Are Protein Folding Intermediates the Evolutionary Consequence of Functional Constraints?

Abstract

High-resolution experiments on several apparently two-state proteins point to the existence of partially structured excited- or intermediate-states in dynamic equilibrium with native states. Are these intermediate states the byproducts of functional constraints that are by necessity evolutionarily conserved or are they merely the hidden imprints of evolutionary processes? To investigate this, we characterize the folding of Barstar that has a rich history of complex conformational behavior employing a combination of methods-statistical-mechanical model, electrostatic calculations, MD simulations and multiple-sequence alignment-that provide a detailed yet consistent view of its landscape in agreement with experiments. We find that the multistate folding in Barstar is the direct consequence of a strong evolutionary pressure to maintain its binding affinity with Barnase through a large negative electrostatic potential on one face. A single mutation (E76K or E80K) at the binding site is shown to not only enhance the native-state stability but also alter the Barstar folding mechanism to resemble an unfrustrated two-state-like system. Our results argue that though natural proteins are expected to be minimally frustrated, functional constraints can singularly determine the folding mechanism even if it occurs at the expense of frustrated multistate folding.

Alterations of Nonconserved Residues Affect Protein Stability and Folding Dynamics through Charge–Charge Interactions

“…Interestingly, we further observed that optimization of the surface charges of TNfn3 significantly reduces the energetic frustration in the MUT TNfn3 compared to the WT. This reduction of energetic frustration upon optimization of charge− charge interactions was previously demonstrated by us using C α -structure-based model 30 and is also in agreement with recent computer simulations of Naganathan et al 31 We also explored the interrelationship between charge− charge interactions and folding mechanism from the correlated fluctuations of the C α atoms at different states for all the three systems of TNfn3. The correlation map captures both the native and non-native interactions from local fluctuations of C α positions of each residue.…”

Modulation of allosteric coupling by mutations: from protein dynamics and packing to altered native ensembles and function

“…Surface mutations also contribute to complex alteration of folded and unfolded ensembles apart from folding mechanisms [83–86]. It is therefore possible that even apparently neutral mutations modulate specific features of the native conformational ensemble which is however invisible or challenging to identify in the absence of a functional output.…”

Thermodynamics and folding landscapes of large proteins from a statistical mechanical model

“…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 ).

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