New assessment of a structural alphabet.

International audienceA statistical analysis of the Protein Databank (PDB) structures had led us to define a set of small 3D structural prototypes called Protein Blocks (PBs). This structural alphabet includes 16 PBs, each one defined by the (phi, psi) dihedral angles of 5 consecutive residues. Here, we analyze the effect of the enlargement of the PDB on the PBs' definition. The results highlight the quality of the 3D approximation ensured by the PBs. These last could be of great interest in ab initio modeling

Editorial for Infectious Diseases - Drug Targets (in silico issue)

International audienceComing from Crimea, the Black Death spread to Western Europe and North Africa during the 1340s. From 1346 to 1352, the plague killed an estimated 25-40% of Europeans of all age-groups [1] , i.e., 30 to 60% of Europe population. One of the earliest and most widely accepted explanations was that God was punishing humanity for their sins. One remedy for the curse was to do penitence. Thus in 1348 there rapidly arose a mass movement of flagellation [2]. In fact flagellation could not really help against such threat. The Black Death or Bubonic plague is caused by Yersinia pestis, a Eubacteria discovered in 1894 by Alexandre Yersin. It is transmitted by the bite of the flea Xenopsylla cheopsis. This flea lives by feeding the blood of many species besides man but its most preferred relationship is with the black rat (Rattus rattus). Fossilized remains of the plague flea have been found in large numbers in Amarna, Egypt [3, 4] about 1350 BC, and thus could be directly linked to the events described in the Book of Samuel [5, 6]. During the epidemic of Bubonic plague in London in 1665-1666, the known treatments were made use of, e.g. the so-famous Theriac or Venice Treacle which is used from the time of ancient Rome as a remedy against poison [7]. Since then, more specialized and novel treatments have been developed. However, since the characterization of Yersinia pestis, numerous drugs have been developed against it, e.g. gentamicin or doxycycline [8]. These researches had been carried out using more elaborated biochemical, biophysical and biological approaches

: Protein Long Local Structure Prediction

International audienceA relevant and accurate description of three-dimensional (3D) protein structures can be achieved by characterizing recurrent local structures. In a previous study, we developed a library of 120 3D structural prototypes encompassing all known 11-residues long local protein structures and ensuring a good quality of structural approximation. A local structure prediction method was also proposed. Here, overlapping properties of local protein structures in global ones are taken into account to characterize frequent local networks. At the same time, we propose a new long local structure prediction strategy which involves the use of evolutionary information coupled with Support Vector Machines (SVMs). Our prediction is evaluated by a stringent geometrical assessment. Every local structure prediction with a Calpha RMSD less than 2.5 A from the true local structure is considered as correct. A global prediction rate of 63.1% is then reached, corresponding to an improvement of 7.7 points compared with the previous strategy. In the same way, the prediction of 88.33% of the 120 structural classes is improved with 8.65% mean gain. 85.33% of proteins have better prediction results with a 9.43% average gain. An analysis of prediction rate per local network also supports the global improvement and gives insights into the potential of our method for predicting super local structures. Moreover, a confidence index for the direct estimation of prediction quality is proposed. Finally, our method is proved to be very competitive with cutting-edge strategies encompassing three categories of local structure predictions. Proteins 2009. (c) 2009 Wiley-Liss, Inc

Protein beta-turn assignments

A classical way to analyze protein 3D structures or models is to investigate their secondary structures. Their predictions are also widely used as a help to build new 3D models. Thus, hundreds of prediction methods have been proposed. Nonetheless before predicting, secondary structure assignment is required even if not trivial. Therefore numerous but diverging assignment methods have been developed. β-turns constitute the third most important secondary structures. However, no analysis to compare the β-turn distributions according to different secondary structure assignment methods has ever been done. We propose in this paper to analyze and evaluate the results of such a comparison. We highlight some important divergence that could have important consequence for the analysis and prediction of β-turns

: peel it

International audienceThree-dimensional structures of proteins are the support of their biological functions. Their folds are maintained by inter-residue interactions which are one of the main focuses to understand the mechanisms of protein folding and stability. Furthermore, protein structures can be composed of single or multiple functional domains that can fold and function independently. Hence, dividing a protein into domains is useful for obtaining an accurate structure and function determination. In previous studies, we enlightened protein contact properties according to different definitions and developed a novel methodology named Protein Peeling. Within protein structures, Protein Peeling characterizes small successive compact units along the sequence called protein units (PUs). The cutting done by Protein Peeling maximizes the number of contacts within the PUs and minimizes the number of contacts between them. This method is so a relevant tool in the context of the protein folding research and particularly regarding the hierarchical model proposed by George Rose. Here, we accurately analyze the PUs at different levels of cutting, using a non-redundant protein databank. Distribution of PU sizes, number of PUs or their accessibility are screened to determine their common and different features. Moreover, we highlight the preferential amino acid interactions inside and between PUs. Our results show that PUs are clearly an intermediate level between secondary structures and protein structural domains

In silico local structure approach: A case study on Outer Membrane Proteins.

International audienceThe detection of Outer Membrane Proteins (OMP) in whole genomes is an actual question, their sequence characteristics have thus been intensively studied. This class of protein displays a common beta-barrel architecture, formed by adjacent antiparallel strands. However, due to the lack of available structures, few structural studies have been made on this class of proteins. Here we propose a novel OMP local structure investigation, based on a structural alphabet approach, i.e., the decomposition of 3D structures using a library of four-residue protein fragments. The optimal decomposition of structures using hidden Markov model results in a specific structural alphabet of 20 fragments, six of them dedicated to the decomposition of beta-strands. This optimal alphabet, called SA20-OMP, is analyzed in details, in terms of local structures and transitions between fragments. It highlights a particular and strong organization of beta-strands as series of regular canonical structural fragments. The comparison with alphabets learned on globular structures indicates that the internal organization of OMP structures is more constrained than in globular structures. The analysis of OMP structures using SA20-OMP reveals some recurrent structural patterns. The preferred location of fragments in the distinct regions of the membrane is investigated. The study of pairwise specificity of fragments reveals that some contacts between structural fragments in beta-sheets are clearly favored whereas others are avoided. This contact specificity is stronger in OMP than in globular structures. Moreover, SA20-OMP also captured sequential information. This can be integrated in a scoring function for structural model ranking with very promising results. Proteins 2007. (c) 2007 Wiley-Liss, Inc

Use of a structural alphabet for analysis of short loops connecting repetitive structures

BACKGROUND: Because loops connect regular secondary structures, analysis of the former depends directly on the definition of the latter. The numerous assignment methods, however, can offer different definitions. In a previous study, we defined a structural alphabet composed of 16 average protein fragments, which we called Protein Blocks (PBs). They allow an accurate description of every region of 3D protein backbones and have been used in local structure prediction. In the present study, we use this structural alphabet to analyze and predict the loops connecting two repetitive structures. RESULTS: We first analyzed the secondary structure assignments. Use of five different assignment methods (DSSP, DEFINE, PCURVE, STRIDE and PSEA) showed the absence of consensus: 20% of the residues were assigned to different states. The discrepancies were particularly important at the extremities of the repetitive structures. We used PBs to describe and predict the short loops because they can help analyze and in part explain these discrepancies. An analysis of the PB distribution in these regions showed some specificities in the sequence-structure relationship. Of the amino acid over- or under-representations observed in the short loop databank, 20% did not appear in the entire databank. Finally, predicting 3D structure in terms of PBs with a Bayesian approach yielded an accuracy rate of 36.0% for all loops and 41.2% for the short loops. Specific learning in the short loops increased the latter by 1%. CONCLUSION: This work highlights the difficulties of assigning repetitive structures and the advantages of using more precise descriptions, that is, PBs. We observed some new amino acid distributions in the short loops and used this information to enhance local prediction. Instead of describing entire loops, our approach predicts each position in the loops locally. It can thus be used to propose many different structures for the loops and to probe and sample their flexibility. It can be a useful tool in ab initio loop prediction

Correlation between local structural dynamics of proteins inferred from NMR ensembles and evolutionary dynamics of homologues of known structure.: Inherent and evolutionary structural dynamics

International audienceConformational changes in proteins are extremely important for their biochemical functions. Correlation between inherent conformational variations in a protein and conformational differences in its homologues of known structure is still unclear. In this study, we have used a structural alphabet called Protein Blocks (PBs). PBs are used to perform abstraction of protein 3-D structures into a 1-D strings of 16 alphabets (a-p) based on dihedral angles of overlapping pentapeptides. We have analyzed the variations in local conformations in terms of PBs represented in the ensembles of 801 protein structures determined using NMR spectroscopy. In the analysis of concatenated data over all the residues in all the NMR ensembles, we observe that the overall nature of inherent local structural variations in NMR ensembles is similar to the nature of local structural differences in homologous proteins with a high correlation coefficient of .94. High correlation at the alignment positions corresponding to helical and β-sheet regions is only expected. However, the correlation coefficient by considering only the loop regions is also quite high (.91). Surprisingly, segregated position-wise analysis shows that this high correlation does not hold true to loop regions at the structurally equivalent positions in NMR ensembles and their homologues of known structure. This suggests that the general nature of local structural changes is unique; however most of the local structural variations in loop regions of NMR ensembles do not correlate to their local structural differences at structurally equivalent positions in homologues

Identification of local conformational similarity in structurally variable regions of homologous proteins using protein blocks.

International audienceStructure comparison tools can be used to align related protein structures to identify structurally conserved and variable regions and to infer functional and evolutionary relationships. While the conserved regions often superimpose well, the variable regions appear non superimposable. Differences in homologous protein structures are thought to be due to evolutionary plasticity to accommodate diverged sequences during evolution. One of the kinds of differences between 3-D structures of homologous proteins is rigid body displacement. A glaring example is not well superimposed equivalent regions of homologous proteins corresponding to α-helical conformation with different spatial orientations. In a rigid body superimposition, these regions would appear variable although they may contain local similarity. Also, due to high spatial deviation in the variable region, one-to-one correspondence at the residue level cannot be determined accurately. Another kind of difference is conformational variability and the most common example is topologically equivalent loops of two homologues but with different conformations. In the current study, we present a refined view of the "structurally variable" regions which may contain local similarity obscured in global alignment of homologous protein structures. As structural alphabet is able to describe local structures of proteins precisely through Protein Blocks approach, conformational similarity has been identified in a substantial number of 'variable' regions in a large data set of protein structural alignments; optimal residue-residue equivalences could be achieved on the basis of Protein Blocks which led to improved local alignments. Also, through an example, we have demonstrated how the additional information on local backbone structures through protein blocks can aid in comparative modeling of a loop region. In addition, understanding on sequence-structure relationships can be enhanced through our approach. This has been illustrated through examples where the equivalent regions in homologous protein structures share sequence similarity to varied extent but do not preserve local structure

VLDP web server: a powerful geometric tool for analysing protein structures in their environment.

International audienceProtein structures are an ensemble of atoms determined experimentally mostly by X-ray crystallography or Nuclear Magnetic Resonance. Studying 3D protein structures is a key point for better understanding protein function at a molecular level. We propose a set of accurate tools, for analysing protein structures, based on the reliable method of Voronoi-Laguerre tessellations. The Voronoi Laguerre Delaunay Protein web server (VLDPws) computes the Laguerre tessellation on a whole given system first embedded in solvent. Through this fine description, VLDPws gives the following data: (i) Amino acid volumes evaluated with high precision, as confirmed by good correlations with experimental data. (ii) A novel definition of inter-residue contacts within the given protein. (iii) A measure of the residue exposure to solvent that significantly improves the standard notion of accessibility in some cases. At present, no equivalent web server is available. VLDPws provides output in two complementary forms: direct visualization of the Laguerre tessellation, mostly its polygonal molecular surfaces; files of volumes; and areas, contacts and similar data for each residue and each atom. These files are available for download for further analysis. VLDPws can be accessed at http://www.dsimb.inserm.fr/dsimb_tools/vldp