…”
Section: Methodsmentioning
confidence: 99%
“…Several computational studies have been conducted to study the folding mechanism of this system and the origin of stabilization by phosphorylation. Gopi et al 29 studied different phosphorylated states using the statistical mechanical Wako–Saitô–Muñoz–Eaton (WSME) model. 30 , 31 They found that phosphorylation-induced stabilization in this system originated from strong electrostatic interactions between phosphate groups and nearby Arg residues, as generally observed in other systems.…”
Section: Introductionmentioning
confidence: 99%
“…For instance, phosphorylated Y54A/L59A [p(Y54A/L59A)], with two residues in the canonical binding motif (Y 54 xxxxL 59 Φ) substituted by alanine, cannot fold but retains the two β-turns. Another mutant, p(D33K), was predicted to have a more stable fold compared to the doubly phosphorylated wild-type (pWT) by Gopi et al 29 Neither of the two mutant stabilities can be understood from pWT’s experimental structure.…”
Upon phosphorylation of specific sites, eukaryotic translation
initiation factor 4E (eIF4E) binding protein 2 (4E-BP2) undergoes
a fundamental structural transformation from a disordered state to
a four-stranded β-sheet, leading to decreased binding affinity
for its partner. This change reflects the significant effects of phosphate
groups on the underlying energy landscapes of proteins. In this study,
we combine high-temperature molecular dynamics simulations and discrete
path sampling to construct energy landscapes for a doubly phosphorylated
4E-BP2
18–62
and two mutants (a single site mutant
D33K and a double mutant Y54A/L59A). The potential and free energy
landscapes for these three systems are multifunneled with the folded
state and several alternative states lying close in energy, suggesting
perhaps a multifunneled and multifunctional protein. Hydrogen bonds
between phosphate groups and other residues not only stabilize these
low-lying conformations to different extents but also play an important
role in interstate transitions. From the energy landscape perspective,
our results explain some interesting experimental observations, including
the low stability of doubly phosphorylated 4E-BP2 and its moderate
binding to eIF4E and the inability of phosphorylated Y54A/L59A to
fold.
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