Protein Structural Topology Research Articles

A unique approach for protein secondary structure comparison under TOPS representation

To unravel the intricate connection between protein function and protein structure, it is imperative to comprehensively evaluate protein secondary structure similarity from various perspectives. While numerous techniques have been suggested for comparing protein secondary structure elements (SSE), there continues to be a substantial need for finding alternative ways of comparing the same. In this paper, Topology of Protein Structure (TOPS) representations of protein secondary structures are considered to offer a new alignment-free method for evaluating similarities/dissimilarities of protein secondary structures. Initially, a two-dimensional numerical representation of the SSE is created, associating each point with a mass reflecting its frequency of occurrence. Then the means of coordinate values are determined by averaging weighted sums, and these mean values are subsequently used to calculate moments-of-inertia. Next, a four-component descriptor is generated out of the eigenvalues of the matrix and the mean values of the represented coordinates. Thereafter, Manhattan distance measure is used to obtain the distance matrix. This is finally applied to obtain the phylogenetic trees under the use of NJ method. SSE considered in the proposed method comprises 36-elements from the Chew-Kedem database giving five different taxa: globin, alpha-beta, tim-barrel, beta, and alpha. Phylogenetic trees were created for these SSE through the application of various methods: Clustal-Omega, LZ-Complexity, SED, TOPS + and TOC, to facilitate comparative analysis. Phylogenetic tree of the proposed method outperformed results of the previous methods when applied to the same SSE. Therefore, the method effectively constructs phylogenetic tree for analyzing protein secondary structure comparison. Communicated by Ramaswamy H. Sarma

A bifunctional spin label reports the structural topology of phospholamban in magnetically-aligned bicelles

We have applied a bifunctional spin label and EPR spectroscopy to determine membrane protein structural topology in magnetically-aligned bicelles, using monomeric phospholamban (PLB) as a model system. Bicelles are a powerful tool for studying membrane proteins by NMR and EPR spectroscopies, where magnetic alignment yields topological constraints by resolving the anisotropic spectral properties of nuclear and electron spins. However, EPR bicelle studies are often hindered by the rotational mobility of monofunctional Cys-linked spin labels, which obscures their orientation relative to the protein backbone. The rigid and stereospecific TOAC label provides high orientational sensitivity but must be introduced via solid-phase peptide synthesis, precluding its use in large proteins. Here we show that a bifunctional methanethiosulfonate spin label attaches rigidly and stereospecifically to Cys residues at i and i+4 positions along PLB’s transmembrane helix, thus providing orientational resolution similar to that of TOAC, while being applicable to larger membrane proteins for which synthesis is impractical. Computational modeling and comparison with NMR data shows that these EPR experiments provide accurate information about helix tilt relative to the membrane normal, thus establishing a robust method for determining structural topology in large membrane proteins with a substantial advantage in sensitivity over NMR.

Solid-state NMR (31)P paramagnetic relaxation enhancement membrane protein immersion depth measurements.

Paramagnetic relaxation enhancement (PRE) is a widely used approach for measuring long-range distance constraints in biomolecular solution NMR spectroscopy. In this paper, we show that 31P PRE solid-state NMR spectroscopy can be utilized to determine the immersion depth of spin-labeled membrane peptides and proteins. Changes in the 31P NMR PRE times coupled with modeling studies can be used to describe the spin-label position/amino acid within the lipid bilayer and the corresponding helical tilt. This method provides valuable insight on protein–lipid interactions and membrane protein structural topology. Solid-state 31P NMR data on the 23 amino acid α-helical nicotinic acetylcholine receptor nAChR M2δ transmembrane domain model peptide followed predicted behavior of 31P PRE rates of the phospholipid headgroup as the spin-label moves from the membrane surface toward the center of the membrane. Residue 11 showed the smallest changes in 31P PRE (center of the membrane), while residue 22 shows the largest 31P PRE change (near the membrane surface), when compared to the diamagnetic control M2δ sample. This PRE SS-NMR technique can be used as a molecular ruler to measure membrane immersion depth.

A New Method to Analyze the Similarity of Protein Structure Using TOPS Representations

As a coarse level description of protein structure, TOPS (Topology of protein structure) diagrams are simplified descriptions of structural topology of proteins and comprise graphical representations of SSEs. In this paper, we propose a new method to analyze the similarities/dissimilarities of protein structure of TOPS representations based on the graphical representation proposed by C. X. Yuan et al. (2003). Instead of calculating the leading eigenvalues of the matrix for graphical representation, we compute torsion of curves as the descriptor to numerically characterize TOPS strings. Using the new method, TOPS strings of the 34 protein chains in the Chew-Kedem data set are analyzed. The similarities/dissimilarities and phylogenetic tree of these protein structures verify the validity of our method.

Comparison of TOPS strings based on LZ complexity

Topology of protein structure (TOPS) cartoons are simplified descriptions of structural topology of proteins in 2D. This is coarse level description of protein structure. The comparison of protein structures is very important for the study of protein functions, and for the analysis of possible evolutionary relationships. In this paper, we use LZ algorithm to compare TOPS strings.

A simple topological representation of protein structure: implications for new, fast, and robust structural classification.

A topological representation of proteins is developed that makes use of two metrics: the Euclidean metric for identifying natural nearest neighboring residues via the Delaunay tessellation in Cartesian space and the distance between residues in sequence space. Using this representation, we introduce a quantitative and computationally inexpensive method for the comparison of protein structural topology. The method ultimately results in a numerical score quantifying the distance between proteins in a heuristically defined topological space. The properties of this scoring scheme are investigated and correlated with the standard Calpha distance root-mean-square deviation measure of protein similarity calculated by rigid body structural alignment. The topological comparison method is shown to have a characteristic dependence on protein conformational differences and secondary structure. This distinctive behavior is also observed in the comparison of proteins within families of structural relatives. The ability of the comparison method to successfully classify proteins into classes, superfamilies, folds, and families that are consistent with standard classification methods, both automated and human-driven, is demonstrated. Furthermore, it is shown that the scoring method allows for a fine-grained classification on the family, protein, and species level that agrees very well with currently established phylogenetic hierarchies. This fine classification is achieved without requiring visual inspection of proteins, sequence analysis, or the use of structural superimposition methods. Implications of the method for a fast, automated, topological hierarchical classification of proteins are discussed.

MSAT

This article describes the development of a new method for multiple sequence alignment based on fold-level protein structure alignments, which provides an improvement in accuracy compared with the most commonly used sequence-only-based techniques. This method integrates the widely used, progressive multiple sequence alignment approach ClustalW with the Topology of Protein Structure (TOPS) topology-based alignment algorithm. The TOPS approach produces a structural alignment for the input protein set by using a topology-based pattern discovery program, providing a set of matched sequence regions that can be used to guide a sequence alignment using ClustalW. The resulting alignments are more reliable than a sequence-only alignment, as determined by 20-fold cross-validation with a set of 106 protein examples from the CATH database, distributed in seven superfold families. The method is particularly effective for sets of proteins that have similar structures at the fold level but low sequence identity. The aim of this research is to contribute towards bridging the gap between protein sequence and structure analysis, in the hope that this can be used to assist the understanding of the relationship between sequence, structure and function. The tool is available at http://balabio.dcs.gla.ac.uk/msat/.

TOPS: an enhanced database of protein structural topology.

The TOPS database holds topological descriptions of protein structures. These compact and highly abstract descriptions reduce the protein fold to a sequence of Secondary Structure Elements (SSEs) and three sets of pairwise relationships between them, hydrogen bonds relating parallel and anti- parallel beta strands, spatial adjacencies relating neighbouring SSEs, and the chiralities of selected supersecondary structures, including connections in betaalphabeta units and between parallel alpha helices. The database is used as a resource for visualizing folding topologies, fast topological pattern searching and structure comparison. Here, significant enhancements to the TOPS database are described. The topological description has been enhanced to include packing relationships between helices, which significantly improves the description of protein folds with little beta strand content. Further, the topological description has been annotated with sequence information. The query interfaces to the database have been improved and the new version can be found at http://www.tops.leeds.ac.uk/.

Protein structural topology: Automated analysis and diagrammatic representation.

The topology of a protein structure is a highly simplified description of its fold including only the sequence of secondary structure elements, and their relative spatial positions and approximate orientations. This information can be embodied in a two-dimensional diagram of protein topology, called a TOPS cartoon. These cartoons are useful for the understanding of particular folds and making comparisons between folds. Here we describe a new algorithm for the production of TOPS cartoons, which is more robust than those previously available, and has a much higher success rate. This algorithm has been used to produce a database of protein topology cartoons that covers most of the data bank of known protein structures.