Hydrophobic‐hydrophilic forces in protein folding

The process of protein folding is obviously driven by forces exerted on the atoms of the amino‐acid chain. These forces arise from interactions with other parts of the protein itself (direct forces), as well as from interactions with the solvent (solvent‐induced forces). We present a statistical–mechanical formalism that describes both these direct and indirect, solvent‐induced thermodynamic forces on groups of the protein. We focus on 2 kinds of protein groups, commonly referred to as hydrophobic and hydrophilic. Analysis of this result leads to the conclusion that the forces on hydrophilic groups are in general stronger than on hydrophobic groups. This is then tested and verified by a series of molecular dynamics simulations, examining both hydrophobic alkanes of different sizes and hydrophilic moieties represented by polar‐neutral hydroxyl groups. The magnitude of the force on assemblies of hydrophilic groups is dependent on their relative orientation: with 2 to 4 times larger forces on groups that are able to form one or more direct hydrogen bonds.     

Investigation of the pH‐dependence of dye‐doped protein–protein interactions

Proteins can dramatically change their conformation under environmental conditions such as temperature and pH. In this context, Glycoprotein's conformational determination is challenging. This is due to the variety of domains which contain rich chemical characters existing within this complex. Here we demonstrate a new, straightforward and efficient technique that uses the pH‐dependent properties of dyes‐doped Pig Gastric Mucin (PGM) for predicting and controlling protein–protein interaction and conformation. We utilize the PGM as natural host matrix which is capable of dynamically changing its conformational shape and adsorbing hydrophobic and hydrophilic dyes under different pH conditions and investigate and control the fluorescent properties of these composites in solution. It is shown at various pH conditions, a large variety of light emission from these complexes such as red, green and white is obtained. This phenomenon is explained by pH‐dependent protein folding and protein–protein interactions that induce different emission spectra which are mediated and controlled by means of dye–dye interactions and surrounding environment. This process is used to form the technologically challenging white light‐emitting liquid or solid coating for LED devices.     

Novel protein folds and their nonsequential structural analogs

Newly determined protein structures are classified to belong to a new fold, if the structures are sufficiently dissimilar from all other so far known protein structures. To analyze structural similarities of proteins, structure alignment tools are used. We demonstrate that the usage of nonsequential structure alignment tools, which neglect the polypeptide chain connectivity, can yield structure alignments with significant similarities between proteins of known three-dimensional structure and newly determined protein structures that possess a new fold. The recently introduced protein structure alignment tool, GANGSTA, is specialized to perform nonsequential alignments with proper assignment of the secondary structure types by focusing on helices and strands only. In the new version, GANGSTA+, the underlying algorithms were completely redesigned, yielding enhanced quality of structure alignments, offering alignment against a larger database of protein structures, and being more efficient. We applied DaliLite, TM-align, and GANGSTA+ on three protein crystal structures considered to be novel folds. Applying GANGSTA+ to these novel folds, we find proteins in the ASTRAL40 database, which possess significant structural similarities, albeit the alignments are nonsequential and in some cases involve secondary structure elements aligned in reverse orientation. A web server is available at http://agknapp.chemie.fu-berlin.de/gplus for pairwise alignment, visualization, and database comparison.     

Hydrophobic folding units at protein-protein interfaces: implications to protein folding and to protein-protein association.

A hydrophobic folding unit cutting algorithm, originally developed for dissecting single-chain proteins, has been applied to a dataset of dissimilar two-chain protein-protein interfaces. Rather than consider each individual chain separately, the two-chain complex has been treated as a single chain. The two-chain parsing results presented in this work show hydrophobicity to be a critical attribute of two-state versus three-state protein-protein complexes. The hydrophobic folding units at the interfaces of two-state complexes suggest that the cooperative nature of the two-chain protein folding is the outcome of the hydrophobic effect, similar to its being the driving force in a single-chain folding. In analogy to the protein-folding process, the two-chain, two-state model complex may correspond to the formation of compact, hydrophobic nuclei. On the other hand, the three-state model complex involves binding of already folded monomers, similar to the association of the hydrophobic folding units within a single chain. The similarity between folding entities in protein cores and in two-state protein-protein interfaces, despite the absence of some chain connectivities in the latter, indicates that chain linkage does not necessarily affect the native conformation. This further substantiates the notion that tertiary, non-local interactions play a critical role in protein folding. These compact, hydrophobic, two-chain folding units, derived from structurally dissimilar protein-protein interfaces, provide a rich set of data useful in investigations of the role played by chain connectivity and by tertiary interactions in studies of binding and of folding. Since they are composed of non-contiguous pieces of protein backbones, they may also aid in defining folding nuclei.     

Statistical significance of hierarchical multi-body potentials based on Delaunay tessellation and their application in sequence-structure alignment.

Statistical potentials based on pairwise interactions between C alpha atoms are commonly used in protein threading/fold-recognition attempts. Inclusion of higher order interaction is a possible means of improving the specificity of these potentials. Delaunay tessellation of the C alpha-atom representation of protein structure has been suggested as a means of defining multi-body interactions. A large number of parameters are required to define all four-body interactions of 20 amino acid types (20(4) = 160,000). Assuming that residue order within a four-body contact is irrelevant reduces this to a manageable 8,855 parameters, using a nonredundant dataset of 608 protein structures. Three lines of evidence support the significance and utility of the four-body potential for sequence-structure matching. First, compared to the four-body model, all lower-order interaction models (three-body, two-body, one-body) are found statistically inadequate to explain the frequency distribution of residue contacts. Second, coherent patterns of interaction are seen in a graphic presentation of the four-body potential. Many patterns have plausible biophysical explanations and are consistent across sets of residues sharing certain properties (e.g., size, hydrophobicity, or charge). Third, the utility of the multi-body potential is tested on a test set of 12 same-length pairs of proteins of known structure for two protocols: Sequence-recognizes-structure, where a query sequence is threaded (without gap) through the native and a non-native structure; and structure-recognizes-sequence, where a query structure is threaded by its native and another non-native sequence. Using cross-validated training, protein sequences correctly recognized their native structure in all 24 cases. Conversely, structures recognized the native sequence in 23 of 24 cases. Further, the score differences between correct and decoy structures increased significantly using the three- or four-body potential compared to potentials of lower order.     

Distinguishing between sequential and nonsequentially folded proteins: implications for folding and misfolding.

We describe here an algorithm for distinguishing sequential from nonsequentially folding proteins. Several experiments have recently suggested that most of the proteins that are synthesized in the eukaryotic cell may fold sequentially. This proposed folding mechanism in vivo is particularly advantageous to the organism. In the absence of chaperones, the probability that a sequentially folding protein will misfold is reduced significantly. The problem we address here is devising a procedure that would differentiate between the two types of folding patterns. Footprints of sequential folding may be found in structures where consecutive fragments of the chain interact with each other. In such cases, the folding complexity may be viewed as being lower. On the other hand, higher folding complexity suggests that at least a portion of the polypeptide backbone folds back upon itself to form three-dimensional (3D) interactions with noncontiguous portion(s) of the chain. Hence, we look at the mechanism of folding of the molecule via analysis of its complexity, that is, through the 3D interactions formed by contiguous segments on the polypeptide chain. To computationally splice the structure into consecutively interacting fragments, we either cut it into compact hydrophobic folding units or into a set of hypothetical, transient, highly populated, contiguous fragments ("building blocks" of the structure). In sequential folding, successive building blocks interact with each other from the amino to the carboxy terminus of the polypeptide chain. Consequently, the results of the parsing differentiate between sequentially vs. nonsequentially folded chains. The automated assessment of the folding complexity provides insight into both the likelihood of misfolding and the kinetic folding rate of the given protein. In terms of the funnel free energy landscape theory, a protein that truly follows the mechanism of sequential folding, in principle, encounters smoother free energy barriers. A simple sequentially folded protein should, therefore, be less error prone and fold faster than a protein with a complex folding pattern.     

Hydrophobicity of amino acid subgroups in proteins

Protein folding studies often utilize areas and volumes to assess the hydrophobic contribution to conformational free energy (Richards, F.M. Annu. Rev. Biophys. Bioeng. 6:151-176, 1977). We have calculated the mean area buried upon folding for every chemical group in each residue within a set of X-ray elucidated proteins. These measurements, together with a standard state cavity size for each group, are documented in a table. It is observed that, on average, each type of group buries a constant fraction of its standard state area. The mean area buried by most, though not all, groups can be closely approximated by summing contributions from three characteristic parameters corresponding to three atom types: (1) carbon or sulfur, which turn out to be 86% buried, on average; (2) neutral oxygen or nitrogen, which are 40% buried, on average; and (3) charged oxygen or nitrogen, which are 32% buried, on average.     

Automatic recognition of hydrophobic clusters and their correlation with protein folding units.

A method is described to objectively identify hydrophobic clusters in proteins of known structure. Clusters are found by examining a protein for compact groupings of side chains. Compact clusters contain seven or more residues, have an average of 65% hydrophobic residues, and usually occur in protein interiors. Although smaller clusters contain only side-chain moieties, larger clusters enclose significant portions of the peptide backbone in regular secondary structure. These clusters agree well with hydrophobic regions assigned by more intuitive methods and many larger clusters correlate with protein domains. These results are in striking contrast with the clustering algorithm of J. Heringa and P. Argos (1991, J Mol Biol 220:151-171). That method finds that clusters located on a protein's surface are not especially hydrophobic and average only 3-4 residues in size. Hydrophobic clusters can be correlated with experimental evidence on early folding intermediates. This correlation is optimized when clusters with less than nine hydrophobic residues are removed from the data set. This suggests that hydrophobic clusters are important in the folding process only if they have enough hydrophobic residues.     

Circular permuted proteins in the universe of protein folds

Finding and identifying circular permuted protein pairs (CPP) is one of the harder tasks for structure alignment programs, because of the different location of the break in the polypeptide chain connectivity. The protein structure alignment tool GANGSTA+ was used to search for CPPs in a database of nearly 10,000 protein structures. It also allows determination of the statistical significance of the occurrence of circular permutations in the protein universe. The number of detected CPPs was found to be higher than expected, raising questions about the evolutionary processes leading to CPPs. The GANGSTA+ protein structure alignment tool is available online via the web server at http://gangsta.chemie.fu‐berlin.de . On the same webpage the complete data base of similar protein structure pairs based on the ASTRAL40 set of protein domains is provided and one can select CPPs specifically. Proteins 2010. © 2009 Wiley‐Liss, Inc.     

Distance geometry generates native-like folds for small helical proteins using the consensus distances of predicted protein structures.

For successful ab initio protein structure prediction, a method is needed to identify native-like structures from a set containing both native and non-native protein-like conformations. In this regard, the use of distance geometry has shown promise when accurate inter-residue distances are available. We describe a method by which distance geometry restraints are culled from sets of 500 protein-like conformations for four small helical proteins generated by the method of Simons et al. (1997). A consensus-based approach was applied in which every inter-Calpha distance was measured, and the most frequently occurring distances were used as input restraints for distance geometry. For each protein, a structure with lower coordinate root-mean-square (RMS) error than the mean of the original set was constructed; in three cases the topology of the fold resembled that of the native protein. When the fold sets were filtered for the best scoring conformations with respect to an all-atom knowledge-based scoring function, the remaining subset of 50 structures yielded restraints of higher accuracy. A second round of distance geometry using these restraints resulted in an average coordinate RMS error of 4.38 A.     

A desolvation barrier to hydrophobic cluster formation may contribute to the rate-limiting step in protein folding.

To gain insight into the free energy changes accompanying protein hydrophobic core formation, we have used computer simulations to study the formation of small clusters of nonpolar solutes in water. A barrier to association is observed at the largest solute separation that does not allow substantial solvent penetration. The barrier reflects an effective increase in the size of the cavity occupied by the expanded but water-excluding cluster relative to both the close-packed cluster and the fully solvated separated solutes; a similar effect may contribute to the barrier to protein folding/unfolding. Importantly for the simulation of protein folding without explicit solvent, we find that the interactions between nonpolar solutes of varying size and number can be approximated by a linear function of the molecular surface, but not the solvent-accessible surface of the solutes. Comparison of the free energy of cluster formation to that of dimer formation suggests that the assumption of pair additivity implicit in current protein database derived potentials may be in error.     

Detection and structure determination of an equilibrium unfolding intermediate of Rd-apocytochrome b562: native fold with non-native hydrophobic interactions

The absence of detectable kinetic and equilibrium folding intermediates by optical probes is commonly taken to indicate that protein folding is a two-state process. However, for some small proteins with apparent two-state behavior, unfolding intermediates have been identified in native-state hydrogen exchange or kinetic unfolding experiments monitored by nuclear magnetic resonance. Rd-apocytochrome b(562), a four-helix bundle, is one such protein. Here, we found another unfolding intermediate for Rd-apocytochrome b(562). It is based on a cooperative transition of (15)N chemical shifts of amide protons as a function of urea concentrations before the global unfolding. We have solved the high-resolution structure of the protein at 2.8 M urea, which is after this cooperative transition but before the global unfolding. All four helices remained intact, but a number of hydrophobic core residues repacked. This intermediate provides a possible structural interpretation for the kinetic unfolding intermediates observed using nuclear magnetic resonance methods for several proteins and has important implications for theoretical studies of protein folding.     

Mechanics and dynamics of B1 domain of protein G: role of packing and surface hydrophobic residues

The structural organization of the B1 domain of streptococcal protein G (PGA) has been probed using molecular dynamics simulations, with a particular emphasis on the role of the solvent exposed Ile6 residue. In addition to the native protein (WT-PGA), three single-mutants (I6G-PGA, I6F-PGA, and I6T-PGA), one double-mutant (I6T,T53G-PGA), and three isolated peptide fragments (corresponding to the helix and the two beta-hairpins) were studied in the presence of explicit water molecules. Comparative analysis of the various systems showed that the level of perturbation was directly related to the hydrophobicity and the size of the side chain of residue 6, the internal rigidity of the proteins decreasing in the order I6T-PGA > I6G-PGA > WT-PGA > I6F-PGA. The results emphasized the importance of residue 6 in controlling both the integrity of the sheet's surface and the orientation of the helix in relation to the sheet by modulation of surface/core interactions. The effects of mutations were delocalized across the structure, and glycine residues, in particular, absorbed most of the introduced strain. A qualitative structural decomposition of the native fold into elementary building-blocks was achieved using principal component analysis and mechanical response matrices. Within this framework, internal motions of the protein were described as coordinated articulations of these structural units, mutations affecting mostly the amplitude of the motions rather than the structure/location of the building-blocks. Analysis of the isolated peptidic fragments suggested that packing did not play a determinant role in defining the elementary building-blocks, but that chain topology was mostly responsible.     

Energetics of aliphatic deletions in protein cores

Although core residues can sometimes be replaced by shorter ones without introducing significant changes in protein structure, the energetic consequences are typically large and destabilizing. Many efforts have been devoted to understand and predict changes in stability from analysis of the environment of mutated residues, but the relationships proposed for individual proteins have often failed to describe additional data. We report here 17 apoflavodoxin large-to-small mutations that cause overall protein destabilizations of 0.6-3.9 kcal.mol(-1). By comparing two-state urea and three-state thermal unfolding data, the overall destabilizations observed are partitioned into effects on the N-to-I and on the I-to-U equilibria. In all cases, the equilibrium intermediate exerts a "buffering" effect that reduces the impact of the overall destabilization on the N-to-I equilibrium. The performance of several structure-energetics relationships, proposed to explain the energetics of hydrophobic shortening mutations, has been evaluated by using an apoflavodoxin data set consisting of 14 mutations involving branching-conservative aliphatic side-chain shortenings and a larger data set, including similar mutations implemented in seven model proteins. Our analysis shows that the stability changes observed for any of the different types of mutations (LA, IA, IV, and VA) in either data set are best explained by a combination of differential hydrophobicity and of the calculated volume of the modeled cavity (as previously observed for LA and IA mutations in lysozyme T4). In contrast, sequence conservation within the flavodoxin family, which is a good predictor for charge-reversal stabilizing mutations, does not perform so well for aliphatic shortening ones.     

Life at the border: Adaptation of proteins to anisotropic membrane environment

This review discusses main features of transmembrane (TM) proteins which distinguish them from water‐soluble proteins and allow their adaptation to the anisotropic membrane environment. We overview the structural limitations on membrane protein architecture, spatial arrangement of proteins in membranes and their intrinsic hydrophobic thickness, co‐translational and post‐translational folding and insertion into lipid bilayers, topogenesis, high propensity to form oligomers, and large‐scale conformational transitions during membrane insertion and transport function. Special attention is paid to the polarity of TM protein surfaces described by profiles of dipolarity/polarizability and hydrogen‐bonding capacity parameters that match polarity of the lipid environment. Analysis of distributions of Trp resides on surfaces of TM proteins from different biological membranes indicates that interfacial membrane regions with preferential accumulation of Trp indole rings correspond to the outer part of the lipid acyl chain region—between double bonds and carbonyl groups of lipids. These “midpolar” regions are not always symmetric in proteins from natural membranes. We also examined the hydrophobic effect that drives insertion of proteins into lipid bilayer and different free energy contributions to TM protein stability, including attractive van der Waals forces and hydrogen bonds, side‐chain conformational entropy, the hydrophobic mismatch, membrane deformations, and specific protein–lipid binding.     

VoroMQA: Assessment of protein structure quality using interatomic contact areas

In the absence of experimentally determined protein structure many biological questions can be addressed using computational structural models. However, the utility of protein structural models depends on their quality. Therefore, the estimation of the quality of predicted structures is an important problem. One of the approaches to this problem is the use of knowledge‐based statistical potentials. Such methods typically rely on the statistics of distances and angles of residue‐residue or atom‐atom interactions collected from experimentally determined structures. Here, we present VoroMQA (Voronoi tessellation‐based Model Quality Assessment), a new method for the estimation of protein structure quality. Our method combines the idea of statistical potentials with the use of interatomic contact areas instead of distances. Contact areas, derived using Voronoi tessellation of protein structure, are used to describe and seamlessly integrate both explicit interactions between protein atoms and implicit interactions of protein atoms with solvent. VoroMQA produces scores at atomic, residue, and global levels, all in the fixed range from 0 to 1. The method was tested on the CASP data and compared to several other single‐model quality assessment methods. VoroMQA showed strong performance in the recognition of the native structure and in the structural model selection tests, thus demonstrating the efficacy of interatomic contact areas in estimating protein structure quality. The software implementation of VoroMQA is freely available as a standalone application and as a web server at http://bioinformatics.lt/software/voromqa . Proteins 2017; 85:1131–1145. © 2017 Wiley Periodicals, Inc.     

Using physical features of protein core packing to distinguish real proteins from decoys

The ability to consistently distinguish real protein structures from computationally generated model decoys is not yet a solved problem. One route to distinguish real protein structures from decoys is to delineate the important physical features that specify a real protein. For example, it has long been appreciated that the hydrophobic cores of proteins contribute significantly to their stability. We used two sources to obtain datasets of decoys to compare with real protein structures: submissions to the biennial Critical Assessment of protein Structure Prediction competition, in which researchers attempt to predict the structure of a protein only knowing its amino acid sequence, and also decoys generated by 3DRobot, which have user‐specified global root‐mean‐squared deviations from experimentally determined structures. Our analysis revealed that both sets of decoys possess cores that do not recapitulate the key features that define real protein cores. In particular, the model structures appear more densely packed (because of energetically unfavorable atomic overlaps), contain too few residues in the core, and have improper distributions of hydrophobic residues throughout the structure. Based on these observations, we developed a feed‐forward neural network, which incorporates key physical features of protein cores, to predict how well a computational model recapitulates the real protein structure without knowledge of the structure of the target sequence. By identifying the important features of protein structure, our method is able to rank decoy structures with similar accuracy to that obtained by state‐of‐the‐art methods that incorporate many additional features. The small number of physical features makes our model interpretable, emphasizing the importance of protein packing and hydrophobicity in protein structure prediction.