Amino acid residues, which play important roles in protein function, are often conserved. Here, we analyze thermodynamic and structural data of protein–DNA interactions to explore a relationship between free energy, sequence conservation and structural cooperativity. We observe that the most stabilizing residues or putative hotspots are those which occur as clusters of conserved residues. The higher packing density of the clusters and available experimental thermodynamic data of mutations suggest cooperativity between conserved residues in the clusters. Conserved singlets contribute to the stability of protein–DNA complexes to a lesser extent. We also analyze structural features of conserved residues and their clusters and examine their role in identifying DNA-binding sites. We show that about half of the observed conserved residue clusters are in the interface with the DNA, which could be identified from their amino acid composition; whereas the remaining clusters are at the protein–protein or protein–ligand interface, or embedded in the structural scaffolds. In protein–protein interfaces, conserved residues are highly correlated with experimental residue hotspots, contributing dominantly and often cooperatively to the stability of protein–protein complexes. Overall, the conservation patterns of the stabilizing residues in DNA-binding proteins also highlight the significance of clustering as compared to single residue conservation.
Thermodynamic parameters were determined for complex formation between the Grb2 SH2 domain and Ac–pTyr–Xaa–Asn derived tripeptides in which the Xaa residue is an α,α-cycloaliphatic amino acid that varies in ring size from 3- to 7-membered. Although the 6- and 7-membered ring analogs are approximately equipotent, binding affinities of those having 3- to 6-membered rings increase incrementally with ring size because increasingly more favorable binding enthalpies dominate increasingly unfavorable binding entropies, a finding consistent with an enthalpy-driven hydrophobic effect. Crystallographic analysis reveals that the only significant differences in structures of the complexes are in the number of van der Waals contacts between the domain and the methylene groups in the Xaa residues. There is a positive correlation between buried nonpolar surface area and binding free energy and enthalpy, but not with ΔCp. Displacing a water molecule from a protein-ligand interface is not necessarily reflected in a favorable change in binding entropy. These findings highlight some of the fallibilities associated with commonly held views of relationships of structure and energetics in protein-ligand interactions and have significant implications for ligand design.
Protein sequences are subject to a mosaic of constraint. Changes to functional domains and buried residues, for example, are more apt to disrupt protein structure and function than are changes to residues participating in loops or exposed to solvent. Regions of constraint on the tertiary structure of a protein often result in loose segmentation of its primary structure into stretches of slowly- and rapidly-evolving amino acids. This clustering can be exploited, and existing methods have done so by relying on local sequence conservation as a signature of selection to help identify functionally important regions within proteins. We invert this paradigm by leveraging the regional nature of protein structure and function to both illuminate and make use of genome-wide patterns of local sequence conservation.
Our hypothesis is that the regional nature of structural and functional constraints will assert a positive autocorrelation on the evolutionary rates of neighboring sites, which, in a pairwise comparison of orthologous proteins, will manifest itself as the clustering of non-synonymous changes across the amino acid sequence. We introduce a dispersion ratio statistic to test this and related hypotheses. Using genome-wide interspecific comparisons of orthologous protein pairs, we reveal a strong log-linear relationship between the degree of clustering and the intensity of constraint. We further demonstrate how this relationship varies with the evolutionary distance between the species being compared. We provide some evidence that proteins with a history of positive selection deviate from genome-wide trends.
We find a significant association between the evolutionary rate of a protein and the degree to which non-synonymous changes cluster along its primary sequence. We show that clustering is a non-redundant predictor of evolutionary rate, and we speculate that conflicting signals of clustering and constraint may be indicative of a historical period of relaxed selection.
Cysteine (Cys) is an enigmatic amino acid residue. Although one of the least abundant, it often occurs in functional sites of proteins. Whereas free Cys is a polar amino acid, Cys in proteins is often buried and its classification on the hydrophobicity scale is ambiguous. We hypothesized that deviation of Cys residues from the properties of a free amino acid is due to their reactivity and addressed this possibility by examining Cys in large protein structure datasets. Compared to other amino acids, Cys was characterized by the most extreme conservation pattern, with the majority of Cys being either highly conserved or poorly conserved. In addition, clustering of Cys with another Cys residue was associated with high conservation, whereas exposure of Cys on protein surface with low conservation. Moreover, although clustered Cys behaved as polar residues, isolated Cys was the most buried residue of all, in disagreement with known physico-chemical properties of Cys. Thus, anomalous hydrophobic behavior and conservation pattern of Cys can be explained by elimination, during evolution, of isolated Cys from protein surface and clustering of other Cys residues. These findings indicate that Cys abundance is governed by Cys function in protein rather than by the sheer chemical and physical properties of the free amino acid, and suggest that high tendency of Cys to be functionally active can considerably limit its abundance on protein surface.
Cysteine; reactive thiols; amino acid conservation; exposure; polarity; hydrophobic scales
We determined the 2.45 Å crystal structure of the nucleosome core particle from Drosophila melanogaster and compared it to that of Xenopus laevis bound to the identical 147 base-pair DNA fragment derived from human α-satellite DNA. Differences between the two structures primarily reflect sixteen amino acid substitutions between species, fifteen of which are in histones H2A and H2B. Four of these involve histone tail residues, resulting in subtly altered protein-DNA interactions that exemplify the structural plasticity of these tails. Of the twelve substitutions occurring within the histone core regions, five involve small, solvent-exposed residues not involved in intra-particle interactions. The remaining seven involve buried hydrophobic residues, and appear to have co-evolved so as to preserve the volume of side chains within the H2A hydrophobic core and H2A-H2B dimer interface. Thus, apart from variations in the histone tails, amino acid substitutions that differentiate Drosophila from Xenopus histones occur in mutually compensatory combinations. This highlights the tight evolutionary constraints exerted on histones since the vertebrate and invertebrate lineages diverged.
Chromatin; nucleosome core particles; protein-DNA interaction; Drosophila; crystal structure
We determined the 2.45 Å crystal structure of the nucleosome core particle from Drosophila melanogaster and compared it to that of Xenopus laevis bound to the identical 147 base-pair DNA fragment derived from human α-satellite DNA. Differences between the two structures primarily reflect 16 amino acid substitutions between species, 15 of which are in histones H2A and H2B. Four of these involve histone tail residues, resulting in subtly altered protein–DNA interactions that exemplify the structural plasticity of these tails. Of the 12 substitutions occurring within the histone core regions, five involve small, solvent-exposed residues not involved in intraparticle interactions. The remaining seven involve buried hydrophobic residues, and appear to have coevolved so as to preserve the volume of side chains within the H2A hydrophobic core and H2A-H2B dimer interface. Thus, apart from variations in the histone tails, amino acid substitutions that differentiate Drosophila from Xenopus histones occur in mutually compensatory combinations. This highlights the tight evolutionary constraints exerted on histones since the vertebrate and invertebrate lineages diverged.
chromatin; nucleosome core particles; protein–DNA interaction; Drosophila; crystal structure
Structural consequences of ionization of residues buried in the hydrophobic interior of proteins were examined systematically in 25 proteins with internal Lys residues. Crystal structures showed that the ionizable groups are buried. NMR spectroscopy showed that in 2 of 25 cases studied the ionization of an internal Lys unfolded the protein globally. In 5 cases the internal charge triggered localized changes in structure and dynamics, and in 3 cases they promoted partial or local unfolding. Remarkably, in 15 proteins the ionization of the internal Lys resulted in no detectable structural consequences. Highly stable proteins appear to be inherently capable of withstanding the presence of charge in their hydrophobic interior, without the need for specialized structural adaptations. The extent of structural reorganization paralleled loosely with global thermodynamic stability, suggesting that structure-based pKa calculations for buried residues could be improved by calculation of thermodynamic stability and by enhanced conformational sampling.
electrostatics; proteins; pKa values; buried charged NMR spectroscopy; staphylococcal nuclease
Identifying mutations that stabilize proteins is challenging because most substitutions are destabilizing. In addition to being of immense practical utility, the ability to evolve protein stability in vivo may indicate how evolution has formed today's protein sequences. Here we describe a genetic selection that directly links the in vivo stability of proteins to antibiotic resistance. It allows the identification of stabilizing mutations within proteins. The large majority of mutants selected for improved antibiotic resistance are stabilized both thermodynamically and kinetically, indicating that similar principles govern stability in vivo and in vitro. The approach requires no prior structural or functional knowledge and allows selection for stability without a need to maintain function. Mutations that enhance thermodynamic stability of the protein Im7 map overwhelmingly to surface residues involved in binding to colicin E7, implying that evolutionary pressures that drive Im7-E7 complex formation may have compromised the stability of the isolated Im7 protein.
Residue depth (RD) is a solvent exposure measure that complements the information provided by conventional accessible surface area (ASA) and describes to what extent a residue is buried in the protein structure space. Previous studies have established that RD is correlated with several protein properties, such as protein stability, residue conservation and amino acid types. Accurate prediction of RD has many potentially important applications in the field of structural bioinformatics, for example, facilitating the identification of functionally important residues, or residues in the folding nucleus, or enzyme active sites from sequence information. In this work, we introduce an efficient approach that uses support vector regression to quantify the relationship between RD and protein sequence. We systematically investigated eight different sequence encoding schemes including both local and global sequence characteristics and examined their respective prediction performances. For the objective evaluation of our approach, we used 5-fold cross-validation to assess the prediction accuracies and showed that the overall best performance could be achieved with a correlation coefficient (CC) of 0.71 between the observed and predicted RD values and a root mean square error (RMSE) of 1.74, after incorporating the relevant multiple sequence features. The results suggest that residue depth could be reliably predicted solely from protein primary sequences: local sequence environments are the major determinants, while global sequence features could influence the prediction performance marginally. We highlight two examples as a comparison in order to illustrate the applicability of this approach. We also discuss the potential implications of this new structural parameter in the field of protein structure prediction and homology modeling. This method might prove to be a powerful tool for sequence analysis.
The structures of polio-, coxsackie-, and rhinovirus polymerases have revealed a conserved yet unusual protein conformation surrounding their buried N termini where a β-strand distortion results in a solvent-exposed hydrophobic amino acid at residue 5. In a previous study, we found that coxsackievirus polymerase activity increased or decreased depending on the size of the amino acid at residue 5 and proposed that this residue becomes buried during the catalytic cycle. In this work, we extend our studies to show that poliovirus polymerase activity is also dependent on the nature of residue 5 and further elucidate which aspects of polymerase function are affected. Poliovirus polymerases with mutations of tryptophan 5 retain wild-type elongation rates, RNA binding affinities, and elongation complex formation rates but form unstable elongation complexes. A large hydrophobic residue is required to maintain the polymerase in an elongation-competent conformation, and smaller hydrophobic residues at position 5 progressively decrease the stability of elongation complexes and their processivity on genome-length templates. Consistent with this, the mutations also reduced viral RNA production in a cell-free replication system. In vivo, viruses containing residue 5 mutants produce viable virus, and an aromatic phenylalanine was maintained with only a slightly decreased virus growth rate. However, nonaromatic amino acids resulted in slow-growing viruses that reverted to wild type. The structural basis for this polymerase phenotype is yet to be determined, and we speculate that amino acid residue 5 interacts directly with template RNA or is involved in a protein structural interaction that stabilizes the elongation complex.
Phylogenetic profiling of amino acid substitution patterns in proteins has led many to conclude that most structural information is carried by interior core residues that are solvent inaccessible. This conclusion is based on the observation that buried residues generally tolerate only conserved sequence changes, while surface residues allow more diverse chemical substitutions. This notion is now changing as it has become apparent that both core and surface residues play important roles in protein folding and stability. Unfortunately, the ability to identify specific mutations that will lead to enhanced stability remains a challenging problem. Here we discuss two mutations that emerged from an in vitro selection experiment designed to improve the folding stability of a non-biological ATP binding protein. These mutations alter two solvent accessible residues, and dramatically enhance the expression, solubility, thermal stability, and ligand binding affinity of the protein. The significance of both mutations was investigated individually and together, and the X-ray crystal structures of the parent sequence and double mutant protein were solved to a resolution limit of 2.8 and 1.65 Å, respectively. Comparative structural analysis of the evolved protein to proteins found in nature reveals that our non-biological protein evolved certain structural features shared by many thermophilic proteins. This experimental result suggests that protein fold optimization by in vitro selection offers a viable approach to generating stable variants of many naturally occurring proteins whose structures and functions are otherwise difficult to study.
We compare various predicted mechanical and thermodynamic properties of nine oxidized thioredoxins (TRX) using a Distance Constraint Model (DCM). The DCM is based on a nonadditive free energy decomposition scheme, where entropic contributions are determined from rigidity and flexibility of structure based on distance constraints. We perform averages over an ensemble of constraint topologies to calculate several thermodynamic and mechanical response functions that together yield quantitative stability/flexibility relationships (QSFR). Applied to the TRX protein family, QSFR metrics display a rich variety of similarities and differences. In particular, backbone flexibility is well conserved across the family, whereas cooperativity correlation describing mechanical and thermodynamic couplings between residue pairs exhibit distinctive features that readily standout. The diversity in predicted QSFR metrics that describe cooperativity correlation between pairs of residues is largely explained by a global flexibility order parameter describing the amount of intrinsic flexibility within the protein. A free energy landscape is calculated as a function of the flexibility order parameter, and key values are determined where the native-state, transition-state and unfolded-state are located. Another key value identifies a mechanical transition where the global nature of the protein changes from flexible to rigid. The key values of the flexibility order parameter help characterize how mechanical and thermodynamic response is linked. Variation in QSFR metrics, and key characteristics of global flexibility are related to the native state x-ray crystal structure primarily through the hydrogen bond network. Furthermore, comparison of three TRX redox pairs reveals differences in thermodynamic response (i.e., relative melting point) and mechanical properties (i.e., backbone flexibility and cooperativity correlation) that are consistent with experimental data on thermal stabilities and NMR dynamical profiles. The results taken together demonstrate that small-scale structural variations are amplified into discernible global differences by propagating mechanical couplings through the H-bond network.
thioredoxin; quantified stability/flexibility relationships; hydrogen bond network; molecular cooperativity; free energy landscape; rigidity
Rapid evolution is a hallmark of centromeric DNA in eukaryotic genomes. Yet, the centromere itself has a conserved functional role that is mediated by the kinetochore protein complex. To broaden our understanding about both the DNA and proteins that interact at the functional centromere, we sought to gain a detailed view of the evolutionary events that have shaped the primate kinetochore. Specifically, we performed comparative mapping and sequencing of the genomic regions encompassing the genes encoding three foundation kinetochore proteins: Centromere Proteins A, B, and C (CENP-A, CENP-B, and CENP-C). A histone H3 variant, CENP-A provides the foundation of the centromere-specific nucleosome. Comparative sequence analyses of the CENP-A gene in 14 primate species revealed encoded amino-acid residues within both the histone-fold domain and the N-terminal tail that are under strong positive selection. Similar comparative analyses of CENP-C, another foundation protein essential for centromere function, identified amino-acid residues throughout the protein under positive selection in the primate lineage, including several in the centromere localization and DNA-binding regions. Perhaps surprisingly, the gene encoding CENP-B, a kinetochore protein that binds specifically to alpha-satellite DNA, was not found to be associated with signatures of positive selection. These findings point to important and distinct evolutionary forces operating on the DNA and proteins of the primate centromere.
kinetochore; selection; evolution; centromere
Many proteins exist and function as oligomers. While hydrophobic interactions have been recognized as the major driving force for oligomerization, detailed molecular mechanisms for the assembly are unknown. Here, we used 14-3-3σ as a model protein and investigated the role of hydrophobic residues at the dimeric interface using MD simulations and coimmunoprecipitations. We found that a half-exposed and half-buried residue in the interface, Phe25, plays a more important role in promoting homodimerization than the hydrophobic core residues by organizing both favorable hydrophobic and hydrophilic interactions. Phe25 is critical in packing and stabilizing hydrophobic core residues. We conclude that the structural stability of hydrophobic cores is critical for a stable homodimer complex and this stable property can be bestowed by residues outside of hydrophobic core. The important organizing activity of Phe25 for homodimerization of 14-3-3σ originates from its unique physical location, rigidity, size, and hydrophobicity. Thus, hydrophobic residues that are not deeply buried at the oligomeric interface may play important but different roles from the buried core residues and they may promote oligomerization by organizing co-operativity of core and other residues for favorable hydrophobic and electrostatic interactions.
Since thermodynamic stability is a global property of proteins that has to be conserved during evolution, the selective pressure at a given site of a protein sequence depends on the amino acids present at other sites. However, models of molecular evolution that aim at reconstructing the evolutionary history of macromolecules become computationally intractable if such correlations between sites are explicitly taken into account.
We introduce an evolutionary model with sites evolving independently under a global constraint on the conservation of structural stability. This model consists of a selection process, which depends on two hydrophobicity parameters that can be computed from protein sequences without any fit, and a mutation process for which we consider various models. It reproduces quantitatively the results of Structurally Constrained Neutral (SCN) simulations of protein evolution in which the stability of the native state is explicitly computed and conserved. We then compare the predicted site-specific amino acid distributions with those sampled from the Protein Data Bank (PDB). The parameters of the mutation model, whose number varies between zero and five, are fitted from the data. The mean correlation coefficient between predicted and observed site-specific amino acid distributions is larger than = 0.70 for a mutation model with no free parameters and no genetic code. In contrast, considering only the mutation process with no selection yields a mean correlation coefficient of = 0.56 with three fitted parameters. The mutation model that best fits the data takes into account increased mutation rate at CpG dinucleotides, yielding = 0.90 with five parameters.
The effective selection process that we propose reproduces well amino acid distributions as observed in the protein sequences in the PDB. Its simplicity makes it very promising for likelihood calculations in phylogenetic studies. Interestingly, in this approach the mutation process influences the effective selection process, i.e. selection and mutation must be entangled in order to obtain effectively independent sites. This interdependence between mutation and selection reflects the deep influence that mutation has on the evolutionary process: The bias in the mutation influences the thermodynamic properties of the evolving proteins, in agreement with comparative studies of bacterial proteomes, and it also influences the rate of accepted mutations.
Prediction of protein solvent accessibility, also called accessible surface area (ASA) prediction, is an important step for tertiary structure prediction directly from one-dimensional sequences. Traditionally, predicting solvent accessibility is regarded as either a two- (exposed or buried) or three-state (exposed, intermediate or buried) classification problem. However, the states of solvent accessibility are not well-defined in real protein structures. Thus, a number of methods have been developed to directly predict the real value ASA based on evolutionary information such as position specific scoring matrix (PSSM).
This study enhances the PSSM-based features for real value ASA prediction by considering the physicochemical properties and solvent propensities of amino acid types. We propose a systematic method for identifying residue groups with respect to protein solvent accessibility. The amino acid columns in the PSSM profile that belong to a certain residue group are merged to generate novel features. Finally, support vector regression (SVR) is adopted to construct a real value ASA predictor. Experimental results demonstrate that the features produced by the proposed selection process are informative for ASA prediction.
Experimental results based on a widely used benchmark reveal that the proposed method performs best among several of existing packages for performing ASA prediction. Furthermore, the feature selection mechanism incorporated in this study can be applied to other regression problems using the PSSM. The program and data are available from the authors upon request.
The concept of conservation of amino acids is widely used to identify important alignment positions of orthologs. The assumption is that important amino acid residues will be conserved in the protein family during the evolutionary process. For paralog alignment, on the other hand, the opposite concept can be used to identify residues that are responsible for specificity. Assuming that the function-specific or ligand-specific residue positions will have higher diversity since they are under evolutionary pressure to fit the target specificity, these function-specific or ligand-specific residues positions will have a lower degree of conservation than other positions in a highly conserved paralog alignment. This study assessed the ability of reverse conservation analysis to identify function-specific and ligand-specific residue positions in closely related paralog.
Reverse conservation analysis of paralog alignments successfully identified all six previously reported substrate recognition sites (SRSs) in cytochrome P450 family 2 (CYP 2). Further analysis of each subfamily identified the specificity-determining residues (SDRs) that have been experimentally found. New potential SDRs were also predicted and await confirmation by further experiments or modeling calculations. This concept may be also applied to identify SDRs in other protein families.
reverse conservation analysis; P450; CYP 2; SDR
It has been widely recognized that the mutations at specific directions are caused by the functional constraints in protein family and the directional mutations at certain positions control the evolutionary direction of the protein family. The mutations at different positions, even distantly separated, are mutually coupled and form an evolutionary network. Finding the controlling mutative positions and the mutative network among residues are firstly important for protein rational design and enzyme engineering.
A computational approach, namely amino acid position conservation-mutation correlation analysis (CMCA), is developed to predict mutually mutative positions and find the evolutionary network in protein family. The amino acid position mutative function, which is the foundational equation of CMCA measuring the mutation of a residue at a position, is derived from the MSA (multiple structure alignment) database of protein evolutionary family. Then the position conservation correlation matrix and position mutation correlation matrix is constructed from the amino acid position mutative equation. Unlike traditional SCA (statistical coupling analysis) approach, which is based on the statistical analysis of position conservations, the CMCA focuses on the correlation analysis of position mutations.
As an example the CMCA approach is used to study the PDZ domain of protein family, and the results well illustrate the distantly allosteric mechanism in PDZ protein family, and find the functional mutative network among residues. We expect that the CMCA approach may find applications in protein engineering study, and suggest new strategy to improve bioactivities and physicochemical properties of enzymes.
Recently, we demonstrated that yeast protein evolutionary rate at the level of individual amino acid residues scales linearly with degree of solvent accessibility. This residue-level structure-evolution relationship is sensitive to protein core size: surface residues from large-core proteins evolve much faster than those from small-core proteins, while buried residues are equally constrained independent of protein core size. In this work, we investigate the joint effects of protein core size and expression on the residue-level structure-evolution relationship. At the whole-protein level, protein expression is a much more dominant determinant of protein evolutionary rate than protein core size. In contrast, at the residue level, protein core size and expression both have major impacts on protein structure-evolution relationships. In addition, protein core size and expression influence residue-level structure-evolution relationships in qualitatively different ways. Protein core size preferentially affects the non-synonymous substitution rates of surface residues compared to buried residues, and has little influence on synonymous substitution rates. In comparison, protein expression uniformly affects all residues independent of degree of solvent accessibility, and affects both non-synonymous and synonymous substitution rates. Protein core size and expression exert largely independent effects on protein evolution at the residue level, and can combine to produce dramatic changes in the slope of the linear relationship between residue evolutionary rate and solvent accessibility. Our residue-level findings demonstrate that protein core size and expression are both important, yet qualitatively different, determinants of protein evolution. These results underscore the complementary nature of residue-level and whole-protein analysis of protein evolution.
The assembly and disassembly of chromatin impacts all DNA dependent processes in eukaryotes. These processes are intricately regulated through stepwise mechanisms, requiring multiple proteins, post-translational modifications and remodeling enzymes, as well as specific proteins to chaperone the highly basic and aggregation-prone histone proteins. The histone chaperones are acidic proteins that perform the latter function by maintaining the stability of the histones when they are not associated with DNA and guiding the deposition and removal of histones from DNA. Understanding the thermodynamics of these processes provides deeper insights into the mechanisms of chromatin assembly and disassembly. Here we describe complementary thermodynamic and biochemical approaches for analysis of the interactions of a major chaperone of the H3/H4 dimer, Anti-silencing function 1 (Asf1) with histones H3/H4 and DNA. Fluorescence quenching approaches are useful for measuring the binding affinity of Asf1 for histones H3/H4 under equilibrium conditions. Electrophoretic mobility shift analyses are useful for examining Asf1 mediated tetrasome (H3/H4-DNA) assembly and disassembly processes. These approaches potentially can be used more generally for the study of other histone chaperone-histone interactions and provide a means to dissect the role of post-translational modifications and other factors that participate in chromatin dynamics.
Anti-silencing function 1 (Asf1); histone H3/H4; tetrasome; binding affinity; fluorescence; electrophoretic mobility shift assay
We have recently discovered that the two tryptophans of human β2-microglobulin have distinctive roles within the structure and function of the protein. Deeply buried in the core, Trp95 is essential for folding stability, whereas Trp60, which is solvent-exposed, plays a crucial role in promoting the binding of β2-microglobulin to the heavy chain of the class I major histocompatibility complex (MHCI). We have previously shown that the thermodynamic disadvantage of having Trp60 exposed on the surface is counter-balanced by the perfect fit between it and a cavity within the MHCI heavy chain that contributes significantly to the functional stabilization of the MHCI. Therefore, based on the peculiar differences of the two tryptophans, we have analysed the evolution of β2-microglobulin with respect to these residues.
Having defined the β2-microglobulin protein family, we performed multiple sequence alignments and analysed the residue conservation in homologous proteins to generate a phylogenetic tree. Our results indicate that Trp60 is highly conserved, whereas some species have a Leu in position 95; the replacement of Trp95 with Leu destabilizes β2-microglobulin by 1 kcal/mol and accelerates the kinetics of unfolding. Both thermodynamic and kinetic data fit with the crystallographic structure of the Trp95Leu variant, which shows how the hydrophobic cavity of the wild-type protein is completely occupied by Trp95, but is only half filled by Leu95.
We have established that the functional Trp60 has been present within the sequence of β2-microglobulin since the evolutionary appearance of proteins responsible for acquired immunity, whereas the structural Trp95 was selected and stabilized, most likely, for its capacity to fully occupy an internal cavity of the protein thereby creating a better stabilization of its folded state.
A great deal is known about the qualitative aspects of the sequence-structure relationship, for example that buried residues are usually more conserved between structurally similar homologues, but no attempts have been made to quantitate the relationship between evolutionary conservation at a sequence position and change to global tertiary structure. In this paper we demonstrate that the Spearman correlation between sequence and structural change is suitable for this purpose.
Buried residues, bends, cysteines, prolines and leucines were significantly more likely to occupy positions highly correlated with structural change than expected by chance. Some buried residues were found to be less informative than expected, particularly residues involved in active sites and the binding of small molecules.
The correlation-based method generates predictions of structural importance for superfamily positions which agree well with previous results of manual analyses, and may be of use in automated residue annotation piplines. A PERL script which implements the method is provided.
Protein thermodynamic stability is a fundamental physical characteristic that determines biological function. Furthermore, alteration of thermodynamic stability by macromolecular interactions or biochemical modifications is a powerful tool for assessing the relationship between protein structure, stability, and biological function. High-throughput approaches for quantifying protein stability are beginning to emerge that enable thermodynamic measurements on small amounts of material, in short periods of time, and using readily accessible instrumentation. Here we present such a method, fast quantitative cysteine reactivity (fQCR), which exploits the linkage between protein stability, sidechain protection by protein structure, and structural dynamics to characterize the thermodynamic and kinetic properties of proteins. In this approach, the reaction of a protected cysteine and thiol-reactive fluorogenic indicator is monitored over a gradient of temperatures after a short incubation time. These labeling data can be used to determine the midpoint of thermal unfolding, measure the temperature dependence of protein stability, quantify ligand-binding affinity, and, under certain conditions, estimate folding rate constants. Here, we demonstrate the fQCR method by characterizing these thermodynamic and kinetic properties for variants of Staphylococcal nuclease and E. coli ribose-binding protein engineered to contain single, protected cysteines. These straightforward, information-rich experiments are likely to find applications in protein engineering and functional genomics.
quantitative cysteine reactivity; thiol reactivity; protein thermodynamic stability; conformational free energy; protein folding kinetics; linkage analysis of protein stability; dissociation constants binding affinity; Staphylococcal nuclease; ribose-binding protein
Membrane curvature of a biological cell is actively involved in various fundamental cell biological functions. It has been discovered that membrane curvature and binding of peripheral membrane proteins follow a symbiotic relationship. The exact mechanism behind this interplay of protein binding and membrane curvature has not yet been properly understood. To improve understanding of the mechanism, we study curvature sorting of proteins in a model system consisting of a tether pulled from a giant unilamellar vesicle using mechanical-thermodynamic models. The concentration of proteins bound to the membrane changes significantly due to curvature. This has also been observed in experiments by other researchers. We also find that there is a phase transition based on protein concentration and we discuss the coexistence of phases and stability of solutions. Furthermore, when sorting is favorable, the increase in protein concentration stabilizes the tether in the sense that less pulling force is required to maintain the tether. A similar mechanism may be in place, when motor proteins pull tethers from donor membranes.
We have performed a kinetic and thermodynamic analysis of 3Dpol derivatives containing substitutions in the ribose-binding pocket with ATP analogues containing correct and incorrect sugar configurations. We find that Asp-238, a residue in structural motif A that is conserved in all RNA-dependent RNA polymerases, is a key determinant of polymerase fidelity. Alterations in the position of the Asp-238 side chain destabilize the catalytically competent 3Dpol-primer/template-NTP complex and reduce the efficiency of phosphoryl transfer. The reduction in phosphoryl transfer may be a reflection of increased mobility of other residues in motif A that are required for stabilizing the triphosphate moiety of the nucleotide substrate in the active conformation. We present a structural model to explain how Asp-238 functions to select nucleotides with a correct sugar configuration and a correct base. We propose that this mechanism is employed by all RNA-dependent RNA polymerases. We discuss the possibility that all nucleic acid polymerases with the canonical “palm”-based active site employ a similar mechanism to maximize fidelity.