Comparison of protein fragments identified by limited proteolysis and by computational cutting of proteins

Determinants of Macromolecular Specificity from Proteomics-Derived Peptide Substrate Data

BACKGROUND

Recent advances in proteomics methodologies allow for high throughput profiling of proteolytic cleavage events. The resulting substrate peptide distributions provide deep insights in the underlying macromolecular recognition events, as determinants of biomolecular specificity identified by proteomics approaches may be compared to structure-based analysis of corresponding protein-protein interfaces.

METHOD

Here, we present an overview of experimental and computational methodologies and tools applied in the area and provide an outlook beyond the protein class of proteases.

RESULTS AND CONCLUSION

We discuss here future potential, synergies and needs of the emerging overlap disciplines of proteomics and structure-based modelling.

Multiple Docking for Protein Structure Prediction

Protein structure prediction and protein docking prediction are two related problems in molecular biology. We suggest the use of multiple docking in the process of protein structure prediction. Once reliable structural models are predicted to disjoint fragments of the protein target sequence, a combinatorial assembly may be used to predict their native arrangement. Here, we present CombDock, a combinatorial docking algorithm for the structural units assembly problem. We have tested the algorithm on various examples using both domains and domain substructures as input. Inaccurate models of the structural units were also used, to test the robustness of the algorithm. The algorithm was able to predict a near-native arrangement of the input structural units in almost all of the cases, showing that the combinatorial approach succeeds in overcoming the inexact shape complementarity caused by the inaccuracy of the models.

Biophysical characterization of the outer membrane polysaccharide export protein and the polysaccharide co-polymerase protein from Xanthomonas campestris

This study investigated the structural and biophysical characteristics of GumB and GumC, two Xanthomonas campestris membrane proteins that are involved in xanthan biosynthesis. Xanthan is an exopolysaccharide that is thought to be a virulence factor that contributes to bacterial in planta growth. It also is one of the most important industrial biopolymers. The first steps of xanthan biosynthesis are well understood, but the polymerization and export mechanisms remain unclear. For this reason, the key proteins must be characterized to better understand these processes. Here we characterized, by biochemical and biophysical techniques, GumB, the outer membrane polysaccharide export protein, and GumC, the polysaccharide co-polymerase protein of the xanthan biosynthesis system. Our results suggested that recombinant GumB is a tetrameric protein in solution. On the other hand, we observed that both native and recombinant GumC present oligomeric conformation consistent with dimers and higher-order oligomers. The transmembrane segments of GumC are required for GumC expression and/or stability. These initial results provide a starting point for additional studies that will clarify the roles of GumB and GumC in the xanthan polymerization and export processes and further elucidate their functions and mechanisms of action.

Getting intimate with trypsin, the leading protease in proteomics

Nowadays, mass spectrometry-based proteomics is carried out primarily in a bottom-up fashion, with peptides obtained after proteolytic digest of a whole proteome lysate as the primary analytes instead of the proteins themselves. This experimental setup crucially relies on a protease to digest an abundant and complex protein mixture into a far more complex peptide mixture. Full knowledge of the working mechanism and specificity of the used proteases is therefore crucial, both for the digestion step itself as well as for the downstream identification and quantification of the (fragmentation) mass spectra acquired for the peptides in the mixture. Targeted protein analysis through selected reaction monitoring, a relative newcomer in the specific field of mass spectrometry-based proteomics, even requires a priori understanding of protease behavior for the proteins of interest. Because of the rapidly increasing popularity of proteomics as an analytical tool in the life sciences, there is now a renewed demand for detailed knowledge on trypsin, the workhorse protease in proteomics. This review addresses this need and provides an overview on the structure and working mechanism of trypsin, followed by a critical analysis of its cleavage behavior, typically simply accepted to occur exclusively yet consistently after Arg and Lys, unless they are followed by a Pro. In this context, shortcomings in our ability to understand and predict the behavior of trypsin will be highlighted, along with the downstream implications. Furthermore, an analysis is carried out on the inherent shortcomings of trypsin with regard to whole proteome analysis, and alternative approaches will be presented that can alleviate these issues. Finally, some reflections on the future of trypsin as the workhorse protease in mass spectrometry-based proteomics will be provided.

A modular perspective of protein structures: application to fragment based loop modeling

Proteins can be decomposed into supersecondary structure modules. We used a generic definition of supersecondary structure elements, so-called Smotifs, which are composed of two flanking regular secondary structures connected by a loop, to explore the evolution and current variety of structure building blocks. Here, we discuss recent observations about the saturation of Smotif geometries in protein structures and how it opens new avenues in protein structure modeling and design. As a first application of these observations we describe our loop conformation modeling algorithm, ArchPred that takes advantage of Smotifs classification. In this application, instead of focusing on specific loop properties the method narrows down possible template conformations in other, often not homologous structures, by identifying the most likely supersecondary structure environment that cradles the loop. Beyond identifying the correct starting supersecondary structure geometry, it takes into account information of fit of anchor residues, sterical clashes, match of predicted and observed dihedral angle preferences, and local sequence signal.

Differential stabilities of alternative exon-skipped rod motifs of dystrophin

Exon skipping repair is a strategy being investigated in early stage clinical trials to treat Duchenne muscular dystrophy. This is most applicable to the majority of cases which arise when genetic defects cause frame shift mutations, and induced exon skipping of out-of-phase exons restores the reading frame. However, the consequences to the edited protein so produced have not been considered. In many cases alternative routes to restoring the reading frame are possible, and we show in a test case involving exon 44 that the resulting differently edited proteins greatly vary in stability, with one of them very similar to normal unskipped dystrophin, and the other much less stable as assessed by the thermodynamics of folding as well as resistance to proteolysis. This has implications for the design of optimal therapeutic exon skipping strategies, which presumably wish to result repairs with as much fidelity to normal dystrophin as possible.

An unusual intrinsically disordered protein from the model legume Lotus japonicus stabilizes proteins in vitro

Intrinsic structural disorder is a prevalent feature of proteins with chaperone activity. Using a complementary set of techniques, we have structurally characterized LjIDP1 (intrinsically disordered protein 1) from the model legume Lotus japonicus, and our results provide the first structural characterization of a member of the Lea5 protein family (PF03242). Contrary to in silico predictions, we show that LjIDP1 is intrinsically disordered and probably exists as an ensemble of conformations with limited residual beta-sheet, turn/loop, and polyproline II secondary structure. Furthermore, we show that LjIDP1 has an inherent propensity to undergo a large conformational shift, adopting a largely alpha-helical structure when it is dehydrated and in the presence of different detergents and alcohols. This is consistent with an overrepresentation of order-promoting residues in LjIDP1 compared with the average of intrinsically disordered proteins. In line with functioning as a chaperone, we show that LjIDP1 effectively prevents inactivation of two model enzymes under conditions that promote protein misfolding and aggregation. The LjIdp1 gene is expressed in all L. japonicus tissues tested. A higher expression level was found in the root tip proximal zone, in roots inoculated with compatible endosymbiotic M. loti, and in functional nitrogen-fixing root nodules. We suggest that the ability of LjIDP1 to prevent protein misfolding and aggregation may play a significant role in tissues, such as symbiotic root nodules, which are characterized by high metabolic activity.

Functionally important segments in proteins dissected using Gene Ontology and geometric clustering of peptide fragments

A geometric clustering algorithm has been developed to dissect protein fragments based on their relevance to function.

We have developed a geometric clustering algorithm using backbone φ,ψ angles to group conformationally similar peptide fragments of any length. By labeling each fragment in the cluster with the level-specific Gene Ontology 'molecular function' term of its protein, we are able to compute statistics for molecular function-propensity and p-value of individual fragments in the cluster. Clustering-cum-statistical analysis for peptide fragments 8 residues in length and with only trans peptide bonds shows that molecular function propensities ≥20 and p-values ≤0.05 can dissect fragments within a protein linked to the molecular function.

Operational definition of intrinsically unstructured protein sequences based on susceptibility to the 20S proteasome

Intrinsically unstructured proteins (IUPs), also known as natively unfolded proteins, lack well-defined secondary and tertiary structure under physiological conditions. In recent years, growing experimental and theoretical evidence has accumulated, indicating that many entire proteins and protein sequences are unstructured under physiological conditions, and that they play significant roles in diverse cellular processes. Bioinformatic algorithms have been developed to identify such sequences in proteins for which structural data are lacking, but still generate substantial numbers of false positives and negatives. We describe here a simple and reliable in vitro assay for identifying IUP sequences based on their susceptibility to 20S proteasomal degradation. We show that 20S proteasomes digest IUP sequences, under conditions in which native, and even molten globule states, are resistant. Furthermore, we show that protein-protein interactions can protect IUPs against 20S proteasomal action. Taken together, our results thus suggest that the 20S proteasome degradation assay provides a powerful system for operational definition of IUPs.

Maturation efficiency, trypsin sensitivity, and optical properties of Arg96, Glu222, and Gly67 variants of green fluorescent protein

Spontaneous chromophore biosynthesis in green fluorescent protein (GFP) is initiated by a main-chain cyclization reaction catalyzed by the protein fold. To investigate the structural prerequisites for chromophore formation, we have substituted the conserved residues Arg96, Glu222, and Gly67. Upon purification, the variants can be ordered based on their decreasing extent of chromophore maturation according to the series EGFP, E222Q, R96K, G67A, and R96M. Arg96 and Glu222 appear to play catalytic roles, whereas Gly67 is likely important in interior packing to enforce correct hydrogen bonding to Arg96. The effect of Arg96 can be partially compensated for by a lysine, but not by a methionine residue, confirming its electrophilic role. Limited trypsinolysis data suggest that protein stability is largely unaffected by the presence of the chromophore, inconsistent with the mechanical compression hypothesis. Trends in optical properties may be related to the degree of chromophore charge delocalization, which is modulated by residue 96.

p25alpha is flexible but natively folded and binds tubulin with oligomeric stoichiometry

p25alpha is a 219-residue protein which stimulates aberrant tubulin polymerization and is implicated in a variety of other functions. The protein has unusual secondary structure involving significant amounts of random coil, and binding to microtubules is accompanied by a large structural change, suggesting a high degree of plasticity. p25alpha has been proposed to be natively unfolded, so that folding is coupled to interaction with its physiological partners. Here we show that recombinant human p25alpha is folded under physiological conditions, since it has a well structured and solvent-sequestered aromatic environment and considerable chemical shift dispersion of amide and aliphatic protons. With increasing urea concentrations, p25alpha undergoes clear spectral changes suggesting significant loss of structure. p25alpha unfolds cooperatively in urea according to a simple two-state transition with a stability in water of approximately 5 kcal/mol. The protein behaves as a monomer and refolds with a transient on-pathway folding intermediate. However, high sensitivity to proteolytic attack and abnormal gel filtration migration behavior suggests a relatively extended structure, possibly organized in distinct domains. A deletion mutant of p25alpha lacking residues 3-43 also unfolds cooperatively and with similar stability, suggesting that the N-terminal region is largely unstructured. Both proteins undergo significant loss of structure when bound to monomeric tubulin. The stoichiometry of binding is estimated to be 3-4 molecules of tubulin per p25alpha and is not significantly affected by the deletion of residues 3-43. In conclusion, we dismiss the proposal that p25alpha is natively unfolded, although the protein is relatively flexible. This flexibility may be linked to its tubulin-binding properties.

Recent developments in structural proteomics for protein structure determination

The major challenges in structural proteomics include identifying all the proteins on the genome-wide scale, determining their structure-function relationships, and outlining the precise three-dimensional structures of the proteins. Protein structures are typically determined by experimental approaches such as X-ray crystallography or nuclear magnetic resonance (NMR) spectroscopy. However, the knowledge of three-dimensional space by these techniques is still limited. Thus, computational methods such as comparative and de novo approaches and molecular dynamic simulations are intensively used as alternative tools to predict the three-dimensional structures and dynamic behavior of proteins. This review summarizes recent developments in structural proteomics for protein structure determination; including instrumental methods such as X-ray crystallography and NMR spectroscopy, and computational methods such as comparative and de novo structure prediction and molecular dynamics simulations.

Combining prediction, computation and experiment for the characterization of protein disorder

Several computational and experimental methods exist for identifying disordered residues within proteins. Computational algorithms can now identify these disordered sequences and predict their occurrence within genomes with relatively high accuracy. Recent advances in NMR and mass spectroscopy permit faster and more detailed studies of disordered states at atomic resolutions. Combining prediction, computation and experimentation is proposed to accelerate and enhance the characterization of intrinsically disordered protein.

In silico protein design by combinatorial assembly of protein building blocks

Utilizing concepts of protein building blocks, we propose a de novo computational algorithm that is similar to combinatorial shuffling experiments. Our goal is to engineer new naturally occurring folds with low homology to existing proteins. A selected protein is first partitioned into its building blocks based on their compactness, degree of isolation from the rest of the structure, and hydrophobicity. Next, the protein building blocks are substituted by fragments taken from other proteins with overall low sequence identity, but with a similar hydrophobic/hydrophilic pattern and a high structural similarity. These criteria ensure that the designed protein has a similar fold, low sequence identity, and a good hydrophobic core compared with its native counterpart. Here, we have selected two proteins for engineering, protein G B1 domain and ubiquitin. The two engineered proteins share approximately 20% and approximately 25% amino acid sequence identities with their native counterparts, respectively. The stabilities of the engineered proteins are tested by explicit water molecular dynamics simulations. The algorithm implements a strategy of designing a protein using relatively stable fragments, with a high population time. Here, we have selected the fragments by searching for local minima along the polypeptide chain using the protein building block model. Such an approach provides a new method for engineering new proteins with similar folds and low homology.

Potential folding-function interrelationship in proteins

The possibility is addressed that protein folding and function may be related via regions that are critical for both folding and function. This approach is based on the building blocks folding model that describes protein folding as binding events of conformationally fluctuating building blocks. Within these, we identify building block fragments that are critical for achieving the native fold. A library of such critical building blocks (CBBs) is constructed. Then, it is asked whether the functionally important residues fall in these CBB fragments. We find that for over two-thirds of the proteins in our library with available functional information, the catalytic or binding site residues lie within the CBB regions. From the evolutionary standpoint, a folding-function relationship is advantageous, since the need to guard against mutations is limited to one region. Furthermore, conformationally similar CBBs are found in globally unrelated proteins with different functions. Hence, substituting CBBs may lead to designed proteins with altered functions. We further find that the CBBs in our library are conformationally unstable.

Small-world communication of residues and significance for protein dynamics

It is not merely the position of residues that is critically important for a protein's function and stability, but also their interactions. We illustrate, by using a network construction on a set of 595 nonhomologous proteins, that regular packing is preserved in short-range interactions, but short average path lengths are achieved through some long-range contacts. Thus, lying between the two extremes of regularity and randomness, residues in folded proteins are distributed according to a "small-world" topology. Using this topology, we show that the core residues have the same local packing arrangements irrespective of protein size. Furthermore, we find that the average shortest path lengths are highly correlated with residue fluctuations, providing a link between the spatial arrangement of the residues and protein dynamics.

Towards realistic description of collective motions in the lattice protein folding models

Collective motions and the formation of clusters of residues play an important role in the folding of real proteins. However, existing Monte Carlo (MC) techniques of the protein folding simulations based on highly popular lattice models provide only a schematic representation of collective motions, which is rather far from physical reality. The Clustering Monte Carlo (CMC) algorithm was developed with particular aim to provide a realistic description of collective motions on the lattice. CMC allows modeling the cluster dynamics and the effects of the solvent viscosity, which is impossible in conventional algorithms. In this study two 2D lattice peptides, with the ground states of hierarchical and non-hierarchical design, were investigated comparatively using three methods: Metropolis MC with the local move set, Metropolis MC with unspecific rigid rotations and the CMC algorithm. We present evidence that the folding pathways and kinetics of hierarchically folding clustered sequence are not adequately described in conventional MC simulations, and the account for cluster dynamics provided by CMC allows to capture essential features of the folding process. Our data suggest that the methods, which enable specific cluster motions, such as CMC, should be used for a more realistic description of protein folding.

Reducing the computational complexity of protein folding via fragment folding and assembly

Understanding, and ultimately predicting, how a 1-D protein chain reaches its native 3-D fold has been one of the most challenging problems during the last few decades. Data increasingly indicate that protein folding is a hierarchical process. Hence, the question arises as to whether we can use the hierarchical concept to reduce the practically intractable computational times. For such a scheme to work, the first step is to cut the protein sequence into fragments that form local minima on the polypeptide chain. The conformations of such fragments in solution are likely to be similar to those when the fragments are embedded in the native fold, although alternate conformations may be favored during the mutual stabilization in the combinatorial assembly process. Two elements are needed for such cutting: (1) a library of (clustered) fragments derived from known protein structures and (2) an assignment algorithm that selects optimal combinations to "cover" the protein sequence. The next two steps in hierarchical folding schemes, not addressed here, are the combinatorial assembly of the fragments and finally, optimization of the obtained conformations. Here, we address the first step in a hierarchical protein-folding scheme. The input is a target protein sequence and a library of fragments created by clustering building blocks that were generated by cutting all protein structures. The output is a set of cutout fragments. We briefly outline a graph theoretic algorithm that automatically assigns building blocks to the target sequence, and we describe a sample of the results we have obtained.

Hierarchical protein folding pathways: a computational study of protein fragments

We have previously presented a building block folding model. The model postulates that protein folding is a hierarchical top-down process. The basic unit from which a fold is constructed, referred to as a hydrophobic folding unit, is the outcome of combinatorial assembly of a set of "building blocks." Results obtained by the computational cutting procedure yield fragments that are in agreement with those obtained experimentally by limited proteolysis. Here we show that as expected, proteins from the same family give very similar building blocks. However, different proteins can also give building blocks that are similar in structure. In such cases the building blocks differ in sequence, stability, contacts with other building blocks, and in their 3D locations in the protein structure. This result, which we have repeatedly observed in many cases, leads us to conclude that while a building block is influenced by its environment, nevertheless, it can be viewed as a stand-alone unit. For small-sized building blocks existing in multiple conformations, interactions with sister building blocks in the protein will increase the population time of the native conformer. With this conclusion in hand, it is possible to develop an algorithm that predicts the building block assignment of a protein sequence whose structure is unknown. Toward this goal, we have created sequentially nonredundant databases of building block sequences. A protein sequence can be aligned against these, in order to be matched to a set of potential building blocks.