Energetic profiling of protein folds

Conserved allosteric ensembles in disordered proteins using TROSY/anti-TROSY R2-filtered spectroscopy

Defining the role of intrinsic disorder in proteins in the myriad of biological processes with which it is involved represents a significant goal in modern biophysics. Toward this end, NMR is uniquely suited for molecular studies of dynamic and disordered regions, but studying these regions in concert with their more structured domains and binding partners presents spectroscopic challenges. Here, we investigate the interactions between the structured and disordered regions of the human glucocorticoid receptor (GR). To do this, we developed an NMR strategy that relies on a novel relaxation filter for the simultaneous study of structured and unstructured regions. Using this approach, we conducted a comparative analysis of three translational isoforms of GR containing a folded DNA-binding domain (DBD) and two disordered regions that flank the DBD, one of which varies in size in the different isoforms. Notably, we were able to assign resonances that had previously been inaccessible because of the spectral complexity of the translational isoforms, which in turn allowed us to 1) identify a region of the structured DBD that undergoes significant changes in the local chemical environment in the presence of the disordered region and 2) determine differences in the conformational ensembles of the disordered regions of the translational isoforms. Furthermore, an ensemble-based thermodynamic analysis of the isoforms reveals conserved patterns of stability within the N-terminal domain of GR that persist despite low sequence conservation. These studies provide an avenue for further investigations of the mechanistic underpinnings of the functional relevance of the translational isoforms of GR while also providing a general NMR strategy for studying systems containing both structured and disordered regions.

Hidden dynamic signatures drive substrate selectivity in the disordered phosphoproteome

The discovery that more than 40% of the eukaryotic proteome is intrinsically disordered, and that these disordered segments are enriched in phosphorylation sites, suggests that conformational heterogeneity may be important to kinase selectivity. Indeed, phosphorylation prediction programs reliant on classic notions of conserved sequence information (i.e., “vertical information”) are only partially effective. We find that the conformational equilibrium of the phosphorylatable site, whose information is embedded in sequence-averaged energetic and structural properties of the protein (i.e., “horizontal information”), plays a major role in distinguishing phosphorylatable versus nonphosphorylatable sites. In fact, employing both horizontal and vertical information produces a state-of-the-art phosphorylation predictor, wherein the conformational equilibrium of the disordered chain is the dominant contributor.

Phosphorylation sites are hyperabundant in the eukaryotic disordered proteome, suggesting that conformational fluctuations play a major role in determining to what extent a kinase interacts with a particular substrate. In biophysical terms, substrate selectivity may be determined not just by the structural–chemical complementarity between the kinase and its protein substrates but also by the free energy difference between the conformational ensembles that are, or are not, recognized by the kinase. To test this hypothesis, we developed a statistical-thermodynamics-based informatics framework, which allows us to probe for the contribution of equilibrium fluctuations to phosphorylation, as evaluated by the ability to predict Ser/Thr/Tyr phosphorylation sites in the disordered proteome. Essential to this framework is a decomposition of substrate sequence information into two types: vertical information encoding conserved kinase specificity motifs and horizontal information encoding substrate conformational equilibrium that is embedded, but often not apparent, within position-specific conservation patterns. We find not only that conformational fluctuations play a major role but also that they are the dominant contribution to substrate selectivity. In fact, the main substrate classifier distinguishing selectivity is the magnitude of change in local compaction of the disordered chain upon phosphorylation of these mostly singly phosphorylated sites. In addition to providing fundamental insights into the consequences of phosphorylation across the proteome, our approach provides a statistical-thermodynamic strategy for partitioning any sequence-based search into contributions from structural–chemical complementarity and those from changes in conformational equilibrium.

The role of key residues in structure, function, and stability of cytochrome-c

Cytochrome-c (cyt-c), a multi-functional protein, plays a significant role in the electron transport chain, and thus is indispensable in the energy-production process. Besides being an important component in apoptosis, it detoxifies reactive oxygen species. Two hundred and eighty-five complete amino acid sequences of cyt-c from different species are known. Sequence analysis suggests that the number of amino acid residues in most mitochondrial cyts-c is in the range 104 ± 10, and amino acid residues at only few positions are highly conserved throughout evolution. These highly conserved residues are Cys14, Cys17, His18, Gly29, Pro30, Gly41, Asn52, Trp59, Tyr67, Leu68, Pro71, Pro76, Thr78, Met80, and Phe82. These are also known as "key residues", which contribute significantly to the structure, function, folding, and stability of cyt-c. The three-dimensional structure of cyt-c from ten eukaryotic species have been determined using X-ray diffraction studies. Structure analysis suggests that the tertiary structure of cyt-c is almost preserved along the evolutionary scale. Furthermore, residues of N/C-terminal helices Gly6, Phe10, Leu94, and Tyr97 interact with each other in a specific manner, forming an evolutionary conserved interface. To understand the role of evolutionary conserved residues on structure, stability, and function, numerous studies have been performed in which these residues were substituted with different amino acids. In these studies, structure deals with the effect of mutation on secondary and tertiary structure measured by spectroscopic techniques; stability deals with the effect of mutation on T m (midpoint of heat denaturation), ∆G D (Gibbs free energy change on denaturation) and folding; and function deals with the effect of mutation on electron transport, apoptosis, cell growth, and protein expression. In this review, we have compiled all these studies at one place. This compilation will be useful to biochemists and biophysicists interested in understanding the importance of conservation of certain residues throughout the evolution in preserving the structure, function, and stability in proteins.

Prediction of protein relative enthalpic stability from molecular dynamics simulations of the folded and unfolded states

For proteins of known structure, the relative enthalpic stability with respect to wild-type, ΔΔH(U), can be estimated by direct computation of the folded and unfolded state energies. We propose a model by which the change in stability upon mutation can be predicted from all-atom molecular dynamics simulations for the folded state and a peptide-based model for the unfolded state. The unfolding enthalpies are expressed in terms of environmental and hydration-solvent reorganization contributions that readily allow a residue-specific analysis of ΔΔH(U). The method is applied to estimate the relative enthalpic stability of variants with buried charged groups in T4 lysozyme. The predicted relative stabilities are in good agreement with experimental data. Environmental factors are observed to contribute more than hydration to the overall ΔΔH(U). The residue-specific analysis finds that the effects of burying charge are both localized and long-range. The enthalpy for hydration-solvent reorganization varies considerably among different amino-acid types, but because the variant folded state structures are similar to those of the wild-type, the hydration-solvent reorganization contribution to ΔΔH(U) is localized at the mutation site, in contrast to environmental contributions. Overall, mutation of apolar and polar amino acids to charged amino acids are destabilizing, but the reasons are complex and differ from site to site.

Protein hydrogen exchange: testing current models

To investigate the determinants of protein hydrogen exchange (HX), HX rates of most of the backbone amide hydrogens of Staphylococcal nuclease were measured by NMR methods. A modified analysis was used to improve accuracy for the faster hydrogens. HX rates of both near surface and well buried hydrogens are spread over more than 7 orders of magnitude. These results were compared with previous hypotheses for HX rate determination. Contrary to a common assumption, proximity to the surface of the native protein does not usually produce fast exchange. The slow HX rates for unprotected surface hydrogens are not well explained by local electrostatic field. The ability of buried hydrogens to exchange is not explained by a solvent penetration mechanism. The exchange rates of structurally protected hydrogens are not well predicted by algorithms that depend only on local interactions or only on transient unfolding reactions. These observations identify some of the present difficulties of HX rate prediction and suggest the need for returning to a detailed hydrogen by hydrogen analysis to examine the bases of structure-rate relationships, as described in the companion paper (Skinner et al., Protein Sci 2012;21:996-1005).

Binding techniques to study the allosteric energy cycle

Thermodynamic principles of cooperativity and allostery have long been used as a starting point to begin understanding the interplay between ligand binding events. Understanding the nature of allosteric effects requires an experimental technique that can be used to quantify ligand binding energies and simultaneously give experimental insights into the conformational dynamics at play upon ligand binding. CD spectroscopy provides macroscopic information about the relative secondary and tertiary structures present in a protein. Here, we use this spectroscopic technique with thermal shift assays wherein ligand binding constants can be quantified based on their stabilizing effect against thermally induced protein denaturation. Binding constants for two ligands are used to determine a pairwise coupling free energy which defines the shared energy that favors or opposes binding of the second ligand binding event in an allosteric system. In CD-based thermal shift assays, temperature is the driving force for protein unfolding and can also influence protein conformational dynamics present in the unbound protein or ligand-bound proteins. Dihydrofolate reductase (DHFR) and glutamate dehydrogenase (GDH) are proposed as example test systems. NADP and methotrexate bind DHFR with positive cooperativity. Mammalian GDH exhibits negative cooperativity with respect to binding of NAD and NADPH coenzyme molecules, activation by ADP, and inhibition by GTP.

Quantitative assessment of protein structural models by comparison of H/D exchange MS data with exchange behavior accurately predicted by DXCOREX

Peptide amide hydrogen/deuterium exchange mass spectrometry (DXMS) data are often used to qualitatively support models for protein structure. We have developed and validated a method (DXCOREX) by which exchange data can be used to quantitatively assess the accuracy of three-dimensional (3-D) models of protein structure. The method utilizes the COREX algorithm to predict a protein's amide hydrogen exchange rates by reference to a hypothesized structure, and these values are used to generate a virtual data set (deuteron incorporation per peptide) that can be quantitatively compared with the deuteration level of the peptide probes measured by hydrogen exchange experimentation. The accuracy of DXCOREX was established in studies performed with 13 proteins for which both high-resolution structures and experimental data were available. The DXCOREX-calculated and experimental data for each protein was highly correlated. We then employed correlation analysis of DXCOREX-calculated versus DXMS experimental data to assess the accuracy of a recently proposed structural model for the catalytic domain of a Ca(2+)-independent phospholipase A(2). The model's calculated exchange behavior was highly correlated with the experimental exchange results available for the protein, supporting the accuracy of the proposed model. This method of analysis will substantially increase the precision with which experimental hydrogen exchange data can help decipher challenging questions regarding protein structure and dynamics.

The role of protein conformational fluctuations in allostery, function, and evolution

It is now well-known that proteins exist at equilibrium as ensembles of conformational states rather than as unique static structures. Here we review from an ensemble perspective important biological effects of such spontaneous fluctuations on protein allostery, function, and evolution. However, rather than present a thorough literature review on each subject, we focus instead on connecting these phenomena through the ensemble-based experimental, theoretical, and computational investigations from our laboratory over the past decade. Special emphasis is given to insights that run counter to some of the prevailing ideas that have emerged over the past 40 years of structural biology research. For instance, when proteins are viewed as conformational ensembles rather than as single structures, the commonly held notion of an allosteric pathway as an obligate series of individual structural distortions loses its meaning. Instead, allostery can result from energetic linkage between distal sites as one Boltzmann distribution of states transitions to another. Additionally, the emerging principles from this ensemble view of proteins have proven surprisingly useful in describing the role of intrinsic disorder in inter-domain communication, functional adaptation mediated by mutational control of fluctuations, and evolutionary conservation of the energetics of protein stability.

Investigating homology between proteins using energetic profiles

Accumulated experimental observations demonstrate that protein stability is often preserved upon conservative point mutation. In contrast, less is known about the effects of large sequence or structure changes on the stability of a particular fold. Almost completely unknown is the degree to which stability of different regions of a protein is generally preserved throughout evolution. In this work, these questions are addressed through thermodynamic analysis of a large representative sample of protein fold space based on remote, yet accepted, homology. More than 3,000 proteins were computationally analyzed using the structural-thermodynamic algorithm COREX/BEST. Estimated position-specific stability (i.e., local Gibbs free energy of folding) and its component enthalpy and entropy were quantitatively compared between all proteins in the sample according to all-vs.-all pairwise structural alignment. It was discovered that the local stabilities of homologous pairs were significantly more correlated than those of non-homologous pairs, indicating that local stability was indeed generally conserved throughout evolution. However, the position-specific enthalpy and entropy underlying stability were less correlated, suggesting that the overall regional stability of a protein was more important than the thermodynamic mechanism utilized to achieve that stability. Finally, two different types of statistically exceptional evolutionary structure-thermodynamic relationships were noted. First, many homologous proteins contained regions of similar thermodynamics despite localized structure change, suggesting a thermodynamic mechanism enabling evolutionary fold change. Second, some homologous proteins with extremely similar structures nonetheless exhibited different local stabilities, a phenomenon previously observed experimentally in this laboratory. These two observations, in conjunction with the principal conclusion that homologous proteins generally conserved local stability, may provide guidance for a future thermodynamically informed classification of protein homology.

Protein structure and function are fundamentally determined by thermodynamics. However, for technical as well as historical reasons, current evolutionary classification schemes and bioinformatics tools do not fully utilize thermodynamic information to describe or analyze proteins. In this work, we address this deficiency by computationally estimating the position-specific thermodynamic quantities of stability (ΔG), enthalpy (ΔH), and entropy (TΔS) for a large and diverse representative sample of protein structures. The sample was drawn from an expertly curated database, such that accepted evolutionary relationships existed for all protein pairs. Importantly, trivial relationships between pairs highly similar in amino acid sequence were explicitly excluded. We found that all position-specific thermodynamic quantities ΔG, ΔH, and TΔS were more similar between proteins that were evolutionarily related (i.e., homologous), and were less similar between proteins that were not evolutionarily related (i.e., non-homologous), with stability being particularly similar between homologous proteins. However, interesting statistically significant exceptions to these trends were observed, exceptions that could indicate novel processes of functional adaptation or evolutionary fold change, mediated by thermodynamics, for the proteins involved. Taken together, these results expand our understanding of the role of thermodynamics in protein evolution and suggest an organizational framework for a future thermodynamically-informed classification of protein homology.

An energetic representation of protein architecture that is independent of primary and secondary structure

Protein fold classification often assumes that similarity in primary, secondary, or tertiary structure signifies a common evolutionary origin. However, when similarity is not obvious, it is sometimes difficult to conclude that particular proteins are completely unrelated. Clearly, a set of organizing principles that is independent of traditional classification could be valuable in linking different structural motifs and identifying common ancestry from seemingly disparate folds. Here, a four-dimensional ensemble-based energetic space spanned by a diverse set of proteins was defined and its characteristics were contrasted with those of Cartesian coordinate space. Eigenvector decomposition of this energetic space revealed the dominant physical processes contributing to the more or less stable regions of a protein. Unexpectedly, those processes were identical for proteins with different secondary structure content and were also identical among different amino-acid types. The implications of these results are twofold. First, it indicates that excited conformational states comprising the protein native state ensemble, largely invisible upon inspection of the high-resolution structure, are the major determinant of the energetic space. Second, it suggests that folds dissimilar in sequence or structure could nonetheless be energetically similar if their respective excited conformational states are considered, one example of which was observed in the N-terminal region of the Arc repressor switch mutant. Taken together, these results provide a surface area-based framework for understanding folds in energetic terms, a framework that may eventually yield a means of identifying common ancestry among structurally dissimilar proteins.