Statistical characterization of salt bridges in proteins

The structure and folding mechanism of a given protein are determined by many factors, including the electrostatic interactions between charged residues of protein molecules known in general as salt bridges. In this study, analyses were conducted on 10,370 salt bridges in 2017 proteins and the results compared to previous statistical surveys of 36 protein structures. Although many of the general trends remained consistent with other studies, more detailed information was illuminated by the larger dataset. In particular, it was shown that there is a strong correlation between secondary structure and salt bridge formation, and that salt bridges display preferential formation in an environment of about 30% solvent accessible surface area.     

Effects of salt bridges on protein structure and design.

Theoretical calculations (Hendsch ZS & Tidor B, 1994, Protein Sci 3:211-226) and experiments (Waldburger CD et al., 1995, Nat Struct Biol 2:122-128; Wimley WC et al., 1996, Proc Natl Acad Sci USA 93:2985-2990) suggest that hydrophobic interactions are more stabilizing than salt bridges in protein folding. The lack of apparent stability benefit for many salt bridges requires an alternative explanation for their occurrence within proteins. To examine the effect of salt bridges on protein structure and stability in more detail, we have developed an energy function for simple cubic lattice polymers based on continuum electrostatic calculations of a representative selection of salt bridges found in known protein crystal structures. There are only three types of residues in the model, with charges of -1, 0, or + 1. We have exhaustively enumerated conformational space and significant regions of sequence space for three-dimensional cubic lattice polymers of length 16. The results demonstrate that, while the more highly charged sequences are less stable, the loss of stability is accompanied by a substantial reduction in the degeneracy of the lowest-energy state. Moreover, the reduction in degeneracy is greater due to charges that pair than for lone charges that remain relatively exposed to solvent. We have also explored and illustrated the use of ion-pairing strategies for rational structural design using model lattice studies.     

Patterns in ionizable side chain interactions in protein structures

In a selected set of 44 high-resolution, non-homologous protein structures, the intramolecular hydrogen bonds or salt bridges formed by ionizable amino acid side chains were identified and analyzed. The analysis was based on the investigation of several properties of the involved residues such as their solvent exposure, their belonging to a certain secondary structural element, and their position relative to the N- and C-termini of their respective structural element. It was observed that two-thirds of the interactions made by basic or acidic side chains are hydrogen bonds to polar uncharged groups. In particular, the majority (78%) of the hydrogen bonds between ionizable side chains and main chain polar groups (sch:mch bonds) involved at least one buried atom, and in 42% of the cases both interacting atoms were buried. In α-helices, the sch:mch bonds observed in the proximity of the C- and N-termini show a clear preference for acidic and basic side chains, respectively. This appears to be due to the partial charges of peptide group atoms at the termini of α-helices, which establish energetically favorable electrostatic interactions with side chain carrying opposite charge, at distances even greater than 4.5 Å. The sch:mch interactions involving ionizable side chains that belong either to β-strands or to the central part of α-helices are based almost exclusively on basic residues. This results from the presence of main chain carbonyl oxygen atoms in the protein core which have unsatisfied hydrogen bonding capabilities.     

On the calculation of pKas in proteins

This paper describes a general method to calculate the pK_as of ionizable groups in proteins. Electrostatic calculations are carried out using the finite difference Poisson–Boltzmann (FDPB) method. A formal treatment of the calculation of pK_as within the framework of the FDPB method is presented. The major change with respect to previous work is the specific incorporation of the complete charge distribution of both the neutral and charged forms of each ionizable group into the formalism. This is extremely important for the treatment of salt bridges. A hybrid statistical mechanical/Tanford–Roxby method, which is found to be significantly faster than previous treatments, is also introduced. This simplifies the problem of summing over the large number of possible ionization states for a complex polyion. Applications to BPTI and serine proteases suggest that the calculations can be quite reliable. However, the necessity of including bound waters in the treatment of the Asp-70…His-31 salt bridge in T4 lysozyme and experience with other proteins suggest that additional factors ultimately need to be considered in a comprehensive treatment of pK_as in proteins. © 1993 Wiley-Liss, Inc.     

Prediction of residues in discontinuous B-cell epitopes using protein 3D structures

Discovery of discontinuous B-cell epitopes is a major challenge in vaccine design. Previous epitope prediction methods have mostly been based on protein sequences and are not very effective. Here, we present DiscoTope, a novel method for discontinuous epitope prediction that uses protein three-dimensional structural data. The method is based on amino acid statistics, spatial information, and surface accessibility in a compiled data set of discontinuous epitopes determined by X-ray crystallography of antibody/antigen protein complexes. DiscoTope is the first method to focus explicitly on discontinuous epitopes. We show that the new structure-based method has a better performance for predicting residues of discontinuous epitopes than methods based solely on sequence information, and that it can successfully predict epitope residues that have been identified by different techniques. DiscoTope detects 15.5% of residues located in discontinuous epitopes with a specificity of 95%. At this level of specificity, the conventional Parker hydrophilicity scale for predicting linear B-cell epitopes identifies only 11.0% of residues located in discontinuous epitopes. Predictions by the DiscoTope method can guide experimental epitope mapping in both rational vaccine design and development of diagnostic tools, and may lead to more efficient epitope identification.     

Overexpression of a tobacco small G protein gene NtRop1 causes salt sensitivity and hydrogen peroxide production in transgenic plants

The small GTPases of Rop/Rho family is central regulators of important cellular processes in plants. Tobacco small G protein gene NtRop1 has been isolated; however, its roles in stress responses were unknown. In the present study, the genomic sequence of NtRop1 was cloned, which has seven exons and six introns, similar to the Rop gene structure from Arabidopsis. The NtRop1 gene was constitutively expressed in the different organs whereas the other six Rop genes from tobacco had differential expression patterns. The expression of the NtRop1 gene was moderately induced by methyl viologen, NaCl, and ACC treatments, but slightly inhibited by ABA treatment, with no significant induction by NAA treatment. The transgenic Arabidopsis plants overexpressing the NtRop1 showed increased salt sensitivity as can be seen from the reduced root growth and elevated relative electrolyte leakage. The hydrogen peroxide production was also promoted in the NtRop1-trangenic plants in comparison with wild type plants. These results imply that the NtRop1 may confer salt sensitivity through activation of H2O2 production during plant response to salt stress.     

Electrostatic interactions in leucine zippers: thermodynamic analysis of the contributions of Glu and His residues and the effect of mutating salt bridges

Electrostatic interactions play a complex role in stabilizing proteins. Here, we present a rigorous thermodynamic analysis of the contribution of individual Glu and His residues to the relative pH-dependent stability of the designed disulfide-linked leucine zipper AB(SS). The contribution of an ionized side-chain to the pH-dependent stability is related to the shift of the pK(a) induced by folding of the coiled coil structure. pK(a)(F) values of ten Glu and two His side-chains in folded AB(SS) and the corresponding pK(a)(U) values in unfolded peptides with partial sequences of AB(SS) were determined by 1H NMR spectroscopy: of four Glu residues not involved in ion pairing, two are destabilizing (-5.6 kJ mol(-1)) and two are interacting with the positive alpha-helix dipoles and are thus stabilizing (+3.8 kJ mol(-1)) in charged form. The two His residues positioned in the C-terminal moiety of AB(SS) interact with the negative alpha-helix dipoles resulting in net stabilization of the coiled coil conformation carrying charged His (-2.6 kJ mol(-1)). Of the six Glu residues involved in inter-helical salt bridges, three are destabilizing and three are stabilizing in charged form, the net contribution of salt-bridged Glu side-chains being destabilizing (-1.1 kJ mol(-1)). The sum of the individual contributions of protonated Glu and His to the higher stability of AB(SS) at acidic pH (-5.4 kJ mol(-1)) agrees with the difference in stability determined by thermal unfolding at pH 8 and pH 2 (-5.3 kJ mol(-1)). To confirm salt bridge formation, the positive charge of the basic partner residue of one stabilizing and one destabilizing Glu was removed by isosteric mutations (Lys-->norleucine, Arg-->norvaline). Both mutations destabilize the coiled coil conformation at neutral pH and increase the pK(a) of the formerly ion-paired Glu side-chain, verifying the formation of a salt bridge even in the case where a charged side-chain is destabilizing. Because removing charges by a double mutation cycle mainly discloses the immediate charge-charge effect, mutational analysis tends to overestimate the overall energetic contribution of salt bridges to protein stability.     

Distance-constraint approach to protein folding. I. Statistical analysis of protein conformations in terms of distances between residues

A statistical analysis of protein conformations in terms of the distance between residues, represented by their C atoms, is presented. We consider four factors that contribute to the determination of the distanced _i,i+k between a given pair ofith and(i+k)th residues in the native conformation of a globular protein: (1) the distancek along the chain, (2) the size of the protein, (3) the conformational states of theith to(i+k)th residues, and (4) the amino acid types of the and(i+k)th residues. In order to account for the dependence on the distancek along the chain, the statistics are taken for three ranges, viz., short, medium, and long ranges (k8; 9k20; andk21; respectively). In the statistics of short-range distances, a mean distanceD _k and its standard deviationS _k are calculated for each value ofk, with and without taking into account the conformational states of all residues fromi toi+k (factors 1 and 3). As an Appendix, the relations for converting from the distances between residues into other conformational parameters are discussed. In the statistics of long-range distances, a reduced distanced* _ij (the actual distance divided by the radius of gyration) is used to scale the data so that they become independent of protein size, and then a mean reduced distanceD _l (a, a) and its standard deviation _l (a, a) are calculated for each amino acid pair (a, a) (factors 2 and 4). The effect of the neighboring residues along the chain on the value of the distanced* _ij is explored by a linear regression analysis between the actual reduced distanced* _ij and the mean value over theD _l for all possible pairs of residues in the two segments of the (i–2)th to the (i+2)th and the (j–2)th to the (j+2)th residues. The effect is assessed in terms of the tangentA _l (a, a) of the calculated regression line for each amino acid pair (a, a). In the statistics of medium-range distances, only factors 1 and 4 are considered, to simplify the analysis. The scaled distanced _i,i+k =(d _i,i+k -D _k )/S _k is used to eliminate the dependence onk, the distance along the chain. The propertiesD _m (a, a), _m (a, a) andA _m (a, a) corresponding toD _l (a, a), _l (a, a), andA _l (a, a), and also calculated for each amino acid pair (a, a). The results are interpreted as follows: the smaller values ofD _l (a, a) andD _m (a, a) indicate a preference of the pair (a, a) for a contact (e.g., pairs between hydrophobic amino acids, and pairs of Cys with aromatic amino acids), and the larger values of these quantities indicate a preference for distant mutual location (e.g., pairs between strong hydrophilic amino acids); the smaller values of _l (a, a) and _m (a, a) indicate a strong preference for either contact or noncontact (e.g., pairs between hydrophobic amino acids, and pairs between strong hydrophobic and hydrophilic amino acids, respectively), and the larger values of these quantities indicate the ambivalent/neutral nature of the preference for contact and noncontact (e.g., pairs containing Ser or Thr); the smaller values ofA _l (a, a) andA _m (a, a) indicate that the distance of an (a, a) pair is determined independently of the amino acid character of the neighboring residues along the chain (e.g., some pairs of Cys or Met with other amino acids) and the larger values of these quantities indicare that such amino acid character contributes strongly to the determination of the distance (e.g., pairs containing Ser or Thr, and pairs between amino acids with small side chains). The difference between the statistics for the long- and medium-range distances is also discussed; the former reflect the difference between the hydrophobic and hydrophilic character of the residues, but the latter cannot be easily interpretable only in terms of hydrophobicity and hydrophilicity. The data analyzed here are used in the optimization of an object function to compute protein conformation in a subsequent paper.     

Determination of network of residues that regulate allostery in protein families using sequence analysis

Allosteric interactions between residues that are spatially apart and well separated in sequence are important in the function of multimeric proteins as well as single-domain proteins. This observation suggests that, among the residues that are involved in long-range communications, mutation at one site should affect interactions at a distant site. By adopting a sequence-based approach, we present an automated approach that uses a generalization of the familiar sequence entropy in conjunction with a coupled two-way clustering algorithm, to predict the network of interactions that trigger allosteric interactions in proteins. We use the method to identify the subset of dynamically important residues in three families, namely, the small PDZ family, G protein-coupled receptors (GPCR), and the Lectins, which are cell-adhesion receptors that mediate the tethering and rolling of leukocytes on inflamed endothelium. For the PDZ and GPCR families, our procedure predicts, in agreement with previous studies, a network containing a small number of residues that are involved in their function. Application to the Lectin family reveals a network of residues interspersed throughout the C-terminal end of the structure that are responsible for binding to ligands. Based on our results and previous studies, we propose that functional robustness requires that only a small subset of distantly connected residues be involved in transmitting allosteric signals in proteins.     

The B domain of protein A retains residual structures in 6 M guanidinium chloride as revealed by hydrogen/deuterium‐exchange NMR spectroscopy

The characterization of residual structures persistent in unfolded proteins is an important issue in studies of protein folding, because the residual structures present, if any, may form a folding initiation site and guide the subsequent folding reactions. Here, we studied the residual structures of the isolated B domain (BDPA) of staphylococcal protein A in 6 M guanidinium chloride. BDPA is a small three‐helix‐bundle protein, and until recently its folding/unfolding reaction has been treated as a simple two‐state process between the native and the fully unfolded states. We employed a dimethylsulfoxide (DMSO)‐quenched hydrogen/deuterium (H/D)‐exchange 2D NMR techniques with the use of spin desalting columns, which allowed us to investigate the H/D‐exchange behavior of individually identified peptide amide (NH) protons. We obtained H/D‐exchange protection factors of the 21 NH protons that form an α‐helical hydrogen bond in the native structure, and the majority of these NH protons were significantly protected with a protection factor of 2.0–5.2 in 6 M guanidinium chloride, strongly suggesting that these weakly protected NH protons form much stronger hydrogen bonds under native folding conditions. The results can be used to deduce the structure of an early folding intermediate, when such an intermediate is shown by other methods. Among three native helical regions, the third helix in the C‐terminal side was highly protected and stabilized by side‐chain salt bridges, probably acting as the folding initiation site of BDPA. The present results are discussed in relation to previous experimental and computational findings on the folding mechanisms of BDPA.     

Description and recognition of regular and distorted secondary structures in proteins using the automated protein structure analysis method

The Automated Protein Structure Analysis (APSA) method, which describes the protein backbone as a smooth line in three‐dimensional space and characterizes it by curvature κ and torsion τ as a function of arc length s, was applied on 77 proteins to determine all secondary structural units via specific κ(s) and τ(s) patterns. A total of 533 α‐helices and 644 β‐strands were recognized by APSA, whereas DSSP gives 536 and 651 units, respectively. Kinks and distortions were quantified and the boundaries (entry and exit) of secondary structures were classified. Similarity between proteins can be easily quantified using APSA, as was demonstrated for the roll architecture of proteins ubiquitin and spinach ferridoxin. A twenty‐by‐twenty comparison of all α domains showed that the curvature‐torsion patterns generated by APSA provide an accurate and meaningful similarity measurement for secondary, super secondary, and tertiary protein structure. APSA is shown to accurately reflect the conformation of the backbone effectively reducing three‐dimensional structure information to two‐dimensional representations that are easy to interpret and understand. Proteins 2009. © 2008 Wiley‐Liss, Inc.     

On the satisfaction of backbone‐carbonyl lone pairs of electrons in protein structures

Protein structures are stabilized by a variety of noncovalent interactions (NCIs), including the hydrophobic effect, hydrogen bonds, electrostatic forces and van der Waals’ interactions. Our knowledge of the contributions of NCIs, and the interplay between them remains incomplete. This has implications for computational modeling of NCIs, and our ability to understand and predict protein structure, stability, and function. One consideration is the satisfaction of the full potential for NCIs made by backbone atoms. Most commonly, backbone‐carbonyl oxygen atoms located within α‐helices and β‐sheets are depicted as making a single hydrogen bond. However, there are two lone pairs of electrons to be satisfied for each of these atoms. To explore this, we used operational geometric definitions to generate an inventory of NCIs for backbone‐carbonyl oxygen atoms from a set of high‐resolution protein structures and associated molecular‐dynamics simulations in water. We included more‐recently appreciated, but weaker NCIs in our analysis, such as n→π* interactions, Cα‐H bonds and methyl‐H bonds. The data demonstrate balanced, dynamic systems for all proteins, with most backbone‐carbonyl oxygen atoms being satisfied by two NCIs most of the time. Combinations of NCIs made may correlate with secondary structure type, though in subtly different ways from traditional models of α‐ and β‐structure. In addition, we find examples of under‐ and over‐satisfied carbonyl‐oxygen atoms, and we identify both sequence‐dependent and sequence‐independent secondary‐structural motifs in which these reside. Our analysis provides a more‐detailed understanding of these contributors to protein structure and stability, which will be of use in protein modeling, engineering and design.     

Conformational analysis of peptides corresponding to all the secondary structure elements of protein L B1 domain: secondary structure propensities are not conserved in proteins with the same fold.

The solution conformation of three peptides corresponding to the two beta-hairpins and the alpha-helix of the protein L B1 domain have been analyzed by circular dichroism (CD) and nuclear magnetic resonance spectroscopy (NMR). In aqueous solution, the three peptides show low populations of native and non-native locally folded structures, but no well-defined hairpin or helix structures are formed. In 30% aqueous trifluoroethanol (TFE), the peptide corresponding to the alpha-helix adopts a high populated helical conformation three residues longer than in the protein. The hairpin peptides aggregate in TFE, and no significant conformational change occurs in the NMR observable fraction of molecules. These results indicate that the helical peptide has a significant intrinsic tendency to adopt its native structure and that the hairpin sequences seem to be selected as non-helical. This suggests that these sequences favor the structure finally attained in the protein, but the contribution of the local interactions alone is not enough to drive the formation of a detectable population of native secondary structures. This pattern of secondary structure tendencies is different to those observed in two structurally related proteins: ubiquitin and the protein G B1 domain. The only common feature is a certain propensity of the helical segments to form the native structure. These results indicate that for a protein to fold, there is no need for large native-like secondary structure propensities, although a minimum tendency to avoid non-native structures and to favor native ones could be required.     

Systematic analysis of residual density suggests that a major limitation in well‐refined X‐ray structures of proteins is the omission of ordered solvent

In the residual electron density map of a fully refined X‐ray protein model, there should be no peaks arising from modeling errors or missing atoms. Any residual peaks that do occur should be contributed by random residual intensity differences between the model and the data. If the model is incomplete (i.e., some atoms are missing), there will be more positive peaks than negative ones. On the other hand, if the model includes inappropriately located atoms, there will be an excess of negative peaks. In this study, random residual peaks are quantified using the probability density function P(x), which is defined as the probability for a peak having peak height between x and x + dx. It is found that P(x) is single‐exponential and symmetric for both positive and negative peaks. Thus, P(x) can be used to discriminate residual peaks contributed by random noise in complete models from residual peaks being attributable to modeling errors in incomplete models. For a number of representative structures in the PDB it is found that P(x) has far more large (greater than 5 sigma) positive peaks than large negative peaks. This excess of large positive peaks suggests that the main defect in these refined structures is the omission of ordered water molecules.     

Frequent side chain methyl carbon‐oxygen hydrogen bonding in proteins revealed by computational and stereochemical analysis of neutron structures

The propensity of backbone Cα atoms to engage in carbon‐oxygen (CH···O) hydrogen bonding is well‐appreciated in protein structure, but side chain CH···O hydrogen bonding remains largely uncharacterized. The extent to which side chain methyl groups in proteins participate in CH···O hydrogen bonding is examined through a survey of neutron crystal structures, quantum chemistry calculations, and molecular dynamics simulations. Using these approaches, methyl groups were observed to form stabilizing CH···O hydrogen bonds within protein structure that are maintained through protein dynamics and participate in correlated motion. Collectively, these findings illustrate that side chain methyl CH···O hydrogen bonding contributes to the energetics of protein structure and folding. Proteins 2015; 83:403–410. © 2014 Wiley Periodicals, Inc.