QSCOP--SCOP quantified by structural relationships

Comparative analysis of the mitochondrial proteins reveals complex structural and functional relationships in Fasciola species

Mitochondria is a cellular source of energy, appears to play an essential role in dealing with cellular stress induced by environmental stimuli. The genetic diversity of mitochondrial genes involved in oxidative phosphorylation affecting the production of cellular energy and regional adaptation to various ecological (climatic) pressures affecting amino acid sequences (variants of protein). However, little is known about the combined effect of protein changes on cell-level metabolic alterations in simultaneous exposure to various environmental conditions, including mitochondrial dysfunction and oxidative stress induction. The present study was designed to address this issue by analyzing the mitochondrial proteins in Fasciola species including Cytochrome oxidase (COX1, COX2, COX3, and CYTB) and NADH dehydrogenase (ND1, ND2, ND3, ND4, ND5, and ND6). Mitochondrial proteins were used for detailed computational investigation, using available standard bioinformatics tools to exploit structural and functional relationships. These proteins in Fasciola hepatica, Fasciola gigentica, and Fasciola jacksoni were functionally annotated using public databases. The results showed that the protein of COX1 of F. hepatica, F. gigantica, and F. jacksoni consist of 510, 513, and 517 amino acids, respectively. The alignment of proteins showed that these proteins are conserved in the same regions at ten positions in COX and CYTB proteins while at twelve locations in NADH. Three-dimensional structure of COX, CYTB, and NADH proteins were compared and showed differences in additional conserved and binding sites in COX and CYTB proteins as compared to NADH in three species of Fasciola. These results based on the amino acid diversity pattern were used to identify sites in the enzyme and the variations in mitochondrial proteins among Fasciola species. Our study provides valuable information for future experimental studies, including identification of therapeutic, diagnostic, and immunoprophylactic interests with novel mitochondrial proteins.

SCOP2 prototype: a new approach to protein structure mining

We present a prototype of a new structural classification of proteins, SCOP2 (http://scop2.mrc-lmb.cam.ac.uk/), that we have developed recently. SCOP2 is a successor to the Structural Classification of Proteins (SCOP, http://scop.mrc-lmb.cam.ac.uk/scop/) database. Similarly to SCOP, the main focus of SCOP2 is to organize structurally characterized proteins according to their structural and evolutionary relationships. SCOP2 was designed to provide a more advanced framework for protein structure annotation and classification. It defines a new approach to the classification of proteins that is essentially different from SCOP, but retains its best features. The SCOP2 classification is described in terms of a directed acyclic graph in which nodes form a complex network of many-to-many relationships and are represented by a region of protein structure and sequence. The new classification project is expected to ensure new advances in the field and open new areas of research.

Current progress in Structure-Based Rational Drug Design marks a new mindset in drug discovery

The past decade has witnessed a paradigm shift in preclinical drug discovery with structure-based drug design (SBDD) making a comeback while high-throughput screening (HTS) methods have continued to generate disappointing results. There is a deficit of information between identified hits and the many criteria that must be fulfilled in parallel to convert them into preclinical candidates that have a real chance to become a drug. This gap can be bridged by investigating the interactions between the ligands and their receptors. Accurate calculations of the free energy of binding are still elusive; however progresses were made with respect to how one may deal with the versatile role of water. A corpus of knowledge combining X-ray structures, bioinformatics and molecular modeling techniques now allows drug designers to routinely produce receptor homology models of increasing quality. These models serve as a basis to establish and validate efficient rationales used to tailor and/or screen virtual libraries with enhanced chances of obtaining hits. Many case reports of successful SBDD show how synergy can be gained from the combined use of several techniques. The role of SBDD with respect to two different classes of widely investigated pharmaceutical targets: (a) protein kinases (PK) and (b) G-protein coupled receptors (GPCR) is discussed. Throughout these examples prototypical situations covering the current possibilities and limitations of SBDD are presented.

Effective techniques for protein structure mining

Retrieval and characterization of protein structure relationships are instrumental in a wide range of tasks in structural biology. The classification of protein structures (COPS) is a web service that provides efficient access to structure and sequence similarities for all currently available protein structures. Here, we focus on the application of COPS to the problem of template selection in homology modeling.

Touring protein space with Matt

Using the Matt structure alignment program, we take a tour of protein space, producing a hierarchical clustering scheme that divides protein structural domains into clusters based on geometric dissimilarity. While it was known that purely structural, geometric, distance-based measures of structural similarity, such as Dali/FSSP, could largely replicate hand-curated schemes such as SCOP at the family level, it was an open question as to whether any such scheme could approximate SCOP at the more distant superfamily and fold levels. We partially answer this question in the affirmative, by designing a clustering scheme based on Matt that approximately matches SCOP at the superfamily level, and demonstrates qualitative differences in performance between Matt and DaliLite. Implications for the debate over the organization of protein fold space are discussed. Based on our clustering of protein space, we introduce the Mattbench benchmark set, a new collection of structural alignments useful for testing sequence aligners on more distantly homologous proteins.

Detection and alignment of 3D domain swapping proteins using angle-distance image-based secondary structural matching techniques

This work presents a novel detection method for three-dimensional domain swapping (DS), a mechanism for forming protein quaternary structures that can be visualized as if monomers had “opened” their “closed” structures and exchanged the opened portion to form intertwined oligomers. Since the first report of DS in the mid 1990s, an increasing number of identified cases has led to the postulation that DS might occur in a protein with an unconstrained terminus under appropriate conditions. DS may play important roles in the molecular evolution and functional regulation of proteins and the formation of depositions in Alzheimer's and prion diseases. Moreover, it is promising for designing auto-assembling biomaterials. Despite the increasing interest in DS, related bioinformatics methods are rarely available. Owing to a dramatic conformational difference between the monomeric/closed and oligomeric/open forms, conventional structural comparison methods are inadequate for detecting DS. Hence, there is also a lack of comprehensive datasets for studying DS. Based on angle-distance (A-D) image transformations of secondary structural elements (SSEs), specific patterns within A-D images can be recognized and classified for structural similarities. In this work, a matching algorithm to extract corresponding SSE pairs from A-D images and a novel DS score have been designed and demonstrated to be applicable to the detection of DS relationships. The Matthews correlation coefficient (MCC) and sensitivity of the proposed DS-detecting method were higher than 0.81 even when the sequence identities of the proteins examined were lower than 10%. On average, the alignment percentage and root-mean-square distance (RMSD) computed by the proposed method were 90% and 1.8Å for a set of 1,211 DS-related pairs of proteins. The performances of structural alignments remain high and stable for DS-related homologs with less than 10% sequence identities. In addition, the quality of its hinge loop determination is comparable to that of manual inspection. This method has been implemented as a web-based tool, which requires two protein structures as the input and then the type and/or existence of DS relationships between the input structures are determined according to the A-D image-based structural alignments and the DS score. The proposed method is expected to trigger large-scale studies of this interesting structural phenomenon and facilitate related applications.

Advances and pitfalls of protein structural alignment

Structure comparison opens a window into the distant past of protein evolution, which has been unreachable by sequence comparison alone. With 55,000 entries in the Protein Data Bank and about 500 new structures added each week, automated processing, comparison, and classification are necessary. A variety of methods use different representations, scoring functions, and optimization algorithms, and they generate contradictory results even for moderately distant structures. Sequence mutations, insertions, and deletions are accommodated by plastic deformations of the common core, retaining the precise geometry of the active site, and peripheral regions may refold completely. Therefore structure comparison methods that allow for flexibility and plasticity generate the most biologically meaningful alignments. Active research directions include both the search for fold invariant features and the modeling of structural transitions in evolution. Advances have been made in algorithmic robustness, multiple alignment, and speeding up database searches.

COPS--a novel workbench for explorations in fold space

The COPS (Classification Of Protein Structures) web server provides access to the complete repertoire of known protein structures and protein structural domains. The COPS classification encodes pairwise structural similarities as quantified metric relationships. The resulting metrical structure is mapped to a hierarchical tree, which is largely equivalent to the structure of a file browser. Exploiting this relationship we implemented the Fold Space Navigator, a tool that makes navigation in fold space as convenient as browsing through a file system. Moreover, pairwise structural similarities among the domains can be visualized and inspected instantaneously. COPS is updated weekly and stays concurrent with the PDB repository. The server also exposes the COPS classification pipeline. Newly determined structures uploaded to the server are chopped into domains, the locations of the new domains in the classification tree are determined, and their neighborhood can be immediately explored through the Fold Space Navigator. The COPS web server is accessible at http://cops.services.came.sbg.ac.at/.

Cross-over between discrete and continuous protein structure space: insights into automatic classification and networks of protein structures

Structural classifications of proteins assume the existence of the fold, which is an intrinsic equivalence class of protein domains. Here, we test in which conditions such an equivalence class is compatible with objective similarity measures. We base our analysis on the transitive property of the equivalence relationship, requiring that similarity of A with B and B with C implies that A and C are also similar. Divergent gene evolution leads us to expect that the transitive property should approximately hold. However, if protein domains are a combination of recurrent short polypeptide fragments, as proposed by several authors, then similarity of partial fragments may violate the transitive property, favouring the continuous view of the protein structure space. We propose a measure to quantify the violations of the transitive property when a clustering algorithm joins elements into clusters, and we find out that such violations present a well defined and detectable cross-over point, from an approximately transitive regime at high structure similarity to a regime with large transitivity violations and large differences in length at low similarity. We argue that protein structure space is discrete and hierarchic classification is justified up to this cross-over point, whereas at lower similarities the structure space is continuous and it should be represented as a network. We have tested the qualitative behaviour of this measure, varying all the choices involved in the automatic classification procedure, i.e., domain decomposition, alignment algorithm, similarity score, and clustering algorithm, and we have found out that this behaviour is quite robust. The final classification depends on the chosen algorithms. We used the values of the clustering coefficient and the transitivity violations to select the optimal choices among those that we tested. Interestingly, this criterion also favours the agreement between automatic and expert classifications. As a domain set, we have selected a consensus set of 2,890 domains decomposed very similarly in SCOP and CATH. As an alignment algorithm, we used a global version of MAMMOTH developed in our group, which is both rapid and accurate. As a similarity measure, we used the size-normalized contact overlap, and as a clustering algorithm, we used average linkage. The resulting automatic classification at the cross-over point was more consistent than expert ones with respect to the structure similarity measure, with 86% of the clusters corresponding to subsets of either SCOP or CATH superfamilies and fewer than 5% containing domains in distinct folds according to both SCOP and CATH. Almost 15% of SCOP superfamilies and 10% of CATH superfamilies were split, consistent with the notion of fold change in protein evolution. These results were qualitatively robust for all choices that we tested, although we did not try to use alignment algorithms developed by other groups. Folds defined in SCOP and CATH would be completely joined in the regime of large transitivity violations where clustering is more arbitrary. Consistently, the agreement between SCOP and CATH at fold level was lower than their agreement with the automatic classification obtained using as a clustering algorithm, respectively, average linkage (for SCOP) or single linkage (for CATH). The networks representing significant evolutionary and structural relationships between clusters beyond the cross-over point may allow us to perform evolutionary, structural, or functional analyses beyond the limits of classification schemes. These networks and the underlying clusters are available at http://ub.cbm.uam.es/research/ProtNet.php

Making order of the fast-growing information on proteins is essential for gaining evolutionary and functional knowledge. The most successful approaches to this task are based on classifications of protein structures, such as SCOP and CATH, which assume a discrete view of the protein structure space as a collection of separated equivalence classes (folds). However, several authors proposed that protein domains should be regarded as assemblies of polypeptide fragments, which implies that the protein–structure space is continuous. Here, we assess these views of domain space through the concept of transitivity; i.e., we test whether structure similarity of A with B and B with C implies that A and C are similar, as required for consistent classification. We find that the domain space is approximately transitive and discrete at high similarity and continuous at low similarity, where transitivity is severely violated. Comparing our classification at the cross-over similarity with CATH and SCOP, we find that they join proteins at low similarity where classification is inconsistent. Part of this discrepancy is due to structural divergence of homologous domains, which are forced to be in a single cluster in CATH and SCOP. Structural and evolutionary relationships between consistent clusters are represented as a network in our approach, going beyond current protein classification schemes. We conjecture that our results are related to a change of evolutionary regime, from uniparental divergent evolution for highly related domains to assembly of large fragments for which the classical tree representation is unsuitable.

A discrete view on fold space

The database of known protein structures contains an overwhelming number of structural similarities that frequently point to intriguing biological relationships. The similarities are often difficult to spot, and once detected their comprehension needs proper visualization. Here we introduce the new concept of a Fold Space Navigator, a user interface enabling the efficient navigation through fold space and the instantaneous visualization of pairwise structure similarities.

AVAILABILITY

The Fold Space Navigator is accessible as a public web service at http://services.came.sbg.ac.at

A note on difficult structure alignment problems

Progress in structural biology depends on several key technologies. In particular tools for alignment and superposition of protein structures are indispensable. Here we describe the use of the TopMatch web service, an effective computational tool for protein structure alignment, for the visualization of structural similarities, and for highlighting relationships found in protein classifications. We provide several instructive examples.

AVAILABILITY

TopMatch is available as a public web service at http://services.came.sbg.ac.at.

QSCOP-BLAST--fast retrieval of quantified structural information for protein sequences of unknown structure

QSCOP is a quantitative structural classification of proteins which distinguishes itself from other classifications by two essential properties: (i) QSCOP is concurrent with the Research Collaboratory for Structural Bioinformatics (RCSB) Protein Data Bank and (ii) QSCOP covers the widely used SCOP classification with layers of quantitative structural information. The QSCOP-BLAST web server presented here combines the BLAST sequence search engine with QSCOP to retrieve, for a given query sequence, all structural information currently available. The resulting search engine is reliable in terms of the quality of results obtained, and it is efficient in that results are displayed instantaneously. The hierarchical organization of QSCOP is used to control the redundancy and diversity of the retrieved hits with the benefit that the often cumbersome and difficult interpretation of search results is an intuitive and straightforward exercise. We demonstrate the use of QSCOP-BLAST by example. The server is accessible at http://qscop-blast.services.came.sbg.ac.at/