180 Integrating structural and systems biology: structure-based prediction of protein–protein interactions on a genome-wide scale

The genome-wide identification of pairs of interacting proteins is an important step in the elucidation of cell regulatory mechanisms. To date, structural information has had only limited impact on genome-scale efforts to predict protein–protein interactions (PPIs). A new algorithm, PrePPI, will be introduced that combines structural information with nonstructural clues and that is comparable in accuracy to high-throughput experiments. The surprising effectiveness of three-dimensional structural information can be attributed to the use of homology models and the exploitation of both close and remote geometric relationships between proteins. More generally, the “structural BLAST” approach encapsulated in PrePPI significantly expands the range of application of protein structure in the annotation of protein function.     

An explantion for the determination of "self" versus "non-self" proteins

Deamidation of proteins, which has been linked to turnover, results in the production of a different protein—different in sequence and shape. It is proposed that this is the protein which is normally encountered by the immune system and is therefore viewed as “self”. If the protein in the form in which it exists in situ is released through disease, or introduced by artificial means, it would then be recognized as “non-self.” This is offered as a hypothesis to explain autoimmune response to the basic protein of myelin.     

Structurally Mapping Endogenous Heme in the CcmCDE Membrane Complex for Cytochrome c Biogenesis

Although many putative heme transporters have been discovered, it has been challenging to prove that these proteins are directly involved with heme trafficking in vivo and to identify their heme binding domains. The prokaryotic pathways for cytochrome c biogenesis, Systems I and II, transport heme from inside the cell to outside for stereochemical attachment to cytochrome c, making them excellent models to study heme trafficking. System I is composed of eight integral membrane proteins (CcmA–H) and is proposed to transport heme via CcmC to an external “WWD” domain for presentation to the membrane-tethered heme chaperone, CcmE. Herein, we develop a new cysteine/heme crosslinking approach to trap and map endogenous heme in CcmC (WWD domain) and CcmE (defining “2-vinyl” and “4-vinyl” pockets for heme). Crosslinking occurs when either of the two vinyl groups of heme localize near a thiol of an engineered cysteine residue. Double crosslinking, whereby both vinyls crosslink to two engineered cysteines, facilitated a more detailed structural mapping of the heme binding sites, including stereospecificity. Using heme crosslinking results, heme ligand identification, and genomic coevolution data, we model the structure of the CcmCDE complex, including the WWD heme binding domain. We conclude that CcmC trafficks heme via its WWD domain and propose the structural basis for stereochemical attachment of heme.     

Structural changes and fluctuations of proteins: I. A statistical thermodynamic model

A general theory of the structural changes and fluctuations of proteins has been proposed based on statistical thermodynanic considerations at the chain level.The “structure” of protein was assumed to be characterized by the state of secondary bonds between unique pairs of specific sites on peptide chains. Every secondary bond changes between the bonded and unboned states by thermal agitation and the “structure” is continuously fluctuating. The free energy of the “structural state” that is defined by the fraction of secondary bonds in the bonded state has been expressed by the bond energy, the cooperative interaction between bonds, the mixing entropy of bonds, and the entropy of polypeptide chains. The most probable “structural state” can be simply determined by graphical analysis and the effect of temperature or solvent composition on it is discussed. The temperature dependence of the free energy, the probability distribution of structural states and the specific heat have been calculated for two examples of structural change.The theory predicts two different types of structural changes from the ordered to disordered state, a “structural transition” and a “gradual structural change” with rising temperature, In the “structural transition”, the probability distribution has two maxima in the temperature range of transition. In the “gradual structural change”, the probability distribution has only one maximum during the change.A considerable fraction of secondary bonds is in the unbonded state and is always fluctuating even in the ordered state at room temperature. Such structural fluctuations in a single protein molecule have been discussed quantitatively.The theory is extended to include small molecules which bind to the protein molecule and affect the structural state. The changes of structural state caused by specific and non-specific binding and allosteric effects are explained in a unified manner.     

“Ensemble” iterative relaxation matrix approach: A new NMR refinement protocol applied to the solution structure of crambin

The structure in solution of crambin, a small protein of 46 residues, has been determined from 2D NMR data using an iterative relaxation matrix approach (IRMA) together with distance geometry, distance bound driven dynamics, molecular dynamics, and energy minimization. A new protocol based on an “ensemble” approach is proposed and compared to the more standard initial rate analysis approach and a “single structure” relaxation matrix approach. The effects of fast local motions are included and R-factor calculations are performed on NOE build-ups to describe the quality of agreement between theory and experiment. A new method for stereospecific assignment of prochiral groups, based on a comparison of theoretical and experimental NOE intensities, has been applied. The solution structure of crambin could be determined with a precision (rmsd from the average structure) of 0.7 Å on backbone atoms and 1.1 Å on all heavy atoms and is largely similar to the crystal structure with a small difference observed in the position of the side chain of Tyr-29 which is determined in solution by both J-coupling and NOE data. Regions of higher structural variability (suggesting higher mobility) are found hi the solution structure, in particular for the loop between the two helices (Gly-20 to Pro-22). © 1993 Wiley-Liss, Inc.     

Sequence Analysis and Comparative Bioinformatics Study of Camelysin Gene (<Emphasis Type="Italic">calY</Emphasis>) Isolated from <Emphasis Type="Italic">Bacillus thuringiensis</Emphasis>

Bacillus strains have been widely used for the production of fibrinolytic enzymes having role in the treatment of cardiovascular disorders. Purification and overproduction of such enzymes has increased their usage in medical fields including metalloproteinases with the ability to degrade extracellular matrix (ECM). Camelysin, a neutral metalloproteinase has been isolated from different species of bacteria like Bacillus cereus, Bacillus anthracis, and Bacillus thuringiensis with fibrinolytic, collagenolytic and actin degradation activity. This project successfully demonstrated the presence of 734-bp coding DNA sequence (CDS) encoding a 20.72331 kDa camelysin gene in local strain of Bacillus thuringiensis containing a signal peptide with cleavage site between residues 19 and 20. The sequence was submitted to GenBank (KT023597) and the sequence showed high homology with the camelysin protein of closely related Bacillus species. The alignment of related proteins through ClustalW displayed difference of four amino acids (“Q” replaced by “P” at position 169 and at position 182–184, “NQE” replaced by “HLK”) in the isolated protein. Comparison including structural and functional analysis of camelysin sequences isolated from different Bacillus species was carried out using different bioinformatics tools and software. The information would help in better understanding the properties of camelysin protein and its role in pathogenicity and clinical treatments.     

A proton nuclear magnetic resonance investigation of histine-binding protein J of salmonella typhimurium: A model for transport of L-histidine across cytoplasmic membrane

Genetic evidence suggests that the high-affinity L-histidine transport in Salmonella typhimurium requires the participation of a periplasmic binding protein (histidine-binding protein J) and two other proteins (P and Q proteins). The histidine-binding protein J binds L-histidine as the first step in the high-affinity active transport of this amino acid across the cytoplasmic membrane. High-resolution proton nuclear magnetic resonance spectroscopy at 600 MHz is used to investigate the conformations of this protein in the absence and presence of substrate. Previous nuclear magnetic resonance results reported by this laboratory have shown that there are extensive spectral changes in this protein upon the addition of L-histidine. When resonances from individual amino acid residues of a protein can be resolved in the proton nuclear magnetic resonance spectrum, a great deal of detailed information about substrate-induced structural changes can be obtained. In order to gain a deeper insight into the nature of these structural changes, deuterated phenylalanine or tyrosine has been incorporated into the bacteria. Proton nuclear magnetic resonance spectra of selectively deuterated histidine-binding protein J were obtained and compared to the normal protein. Several of the proton resonances have been assigned to the various aromatic amino acid residues of this protein. A model for the high-affinity transport of L-histidine across the cytoplasmic membrane of S typhimurium is proposed. This model, which is a version of the pore model, assumes that both P and Q proteins are membrane-bound and that the interface between these two proteins forms the channel for the passage of substrate. The histidine-binding protein J serves as the “key” for the opening of the channel for the passage of L-histidine. In the absence of substrate, this channel or gate is closed owing to a lack of appropriate interactions among these three proteins. The channel can be opened upon receiving a specific signal from the “key”; namely, the substrate-induced conformational changes in the histidine-binding protein J molecule. This model is consistent with available experimental evidence for the high-affinity transport of L-histidine across the cytoplasmic membrane of S typhimurium.     

Insights into a putative hinge region in elastin using molecular dynamics simulations

The resiliency and elasticity of vertebrate tissues are traced to elastin, a crosslinked protein with extensive hydrophobic regions. There is little discussion in the literature on the structure and dynamics of the alanine-rich crosslinking regions of elastin that comprise a significant part of the native protein. In particular, the region encoded by exons 21 and 23, a contiguous splice form found in all types of human elastin, is believed to be strategically positioned for proper function of the protein, namely, in the reversible elongation and contraction of tissue. Hence, molecular dynamics (MD) calculations on the EX21/23 domain are reported here. This crosslinking domain has been assumed to adopt an architecture in which the putative hinge region links two α-helices. In this paper, we use a homology-based approach to obtain starting structures in the hinge region. The subsequent MD brings new insights into the possibility of fluctuations between “open” and “closed” states, as well as distinguishing structural features of the latter. The significance of these findings towards an enhanced understanding of structure–function relationships in elastin and the elastic fiber is discussed.     

More than Just a Phase: Prions at the Crossroads of Epigenetic Inheritance and Evolutionary Change

A central tenet of molecular biology is that heritable information is stored in nucleic acids. However, this paradigm has been overturned by a group of proteins called “prions.” Prion proteins, many of which are intrinsically disordered, can adopt multiple conformations, at least one of which has the capacity to self-template. This unusual folding landscape drives a form of extreme epigenetic inheritance that can be stable through both mitotic and meiotic cell divisions. Although the first prion discovered—mammalian PrP—is the causative agent of debilitating neuropathies, many additional prions have now been identified that are not obviously detrimental and can even be adaptive. Intrinsically disordered regions, which endow proteins with the bulk property of “phase-separation,” can also be drivers of prion formation. Indeed, many protein domains that promote phase separation have been described as prion-like. In this review, we describe how prions lie at the crossroads of phase separation, epigenetic inheritance, and evolutionary adaptation.     

"Subunit-exchange" chromatography of proteins: behavior of alpha-chymotrypsin.

Protein subunits attached covalently to a solid matrix bind free subunits under conditions where an association-dissociation equilibrium exists in the soluble protein. This is the basis of a process which may be called “subunit-exchange chromatography”. The process, which may be applied to any self-associating protein, is exemplified here with α-chymotrypsin. The behavior of the system has been studied in detail especially with respect to the conditions of immobilization of the monomer. The results indicate the potentialities of the method for analytical and preparative purposes.     

Neural networks for secondary structure and structural class predictions

A pair of neural network-based algorithms is presented for predicting the tertiary structural class and the secondary structure of proteins. Each algorithm realizes improvements in accuracy based on information provided by the other. Structural class prediction of proteins nonhomologous to any in the training set is improved significantly, from 62.3% to 73.9%, and secondary structure prediction accuracy improves slightly, from 62.26% to 62.64%. A number of aspects of neural network optimization and testing are examined. They include network overtraining and an output filter based on a rolling average. Secondary structure prediction results vary greatly depending on the particular proteins chosen for the training and test sets; consequently, an appropriate measure of accuracy reflects the more unbiased approach of “jackknife” cross-validation (testing each protein in the database individually).     

Exploiting the Link between Protein Rigidity and Thermostability for Data‐Driven Protein Engineering

Understanding and exploiting the relationship between microscopic structure and macroscopic stability is important for developing strategies to improve protein stability at high temperatures. The thermostability of proteins has been repeatedly linked to an enhanced structural rigidity of the folded native state. In the current study, the rigidity of protein structures from mesophilic and thermophilic organisms along a thermal unfolding trajectory is directly probed. In order to perform this, protein structures were modeled as constraint networks, and the rigidity in these networks was quantified using the Floppy Inclusion and Rigid Substructure Topography (FIRST) method. During the thermal unfolding, a phase transition was observed that defines the rigidity percolation threshold and corresponds to the folded‐unfolded transition in protein folding. Using concepts from percolation theory and network science, a higher phase transition temperature was observed for ca. two‐thirds of the proteins from thermophilic organisms compared to their mesophilic counterparts, when applied to a data set of 20 pairs of homologues. From both the analysis of the microstructure of the constraint networks and monitoring the macroscopic behavior during the thermal unfolding, direct evidence was found for the “corresponding states” concept, which states that mesophilic and thermophilic enzymes are in corresponding states of similar flexibility at their respective optimal temperature. Finally, the current approach facilitated the identification of structural features from which a destabilization of the structure originates upon thermal unfolding. These predictions show a good agreement with the experimental data. Therefore, the information might be exploited in data‐driven protein engineering by pointing to residues that should be varied to obtain a protein with higher thermostability.     

A model of gradient interpretation based on morphogen binding

We propose a model in which pattern formation is controlled by several concentration gradients of “morphogens” and by allosteric proteins which bind them. In this model, each protein can bind up to two molecules of each morphogen and has an “active state” when one molecule of each morphogen is bound. The concentration of the active state of such a “morphogen binding protein” varies with position in a way that depends on the values given the binding constants. In a contour map of the active state concentration, the contours can have a variety of simple shapes.Simply-shaped regions of cell differentiation can be defined directly by concentration contours of a morphogen binding protein using a threshold-sensing mechanism. More complex shapes may be generated using several proteins and a “winner-take-all” rule according to which each protein specifies some particular sort of cell differentiation and the differentiation of cells in any position is governed by the protein with the highest active state concentration.We present an application of our model to the vertebrate limb skeleton; we use the “winner-take-all” mechanism and thirteen morphogen binding proteins, eleven of which specify cartilage formation. In this model we use one morphogen binding protein to specify the shaft of a typical long bone and one for each epiphysis. Our model is reasonably successful in imitating the in vivo positions and orientations of developing bones and in generating simple, plausible-looking articular surfaces.In addition to the morphogen-binding model we propose a mechanism which could transform morphogen-binding patterns into high-amplitude patterns capable of controlling the activity of structural genes. This “amplifying mechanism” can account for two previously unexplained features of limb skeletal development: the early formation of the diffusely-bounded “scleroblastema” in the limb bud and the center-to-edge gradations in cartilage formation rate which are later seen within individual chondrification foci.A simple modification of the morphogen-binding model provides an explanation for the general anatomical phenomenon of metamerism: The model can account for the formation of inexactly repeating patterns (such as the pattern of the vertebral column) and suggests a mechanism by which such patterns could (1) evolve from exactly repeating patterns, and (2) acquire, in further evolution, a high degree of specialization of the individual repeating units.The most promising approach for testing the morphogen-binding model would appear to involve experiments in which cytoplasm is transferred between cells at various stages of pattern development. Support for the model could also come from the discovery of certain kinds of hereditary limb defects.     

PyXlinkViewer: A flexible tool for visualization of protein chemical crosslinking data within the PyMOL molecular graphics system

Chemical crosslinking‐mass spectrometry (XL‐MS) is a valuable technique for gaining insights into protein structure and the organization of macromolecular complexes. XL‐MS data yield inter‐residue restraints that can be compared with high‐resolution structural data. Distances greater than the crosslinker spacer‐arm can reveal lowly populated “excited” states of proteins/protein assemblies, or crosslinks can be used as restraints to generate structural models in the absence of structural data. Despite increasing uptake of XL‐MS, there are few tools to enable rapid and facile mapping of XL‐MS data onto high‐resolution structures or structural models. PyXlinkViewer is a user‐friendly plugin for PyMOL v2 that maps intra‐protein, inter‐protein, and dead‐end crosslinks onto protein structures/models and automates the calculation of inter‐residue distances for the detected crosslinks. This enables rapid visualization of XL‐MS data, assessment of whether a set of detected crosslinks is congruent with structural data, and easy production of high‐quality images for publication.     

Photoaffinity labeling combined with mass spectrometric approaches as a tool for structural proteomics

Protein chemistry, such as crosslinking and photoaffinity labeling, in combination with modern mass spectrometric techniques, can provide information regarding protein–protein interactions beyond that normally obtained from protein identification and characterization studies. While protein crosslinking can make tertiary and quaternary protein structure information available, photoaffinity labeling can be used to obtain structural data about ligand–protein interaction sites, such as oligonucleotide–protein, drug–protein and protein–protein interaction. In this article, we describe mass spectrometry-based photoaffinity labeling methodologies currently used and discuss their current limitations. We also discuss their potential as a common approach to structural proteomics for providing 3D information regarding the binding region, which ultimately will be used for molecular modeling and structure-based drug design.     

An electrophoretic method for the purification of RNA regions involved in protein crosslinking.

Direct information about structural interactions in ribonucleoprotein complexes can be obtained from crosslinking data. The purification of specific complexes, i.e., their separation from noncrosslinked proteins, from free RNA, and from other complexes, is essential for the identification of the bound proteins and the precise localization of their attachment sites in RNA. We describe a two-dimensional denaturing gel system which achieves this purification; in the first dimension basic proteins do not enter the gel and RNA--protein complexes are slowed down compared to protein free RNA, and in the second dimension sodium dodecyl sulfate improves the separation between the different complexes on the basis of their protein content.     

Photoaffinity labeling combined with mass spectrometric approaches as a tool for structural proteomics

Protein chemistry, such as crosslinking and photoaffinity labeling, in combination with modern mass spectrometric techniques, can provide information regarding protein-protein interactions beyond that normally obtained from protein identification and characterization studies. While protein crosslinking can make tertiary and quaternary protein structure information available, photoaffinity labeling can be used to obtain structural data about ligand-protein interaction sites, such as oligonucleotide-protein, drug-protein and protein-protein interaction. In this article, we describe mass spectrometry-based photoaffinity labeling methodologies currently used and discuss their current limitations. We also discuss their potential as a common approach to structural proteomics for providing 3D information regarding the binding region, which ultimately will be used for molecular modeling and structure-based drug design.     

Recent advances in exploiting ionic liquids for biomolecules: Solubility,stability and applications

The technological utility of biomolecules (e.g. proteins, enzymes and DNA) can be significantly enhanced by combining them with ionic liquids (ILs) – potentially attractive ”green“ and ”designer“ solvents – rather than using in conventional organic solvents or water. In recent years, ILs have been used as solvents, cosolvents, and reagents for biocatalysis, biotransformation, protein preservation and stabilization, DNA solubilization and stabilization, and other biomolecule‐based applications. Using ILs can dramatically enhance the structural and chemical stability of proteins, DNA, and enzymes. This article reviews the recent technological developments of ILs in protein‐, enzyme‐, and DNA‐based applications. We discuss the different routes to increase biomolecule stability and activity in ILs, and the design of biomolecule‐friendly ILs that can dissolve biomolecules with minimum alteration to their structure. This information will be helpful to design IL‐based processes in biotechnology and the biological sciences that can serve as novel and selective processes for enzymatic reactions, protein and DNA stability, and other biomolecule‐based applications.     

Annexin A2/P11 interaction: new insights into annexin A2 tetramer structure by chemical crosslinking, high-resolution mass spectrometry, and computational modeling

During the past few years, the structural analysis of proteins and protein complexes by chemical crosslinking and mass spectrometry has enjoyed increasing popularity. With this approach we have investigated the quaternary structure of the complex between annexin A2 and p11, which is involved in numerous cellular processes. Although high-resolution data are available for both interaction partners as well as for the complex between two p11 subunits and two annexin A2 N-terminal peptides, the structure of the complete annexin A2/p11 heterotetramer has not yet been solved at high resolution. Thus, the quaternary structure of the biologically relevant, membrane-bound annexin A2/p11 complex is still under discussion, while the existence of a heterotetramer or a heterooctamer is the prevailing opinion. We gained further insight into the spatial organization of the annexin A2/p11 heterotetramer by employing chemical crosslinking combined with high-resolution mass spectrometry. Furthermore, tandem mass spectrometry served as a tool for an exact localization of crosslinked amino acid residues and for a confirmation of crosslinked product assignment. On the basis of distance constraints from the crosslinking data we derived structural models of the annexin A2/p11 heterotetramer by computational docking with Rosetta. We propose an octameric model for the annexin A2/p11 complex, which exerts annexin A2 function. The proposed structure of the annexin A2/p11 octamer differs from so far suggested models and sheds new light into annexin A2/p11 interaction.