Arrangement Of Secondary Structure Elements Research Articles

The Multiscale Ernwin/SPQR RNA Structure Prediction Pipeline.

Aside from the well-known role in protein synthesis, RNA can perform catalytic, regulatory, and other essential biological functions which are determined by its three-dimensional structure. In this regard, a great effort has been made during the past decade to develop computational tools for the prediction of the structure of RNAs from the knowledge of their sequence, incorporating experimental data to refine or guide the modeling process. Nevertheless, this task can become exceptionally challenging when dealing with long noncoding RNAs, constituted by more than 200 nucleotides, due to their large size and the specific interactions involved. In this chapter, we describe a multiscale approach to predict such structures, incorporating SAXS experimental data into a hierarchical procedure which couples two coarse-grained representations: Ernwin, a helix-based approach, which deals with the global arrangement of secondary structure elements, and SPQR, a nucleotide-centered coarse-grained model, which corrects and refines the structures predicted at the coarser level.We describe the methodology through its application on the Braveheart long noncoding RNA, starting from the SAXS and secondary structure data to propose a refined, all-atom structure.

Target classification in the 14th round of the critical assessment of protein structure prediction (CASP14).

An evolutionary-based definition and classification of target evaluation units (EUs) is presented for the 14th round of the critical assessment of structure prediction (CASP14). CASP14 targets included 84 experimental models submitted by various structural groups (designated T1024-T1101). Targets were split into EUs based on the domain organization of available templates and performance of server groups. Several targets required splitting (19 out of 25 multidomain targets) due in part to observed conformation changes. All in all, 96 CASP14 EUs were defined and assigned to tertiary structure assessment categories (Topology-based FM or High Accuracy-based TBM-easy and TBM-hard) considering their evolutionary relationship to existing ECOD fold space: 24 family level, 50 distant homologs (H-group), 12 analogs (X-group), and 10 new folds. Principal component analysis and heatmap visualization of sequence and structure similarity to known templates as well as performance of servers highlighted trends in CASP14 target difficulty. The assigned evolutionary levels (i.e., H-groups) and assessment classes (i.e., FM) displayed overlapping clusters of EUs. Many viral targets diverged considerably from their template homologs and thus were more difficult for prediction than other homology-related targets. On the other hand, some targets did not have sequence-identifiable templates, but were predicted better than expected due to relatively simple arrangements of secondary structural elements. An apparent improvement in overall server performance in CASP14 further complicated traditional classification, which ultimately assigned EUs into high-accuracy modeling (27 TBM-easy and 31 TBM-hard), topology (23 FM), or both (15 FM/TBM).

2DProts: database of family-wide protein secondary structure diagrams.

SummarySecondary structures provide a deep insight into the protein architecture. They can serve for comparison between individual protein family members. The most straightforward way how to deal with protein secondary structure is its visualization using 2D diagrams. Several software tools for the generation of 2D diagrams were developed. Unfortunately, they create 2D diagrams based on only a single protein. Therefore, 2D diagrams of two proteins from one family markedly differ. For this reason, we developed the 2DProts database, which contains secondary structure 2D diagrams for all domains from the CATH and all proteins from PDB databases. These 2D diagrams are generated based on a whole protein family, and they also consider information about the 3D arrangement of secondary structure elements. Moreover, 2DProts database contains multiple 2D diagrams, which provide an overview of a whole protein family's secondary structures. 2DProts is updated weekly and is integrated into CATH.Availability and ImplementationFreely accessible at https://2dprots.ncbr.muni.cz. The web interface was implemented in JavaScript. The database was implemented in Python.Supplementary information Supplementary data are available at Bioinformatics online.

Difference contact maps: From what to why in the analysis of the conformational flexibility of proteins.

Protein structures, usually visualized in various highly idealized forms focusing on the three-dimensional arrangements of secondary structure elements, can also be described as lists of interacting residues or atoms and visualized as two-dimensional distance or contact maps. We show that contact maps provide an ideal tool to describe and analyze differences between structures of proteins in different conformations. Expanding functionality of the PDBFlex server and database developed previously in our group, we describe how analysis of difference contact maps (DCMs) can be used to identify critical interactions stabilizing alternative protein conformations, recognize residues and positions controlling protein functions and build hypotheses as to molecular mechanisms of disease mutations.

Structure of the full-length Serratia marcescens acetyltransferase AAC(3)-Ia in complex with coenzyme A.

Acyl-coenzyme A-dependent N-acetyltransferases (AACs) catalyze the modification of aminoglycosides rendering the bacteria carrying such enzymes resistant to this class of antibiotics. Here we present the crystal structure of AAC(3)-Ia enzyme from Serratia marcescens in complex with coenzyme A determined to 1.8 Å resolution. This enzyme served as an architype for the AAC enzymes targeting the amino group at Position 3 of aminoglycoside main aminocyclitol ring. The structure of this enzyme has been previously determined only in truncated form and was interpreted as distinct from subsequently characterized AACs. The reason for the unusual arrangement of secondary structure elements of AAC(3)-Ia was not further investigated. By determining the full-length structure of AAC(3)-Ia we establish that this enzyme adopts the canonical AAC fold conserved across this family and it does not undergo through significant rearrangement of secondary structure elements upon ligand binding as was proposed previously. In addition, our results suggest that the C-terminal tail in AAC(3)-Ia monomer forms intramolecular hydrogen bonds that contributes to formation of stable dimer, representing the predominant oligomeric state for this enzyme.

Energy Landscape of the Designed Protein Top7.

To fold on biologically relevant time scales, proteins have evolved funnelled energy landscapes with minimal energetic trapping. However, the polymeric nature of proteins and the spatial arrangement of secondary structural elements can create topological traps and slow folding. It is challenging to identify, visualize, and quantify such topological trapping. Designed proteins have not had the benefit of evolution, and it has been hypothesized that de novo designed protein topologies may therefore feature more topological trapping. Structure-based models (SBMs) are inherently funnelled, removing most energetic trapping, and can thus be used to isolate the effect of protein topology on the landscape. Here, we compare Top7, a designed protein with a topology unknown in nature, to S6, a naturally occurring ribosomal protein of similar size and topology. Possible kinetic traps and the energetic barriers separating them from the native state are elucidated. We find that, even with an SBM, the potential energy landscape (PEL) of the designed protein is more frustrated than that of the natural protein. We then quantify the effect of adding non-native hydrophobic interactions and coarse-grained side-chains through a frustration density parameter. A clear increase in frustration is observed including side-chains, whereas adding hydrophobic interactions leads to a narrowing of the funnel and a decrease in complexity. The most likely (un)folding routes for all models are derived through the construction of probability contact maps. The ability to quantitatively understand and optimize the organization of the PEL for designed proteins may enable us to design structure-seeking landscapes, mimicking the effect of evolution.

Rules for connectivity of secondary structure elements in protein: Two-layer αβ sandwiches.

In protein structures, the fold is described according to the spatial arrangement of secondary structure elements (SSEs: α-helices and β-strands) and their connectivity. The connectivity or the pattern of links among SSEs is one of the most important factors for understanding the variety of protein folds. In this study, we introduced the connectivity strings that encode the connectivities by using the types, positions, and connections of SSEs, and computationally enumerated all the connectivities of two-layer αβ sandwiches. The calculated connectivities were compared with those in natural proteins determined using MICAN, a nonsequential structure comparison method. For 2α-4β, among 23,000 of all connectivities, only 48 were free from irregular connectivities such as loop crossing. Of these, only 20 were found in natural proteins and the superfamilies were biased toward certain types of connectivities. A similar disproportional distribution was confirmed for most of other spatial arrangements of SSEs in the two-layer αβ sandwiches. We found two connectivity rules that explain the bias well: the abundances of interlayer connecting loops that bridge SSEs in the distinct layers; and nonlocal β-strand pairs, two spatially adjacent β-strands located at discontinuous positions in the amino acid sequence. A two-dimensional plot of these two properties indicated that the two connectivity rules are not independent, which may be interpreted as a rule for the cooperativity of proteins.

Fluorescence Evidences for Non-Homogeneity and Residual Structure of Denatured States

About 30 % of human proteins do not fold into a stable 3D arrangement of secondary structure elements, but stay predominantly unfolded -similar to proteins under highly denaturing conditions. These proteins are involved in many cell signaling processes. Their characterization poses a great challenge for current experimental methods as they consist of an ensemble of rapidly interconverting conformations. Intense debate exists on the possibility that they show, to certain extent, residual structure, which might facilitate folding or enhance ligand binding. To study the unfolded state conformational heterogeneity using Forster resonance energy transfer (FRET), we used the lysozyme from the phage T4 (T4L) in denaturing conditions as a model system. We built an elastic network model that spans T4L's topology in order to evaluate local and global conformational changes by combining ensemble (ensemble time-resolved fluorescence lifetime and anisotropy) and single-molecule spectroscopic (multiparameter fluorescence detection, photon distribution analysis, (filtered) fluorescence correlation spectroscopy) methods. Through extensive comparison of models, we identified regions with apparent residual structure under highly denaturing conditions, which might serve as folding nuclei; and additionally we showed that chemically denatured T4L is not a random coil as previously thought. By using obtained distance restraints we determined that denatured T4L shows a native-like mean structure, albeit larger in size compared to the native state. We demonstrate here the necessity of careful data interpretation, but also the potential of a multidimensional approach to characterize an ensemble of states, which can be applied generally to unstructured or denatured proteins.

The Intrinsic Pepsin Resistance of Interleukin-8 Can Be Explained from a Combined Bioinformatical and Experimental Approach.

Interleukin-8 (IL-8, CXCL8) is a neutrophil chemotactic factor belonging to the family of chemokines. IL-8 was shown to resist pepsin cleavage displaying its high resistance to this protease. However, the molecular mechanisms underlying this resistance are not fully understood. Using our in-house database containing the data on three-dimensional arrangements of secondary structure elements from the whole Protein Data Bank, we found a striking structural similarity between IL-8 and pepsin inhibitor-3. Such similarity could play a key role in understanding IL-8 resistance to the protease pepsin. To support this hypothesis, we applied pepsin assays confirming that intact IL-8 is not degraded by pepsin in comparison to IL-8 in a denaturated state. Applying 1H-15N Heteronuclear Single Quantum Coherence NMR measurements, we determined the putative regions at IL-8 that are potentially responsible for interactions with the pepsin. The results obtained in this work contribute to the understanding of the resistance of IL-8 to pepsin proteolysis in terms of its structural properties.

Force-dependent switch in protein unfolding pathways and transition-state movements.

Although it is known that single-domain proteins fold and unfold by parallel pathways, demonstration of this expectation has been difficult to establish in experiments. Unfolding rate, [Formula: see text], as a function of force f, obtained in single-molecule pulling experiments on src SH3 domain, exhibits upward curvature on a [Formula: see text] plot. Similar observations were reported for other proteins for the unfolding rate [Formula: see text]. These findings imply unfolding in these single-domain proteins involves a switch in the pathway as f or [Formula: see text] is increased from a low to a high value. We provide a unified theory demonstrating that if [Formula: see text] as a function of a perturbation (f or [Formula: see text]) exhibits upward curvature then the underlying energy landscape must be strongly multidimensional. Using molecular simulations we provide a structural basis for the switch in the pathways and dramatic shifts in the transition-state ensemble (TSE) in src SH3 domain as f is increased. We show that a single-point mutation shifts the upward curvature in [Formula: see text] to a lower force, thus establishing the malleability of the underlying folding landscape. Our theory, applicable to any perturbation that affects the free energy of the protein linearly, readily explains movement in the TSE in a β-sandwich (I27) protein and single-chain monellin as the denaturant concentration is varied. We predict that in the force range accessible in laser optical tweezer experiments there should be a switch in the unfolding pathways in I27 or its mutants.

Efficient and automated large-scale detection of structural relationships in proteins with a flexible aligner.

BackgroundThe total number of known three-dimensional protein structures is rapidly increasing. Consequently, the need for fast structural search against complete databases without a significant loss of accuracy is increasingly demanding. Recently, TopSearch, an ultra-fast method for finding rigid structural relationships between a query structure and the complete Protein Data Bank (PDB), at the multi-chain level, has been released. However, comparable accurate flexible structural aligners to perform efficient whole database searches of multi-domain proteins are not yet available. The availability of such a tool is critical for a sustainable boosting of biological discovery.ResultsHere we report on the development of a new method for the fast and flexible comparison of protein structure chains. The method relies on the calculation of 2D matrices containing a description of the three-dimensional arrangement of secondary structure elements (angles and distances). The comparison involves the matching of an ensemble of substructures through a nested-two-steps dynamic programming algorithm. The unique features of this new approach are the integration and trade-off balancing of the following: 1) speed, 2) accuracy and 3) global and semiglobal flexible structure alignment by integration of local substructure matching. The comparison, and matching with competitive accuracy, of one medium sized (250-aa) query structure against the complete PDB database (216,322 protein chains) takes about 8 min using an average desktop computer. The method is at least 2–3 orders of magnitude faster than other tested tools with similar accuracy. We validate the performance of the method for fold and superfamily assignment in a large benchmark set of protein structures. We finally provide a series of examples to illustrate the usefulness of this method and its application in biological discovery.ConclusionsThe method is able to detect partial structure matching, rigid body shifts, conformational changes and tolerates substantial structural variation arising from insertions, deletions and sequence divergence, as well as structural convergence of unrelated proteins.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-015-0866-8) contains supplementary material, which is available to authorized users.

How a Spatial Arrangement of Secondary Structure Elements Is Dispersed in the Universe of Protein Folds

It has been known that topologically different proteins of the same class sometimes share the same spatial arrangement of secondary structure elements (SSEs). However, the frequency by which topologically different structures share the same spatial arrangement of SSEs is unclear. It is important to estimate this frequency because it provides both a deeper understanding of the geometry of protein folds and a valuable suggestion for predicting protein structures with novel folds. Here we clarified the frequency with which protein folds share the same SSE packing arrangement with other folds, the types of spatial arrangement of SSEs that are frequently observed across different folds, and the diversity of protein folds that share the same spatial arrangement of SSEs with a given fold, using a protein structure alignment program MICAN, which we have been developing. By performing comprehensive structural comparison of SCOP fold representatives, we found that approximately 80% of protein folds share the same spatial arrangement of SSEs with other folds. We also observed that many protein pairs that share the same spatial arrangement of SSEs belong to the different classes, often with an opposing N- to C-terminal direction of the polypeptide chain. The most frequently observed spatial arrangement of SSEs was the 2-layer α/β packing arrangement and it was dispersed among as many as 27% of SCOP fold representatives. These results suggest that the same spatial arrangements of SSEs are adopted by a wide variety of different folds and that the spatial arrangement of SSEs is highly robust against the N- to C-terminal direction of the polypeptide chain.

Progress towards structural understanding of infectious sheep PrP-amyloid

The still elusive structural difference of non-infectious and infectious amyloid of the mammalian prion protein (PrP) is a major pending milestone in understanding protein-mediated infectivity in neurodegenerative diseases. Preparations of PrP-amyloid proven to be infectious have never been investigated with a high-resolution technique. All available models to date have been based on low-resolution data. Here, we establish protocols for the preparation of infectious samples of full-length recombinant (rec) PrP-amyloid in NMR-sufficient amounts by spontaneous fibrillation and seeded fibril growth from brain extract. We link biological and structural data of infectious recPrP-amyloid, derived from bioassays, atomic force microscopy, and solid-state NMR spectroscopy. Our data indicate a semi-mobile N‑terminus, some residues with secondary chemical shifts typical of α‑helical secondary structure in the middle part between ∼115 to ∼155, and a distinct β‑sheet core C‑terminal of residue ∼155. These findings are not in agreement with all current models for PrP-amyloid. We also provide evidence that samples seeded from brain extract may not differ in the overall arrangement of secondary structure elements, but rather in the flexibility of protein segments outside the β-core region. Taken together, our protocols provide an essential basis for the high-resolution characterization of non-infectious and infectious PrP-amyloid in the near future.

Exploring protein domain organization by recognition of secondary structure packing interfaces.

Protein domains are fundamental units of protein structure, function and evolution; thus, it is critical to gain a deep understanding of protein domain organization. Previous works have attempted to identify key residues involved in organization of domain architecture. Because one of the most important characteristics of domain architecture is the arrangement of secondary structure elements (SSEs), here we present a picture of domain organization through an integrated consideration of SSE arrangements and residue contact networks. In this work, by representing SSEs as main-chain scaffolds and side-chain interfaces and through construction of residue contact networks, we have identified the SSE interfaces well packed within protein domains as SSE packing clusters. In total, 17 334 SSE packing clusters were recognized from 9015 Structural Classification of Proteins domains of <40% sequence identity. The similar SSE packing clusters were observed not only among domains of the same folds, but also among domains of different folds, indicating their roles as common scaffolds for organization of protein domains. Further analysis of 14 small single-domain proteins reveals a high correlation between the SSE packing clusters and the folding nuclei. Consistent with their important roles in domain organization, SSE packing clusters were found to be more conserved than other regions within the same proteins. Supplementary data are available at Bioinformatics online.

More than a rigid framework: molecular design using secondary structure element information

The structure-based design of small molecule modulators of protein-ligand binding and protein-protein interaction is a key component in drug discovery. The underlying protein interactions can be regarded based on structural similarity of the involved secondary structure elements [1]. The most prominent example is the protein fold of a protein domain that is more conserved than the amino acid sequence and proteins with similar fold but dissimilar sequence and function can bind similar ligands. Similar ligand binding can also occur between different proteins that have a similar spatial arrangement of secondary structure elements around the ligand binding site (ligand-sensing cores) independent from the overall fold [2]. Analogous to this, similar protein-protein interfaces can occur within different protein folds showing different function, since the structural space of protein interfaces is degenerated and is represented by roughly 1000 distinct interfaces [3]. These similarities in otherwise unrelated proteins can be useful in the design of protein function modulators. The successful applications in molecular design described in literature using predicted polypharmacology in protein-ligand binding will be shown and the analogy in the design of protein-protein interaction inhibitors and the potential of polypharmacology prediction will be discussed.

Protein Kinase Inhibitors for Clinical Targeted Cancer Treatment

Protein kinases are defined by their ability to catalyse the transfer of the terminal phosphate of ATP to substrates that usually contain a serine, threonine or tyrosine residue. They typically share a conserved arrangement of secondary structure elements that are arranged into 12 sub domains that fold into a bi-lobed catalytic core structure with ATP binding in a deep cleft located between the lobes. ATP binds in the cleft with the adenine ring forming hydrogen bonds with the kinase ‘hinge’ the segment that connects the aminoand carboxyterminal kinase domains. The highly conserved DFG-motif position in A-loop along with catalytic Lys from β3 strand usually determines kinase activity. Deregulation of protein kinase activities, particularly dominant kinase mutations (such as BRAF V600E in A-loop, and JAK2 V617F in the auto-inhibitory pseudokinase domain), may result in a number of conditions such as cancer, inflammatory or infectious diseases, diabetes, degenerative nerve diseases, and cardiovascular disorders. There are 518 protein kinases and about 20 lipid-modifying kinases encoded by the human genome [1,2], and a much larger proportion of additional kinases are present in parasite, bacterial, fungal, and viral genomes that are susceptible to exploitation as drug targets. Cancer is global leading causes of death which is responsible for about 25% of all deaths and features with 0.5% annual diagnostic rate. The National Institutes of Health (NIH) estimates that the overall costs of cancer in 2007 were $226.8 billion.

BCL::Score—Knowledge Based Energy Potentials for Ranking Protein Models Represented by Idealized Secondary Structure Elements

The topology of most experimentally determined protein domains is defined by the relative arrangement of secondary structure elements, i.e. α-helices and β-strands, which make up 50–70% of the sequence. Pairing of β-strands defines the topology of β-sheets. The packing of side chains between α-helices and β-sheets defines the majority of the protein core. Often, limited experimental datasets restrain the position of secondary structure elements while lacking detail with respect to loop or side chain conformation. At the same time the regular structure and reduced flexibility of secondary structure elements make these interactions more predictable when compared to flexible loops and side chains. To determine the topology of the protein in such settings, we introduce a tailored knowledge-based energy function that evaluates arrangement of secondary structure elements only. Based on the amino acid Cβ atom coordinates within secondary structure elements, potentials for amino acid pair distance, amino acid environment, secondary structure element packing, β-strand pairing, loop length, radius of gyration, contact order and secondary structure prediction agreement are defined. Separate penalty functions exclude conformations with clashes between amino acids or secondary structure elements and loops that cannot be closed. Each individual term discriminates for native-like protein structures. The composite potential significantly enriches for native-like models in three different databases of 10,000–12,000 protein models in 80–94% of the cases. The corresponding application, “BCL::ScoreProtein,” is available at www.meilerlab.org.

EM-Fold: De Novo Atomic-Detail Protein Structure Determination from Medium-Resolution Density Maps

Electron density maps of membrane proteins or large macromolecular complexes are frequently only determined at medium resolution between 4Å and 10Å, either by cryo-electron microscopy or X-ray crystallography. In these density maps, the general arrangement of secondary structure elements (SSEs) is revealed, whereas their directionality and connectivity remain elusive. We demonstrate that the topology of proteins with up to 250 amino acids can be determined from such density maps when combined with a computational protein folding protocol. Furthermore, we accurately reconstruct atomic detail in loop regions and amino acid side chains not visible in the experimental data. The EM-Fold algorithm assembles the SSEs de novo before atomic detail is added using Rosetta. In a benchmark of 27 proteins, the protocol consistently and reproducibly achieves models with root mean square deviation values <3Å.

Exploring symmetry as an avenue to the computational design of large protein domains.

It has been demonstrated previously that symmetric, homodimeric proteins are energetically favored, which explains their abundance in nature. It has been proposed that such symmetric homodimers underwent gene duplication and fusion to evolve into protein topologies that have a symmetric arrangement of secondary structure elements--"symmetric superfolds". Here, the ROSETTA protein design software was used to computationally engineer a perfectly symmetric variant of imidazole glycerol phosphate synthase and its corresponding symmetric homodimer. The new protein, termed FLR, adopts the symmetric (βα)(8) TIM-barrel superfold. The protein is soluble and monomeric and exhibits two-fold symmetry not only in the arrangement of secondary structure elements but also in sequence and at atomic detail, as verified by crystallography. When cut in half, FLR dimerizes readily to form the symmetric homodimer. The successful computational design of FLR demonstrates progress in our understanding of the underlying principles of protein stability and presents an attractive strategy for the in silico construction of larger protein domains from smaller pieces.

Impact of initial solvent on thermal stability and mechanical properties of recombinant spider silk films

Spider silk fibers are one of the most remarkable biopolymers displaying a unique combination of mechanical properties, biocompatibility and biodegradability. The recombinant production of spider silk proteins now allows the processing of silk proteins into novel materials with the aim of future applications. Here, we analyzed films made of a recombinantly produced, engineered spider silk protein with a sequence derived from the dragline silk protein ADF4 of the European garden spider Araneus diadematus. An influence of different initial solvents (aqueous buffer, hexafluoro-2-propanol and formic acid) on certain film properties was identified in as cast as well as methanol post-treated films: while no significant effects on the films' thermal stability were observed, a significant influence on their mechanical properties could be shown. Interestingly, solvent-induced effects were sustained after methanol post-treatment and could be correlated with the presence and arrangement of secondary structure elements. Insights into molecular orientation of individual structural elements within the films upon applied load were revealed by combined polarized IR spectroscopy and mechanical measurements.