Non-redundant Protein Data Bank Research Articles

Light spectra affect the in vitro shoot development of Cedrela fissilis Vell. (Meliaceae) by changing the protein profile and polyamine contents

The light spectrum quality is an important signal for plant growth and development. We evaluated the effects of different light spectra on the in vitro shoot development of Cedrela fissilis and its proteomic and polyamine (PA) profiles. Cotyledonary and apical nodal segments were grown under different light emitting diodes (LED) and fluorescent lamps. Shoots from cotyledonary nodal segments cultured with 6-benzyladenine (BA) that were grown under WmBdR LED showed increased length and higher fresh and dry matter compared to shoots grown under fluorescent lamps. A nonredundant protein databank generated by transcriptome sequencing and the de novo assembly of C. fissilis improved, and almost doubled, the protein identification compared to a Citrus sinensis databank. A total of 616 proteins were identified, with 23 up- and 103 down-accumulated in the shoots under WmBdR LEDs compared to fluorescent lamps. Most differentially accumulated proteins in shoots grown under the WmBdR LED lamp treatment compared to the fluorescent lamp treatment are involved in responding to metabolic processes, stress, biosynthetic and cellular protein modifications, and light stimulus processes. Among the proteins, the up-accumulation of argininosuccinate synthase was associated with an increase in the free putrescine content and, consequently, with higher shoot elongation under WmBdR LED. The down-accumulation of calreticulin, heat shock proteins, plastid-lipid-associated protein, ubiquitin-conjugating enzymes, and ultraviolet-B receptor UVR8 isoform X1 could be related to the longer shoot length noted under LED treatment. This study provides important data related to the effects of the light spectrum quality on in vitro morphogenesis through the modulation of specific proteins and free putrescine biosynthesis in C. fissilis, an endangered wood species from the Brazilian Atlantic Forest of economic and ecological relevance. The nonredundant protein databank of C. fissilis is available via ProteomeXchange under identifier PXD018020.

SIMBAD: a sequence-independent molecular-replacement pipeline.

The conventional approach to finding structurally similar search models for use in molecular replacement (MR) is to use the sequence of the target to search against those of a set of known structures. Sequence similarity often correlates with structure similarity. Given sufficient similarity, a known structure correctly positioned in the target cell by the MR process can provide an approximation to the unknown phases of the target. An alternative approach to identifying homologous structures suitable for MR is to exploit the measured data directly, comparing the lattice parameters or the experimentally derived structure-factor amplitudes with those of known structures. Here, SIMBAD, a new sequence-independent MR pipeline which implements these approaches, is presented. SIMBAD can identify cases of contaminant crystallization and other mishaps such as mistaken identity (swapped crystallization trays), as well as solving unsequenced targets and providing a brute-force approach where sequence-dependent search-model identification may be nontrivial, for example because of conformational diversity among identifiable homologues. The program implements a three-step pipeline to efficiently identify a suitable search model in a database of known structures. The first step performs a lattice-parameter search against the entire Protein Data Bank (PDB), rapidly determining whether or not a homologue exists in the same crystal form. The second step is designed to screen the target data for the presence of a crystallized contaminant, a not uncommon occurrence in macromolecular crystallography. Solving structures with MR in such cases can remain problematic for many years, since the search models, which are assumed to be similar to the structure of interest, are not necessarily related to the structures that have actually crystallized. To cater for this eventuality, SIMBAD rapidly screens the data against a database of known contaminant structures. Where the first two steps fail to yield a solution, a final step in SIMBAD can be invoked to perform a brute-force search of a nonredundant PDB database provided by the MoRDa MR software. Through early-access usage of SIMBAD, this approach has solved novel cases that have otherwise proved difficult to solve.

Structurally Conserved Binding Sites of Hemagglutinin as Targets for Influenza Drug and Vaccine Development

ProBiS is a new method to identify the binding site of protein through local structural alignment against the nonredundant Protein Data Bank (PDB), which may result in unique findings compared to the energy-based, geometry-based, and sequence-based predictors. In this work, binding sites of Hemagglutinin (HA), which is an important target for drugs and vaccines in influenza treatment, have been revisited by ProBiS. For the first time, the identification of conserved binding sites by local structural alignment across all subtypes and strains of HA available in PDB is presented. ProBiS finds three distinctive conserved sites on HA's structure (named Site 1, Site 2, and Site 3). Compared to other predictors, ProBiS is the only one that accurately defines the receptor binding site (Site 1). Apart from that, Site 2, which is located slightly above the TBHQ binding site, is proposed as a potential novel conserved target for membrane fusion inhibitor. Lastly, Site 3, located around Helix A at the stem domain and recently targeted by cross-reactive antibodies, is predicted to be conserved in the latest H7N9 China 2013 strain as well. The further exploration of these three sites provides valuable insight in optimizing the influenza drug and vaccine development.

Measurement of Hydrophobicity Distribution in Proteins - Non-redundant Protein Data Bank

Abstract The cluster analysis is applied to the analysis of the data describing the status of protein structure in respect to hydrophobic core characteristics. The analysis revealed presence of two clusters distinguishing the proteins accordant with the “fuzzy oil drop” model and those which appear as discordant in respect to this model. The analysis was performed separately for chains treated as structural unit and for units defined according to IV-order (taking the functional protein complex). The characteristics of these two classification system appeared to differ in respect to number of proteins belonging to each of two clusters as well as relation between them.

A Survey of Aspartate−Phenylalanine and Glutamate−Phenylalanine Interactions in the Protein Data Bank: Searching for Anion−π Pairs

Protein structures are stabilized using noncovalent interactions. In addition to the traditional noncovalent interactions, newer types of interactions are thought to be present in proteins. One such interaction, an anion-π pair, in which the positively charged edge of an aromatic ring interacts with an anion, forming a favorable anion-quadrupole interaction, has been previously proposed [Jackson, M. R., et al. (2007) J. Phys. Chem. B111, 8242-8249]. To study the role of anion-π interactions in stabilizing protein structure, we analyzed pairwise interactions between phenylalanine (Phe) and the anionic amino acids, aspartate (Asp) and glutamate (Glu). Particular emphasis was focused on identification of Phe-Asp or -Glu pairs separated by less than 7 Å in the high-resolution, nonredundant Protein Data Bank. Simplifying Phe to benzene and Asp or Glu to formate molecules facilitated in silico analysis of the pairs. Kitaura-Morokuma energy calculations were performed on roughly 19000 benzene-formate pairs and the resulting energies analyzed as a function of distance and angle. Edgewise interactions typically produced strongly stabilizing interaction energies (-2 to -7.3 kcal/mol), while interactions involving the ring face resulted in weakly stabilizing to repulsive interaction energies. The strongest, most stabilizing interactions were identified as preferentially occurring in buried residues. Anion-π pairs are found throughout protein structures, in helices as well as β strands. Numerous pairs also had nearby cation-π interactions as well as potential π-π stacking. While more than 1000 structures did not contain an anion-π pair, the 3134 remaining structures contained approximately 2.6 anion-π pairs per protein, suggesting it is a reasonably common motif that could contribute to the overall structural stability of a protein.

The LabelHash algorithm for substructure matching

BackgroundThere is an increasing number of proteins with known structure but unknown function. Determining their function would have a significant impact on understanding diseases and designing new therapeutics. However, experimental protein function determination is expensive and very time-consuming. Computational methods can facilitate function determination by identifying proteins that have high structural and chemical similarity.ResultsWe present LabelHash, a novel algorithm for matching substructural motifs to large collections of protein structures. The algorithm consists of two phases. In the first phase the proteins are preprocessed in a fashion that allows for instant lookup of partial matches to any motif. In the second phase, partial matches for a given motif are expanded to complete matches. The general applicability of the algorithm is demonstrated with three different case studies. First, we show that we can accurately identify members of the enolase superfamily with a single motif. Next, we demonstrate how LabelHash can complement SOIPPA, an algorithm for motif identification and pairwise substructure alignment. Finally, a large collection of Catalytic Site Atlas motifs is used to benchmark the performance of the algorithm. LabelHash runs very efficiently in parallel; matching a motif against all proteins in the 95% sequence identity filtered non-redundant Protein Data Bank typically takes no more than a few minutes. The LabelHash algorithm is available through a web server and as a suite of standalone programs at http://labelhash.kavrakilab.org. The output of the LabelHash algorithm can be further analyzed with Chimera through a plugin that we developed for this purpose.ConclusionsLabelHash is an efficient, versatile algorithm for large-scale substructure matching. When LabelHash is running in parallel, motifs can typically be matched against the entire PDB on the order of minutes. The algorithm is able to identify functional homologs beyond the twilight zone of sequence identity and even beyond fold similarity. The three case studies presented in this paper illustrate the versatility of the algorithm.

CMASA: an accurate algorithm for detecting local protein structural similarity and its application to enzyme catalytic site annotation

BackgroundThe rapid development of structural genomics has resulted in many "unknown function" proteins being deposited in Protein Data Bank (PDB), thus, the functional prediction of these proteins has become a challenge for structural bioinformatics. Several sequence-based and structure-based methods have been developed to predict protein function, but these methods need to be improved further, such as, enhancing the accuracy, sensitivity, and the computational speed. Here, an accurate algorithm, the CMASA (Contact MAtrix based local Structural Alignment algorithm), has been developed to predict unknown functions of proteins based on the local protein structural similarity. This algorithm has been evaluated by building a test set including 164 enzyme families, and also been compared to other methods.ResultsThe evaluation of CMASA shows that the CMASA is highly accurate (0.96), sensitive (0.86), and fast enough to be used in the large-scale functional annotation. Comparing to both sequence-based and global structure-based methods, not only the CMASA can find remote homologous proteins, but also can find the active site convergence. Comparing to other local structure comparison-based methods, the CMASA can obtain the better performance than both FFF (a method using geometry to predict protein function) and SPASM (a local structure alignment method); and the CMASA is more sensitive than PINTS and is more accurate than JESS (both are local structure alignment methods). The CMASA was applied to annotate the enzyme catalytic sites of the non-redundant PDB, and at least 166 putative catalytic sites have been suggested, these sites can not be observed by the Catalytic Site Atlas (CSA).ConclusionsThe CMASA is an accurate algorithm for detecting local protein structural similarity, and it holds several advantages in predicting enzyme active sites. The CMASA can be used in large-scale enzyme active site annotation. The CMASA can be available by the mail-based server (http://159.226.149.45/other1/CMASA/CMASA.htm).

Alternative to Homo-oligomerisation: The Creation of Local Symmetry in Proteins by Internal Amplification

The biologically active state of many proteins requires their prior homo-oligomerisation. Such complexes are typically symmetrical, a feature that has been proposed to increase their stability and facilitate the evolution of allosteric regulation. We wished to examine the possibility that similar structures and properties could arise from genetic amplifications leading to internal symmetrical repeats. For this, we identified internal structural repeats in a nonredundant Protein Data Bank subset. While testing if repeats in proteins tend to be symmetrical, we found that about half of the large internal repeats are symmetrical, most frequently around a rotation axis of 180°. These repeats were most likely created by genetic amplification processes because they show significant sequence similarity. Symmetrical repeats tend to have a fixed number of copies corresponding to their rotational symmetry order, that is, two for 180° rotation axis, whereas asymmetrical repeats are in longer proteins and show copy number variability. When possible, we confirmed that proteins with symmetrical repeats folding as an n-mer have homologues lacking the repeat with a higher oligomerisation number corresponding to the rotation symmetry order of the repeat. Phylogenetic analyses of these protein families suggest that typically, but not always, symmetrical repeats arise in one single event from proteins that are homo-oligomers. These results suggest that oligomerisation and amplification of internal sequences can interplay in evolutionary terms because they result in functional analogues when the latter exhibit rotational symmetry.

Analysis of protein contacts into Protein Units

Three-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.

Molecular Design of Specific Metal‐Binding Peptide Sequences from Protein Fragments: Theory and Experiment

A novel strategy is presented for designing peptides with specific metal-ion chelation sites, based on linking computationally predicted ion-specific combinations of amino acid side chains coordinated at the vertices of the desired coordination polyhedron into a single polypeptide chain. With this aim, a series of computer programs have been written that 1) creates a structural combinatorial library containing Zi-(X)n-Zj sequences (n=0-14; Z: amino acid that binds the metal through the side chain; X: any amino acid) from the existing protein structures in the non-redundant Protein Data Bank; 2) merges these fragments into a single Z1-(X)n1 -Z2-(X)n2 -Z3-(X)n3 -...-Zj polypeptide chain; and 3) automatically performs two simple molecular mechanics calculations that make it possible to estimate the internal strain in the newly designed peptide. The application of this procedure for the most M2+-specific combinations of amino acid side chains (M: metal; see L. Rulísek, Z. Havlas J. Phys. Chem. B 2003, 107, 2376-2385) yielded several peptide sequences (with lengths of 6-20 amino acids) with the potential for specific binding with six metal ions (Co2+, Ni2+, Cu2+, Zn2+, Cd2+ and Hg2+). The gas-phase association constants of the studied metal ions with these de novo designed peptides were experimentally determined by MALDI mass spectrometry by using 3,4,5-trihydroxyacetophenone as a matrix, whereas the thermodynamic parameters of the metal-ion coordination in the condensed phase were measured by isothermal titration calorimetry (ITC), chelatometry and NMR spectroscopy methods. The data indicate that some of the computationally predicted peptides are potential M2+-specific metal-ion chelators.

Conformational flexibility may explain multiple cellular roles of PEST motifs

PEST sequences are one of the major motifs that serve as signal for the protein degradation and are also involved in various cellular processes such as phosphorylation and protein-protein interaction. In our earlier study, we found that these motifs contribute largely to eukaryotic protein disorder. This observation led us to evaluate their conformational variability in the nonredundant Protein Data Bank (PDB) structures. For this purpose, crystallographic temperature factors, structural alignment of multiple NMR models, and dihedral angle order parameters have been used in this study. The study has revealed the hypermobility of PEST motifs as compared to other regions of the protein. Conformational flexibility may allow them to participate in number of molecular interactions under different conditions. This analysis may explain the role of protein backbone flexibility in bringing about multiple cellular roles of PEST motifs.

Clustering of domains of functionally related enzymes in the interaction database PRECISE by the generation of primary sequence patterns

The PRECISE database was developed by our laboratory to allow for the systematic study of the ligand interactions common to a set of functionally related enzymes, where an interaction site is defined broadly as any residue(s) that interact with a ligand. During the construction of PRECISE, enzyme chains are extracted from the protein data bank (PDB) and clustered according to functional homology as defined by the enzyme commission (EC) nomenclature system. A sequence representative is chosen from each cluster based on the criterion set forth by the non-redundant PDB set, and pair-wise alignments of each cluster member to the representative are performed. Atom-based residue–ligand interactions are calculated for each cluster member, and the summation of ligand interactions for all cluster members at each aligned position is determined. Although we were able to successfully align most clusters using a simple dynamic programming algorithm, several cluster created exhibited poor pair-wise alignments of each cluster member to its sequence representative. We hypothesized that the observed alignment problems were, in most cases, due to the incorrect separation and alignment of different domains in multi-domain proteins, a mistake that frequently causes error proliferation in functional annotation. Here we present the results of generating primary sequence patterns for each poorly aligned cluster in PRECISE to assess the extent to which multi-domain proteins that are incorrectly aligned contributes to poor pair-wise alignments of each cluster member to its representative. This requires the use of an iterative locally optimal pair-wise alignment algorithm to build a hierarchical similarity-based sequence pattern for a set of functionally related enzymes. Our results show that poor alignments in PRECISE are caused most frequently by the misalignment of multi-domain proteins, and that the generation of primary sequence patterns for the assignment of sequence family membership yields better alignments for the functionally related enzyme clusters in PRECISE than our original alignment algorithm.

PMUT: a web-based tool for the annotation of pathological mutations on proteins

PMUT allows the fast and accurate prediction (approximately 80% success rate in humans) of the pathological character of single point amino acidic mutations based on the use of neural networks. The program also allows the fast scanning of mutational hot spots, which are obtained by three procedures: (1) alanine scanning, (2) massive mutation and (3) genetically accessible mutations. A graphical interface for Protein Data Bank (PDB) structures, when available, and a database containing hot spot profiles for all non-redundant PDB structures are also accessible from the PMUT server.

NdPASA: A novel pairwise protein sequence alignment algorithm that incorporates neighbor‐dependent amino acid propensities

Sequence alignment has become one of the essential bioinformatics tools in biomedical research. Existing sequence alignment methods can produce reliable alignments for homologous proteins sharing a high percentage of sequence identity. The performance of these methods deteriorates sharply for the sequence pairs sharing less than 25% sequence identity. We report here a new method, NdPASA, for pairwise sequence alignment. This method employs neighbor-dependent propensities of amino acids as a unique parameter for alignment. The values of neighbor-dependent propensity measure the preference of an amino acid pair adopting a particular secondary structure conformation. NdPASA optimizes alignment by evaluating the likelihood of a residue pair in the query sequence matching against a corresponding residue pair adopting a particular secondary structure in the template sequence. Using superpositions of homologous proteins derived from the PSI-BLAST analysis and the Structural Classification of Proteins (SCOP) classification of a nonredundant Protein Data Bank (PDB) database as a gold standard, we show that NdPASA has improved pairwise alignment. Statistical analyses of the performance of NdPASA indicate that the introduction of sequence patterns of secondary structure derived from neighbor-dependent sequence analysis clearly improves alignment performance for sequence pairs sharing less than 20% sequence identity. For sequence pairs sharing 13-21% sequence identity, NdPASA improves the accuracy of alignment over the conventional global alignment (GA) algorithm using the BLOSUM62 by an average of 8.6%. NdPASA is most effective for aligning query sequences with template sequences whose structure is known. NdPASA can be accessed online at http://astro.temple.edu/feng/Servers/BioinformaticServers.htm.

Toward the detection and validation of repeats in protein structure

We present a method called DAVROS to detect, localize, and validate repeating motifs in protein structure allowing for insertions and deletions. DAVROS uses the score matrix from a structural alignment program (SAP) to search for repeating motifs using an algorithm based on concepts from signal processing and the statistical properties of the alignments. The method was tested against a nonredundant Protein Data Bank, and each chain was assigned a score. For the top 50 chains ranked by score, 70% contain repeating motifs detected without error. These represent 14 types of fold covering alpha, beta, and alphabeta protein classes. A second data set comprising protein chains in different sequence families for triosephosphate isomerase (TIM) barrel, leucine-rich repeat (LRR), trefoil, and alpha-alpha barrel folds was used to assess the ability of DAVROS to detect all motifs within a specific fold. For the second test set, the percentage of motifs detected was highest for the LRR chains (88.7%) and least for the TIM barrels (60%). This variability results from the regularity of the LRR motif compared to the alphabeta units of the TIM barrel, which generally have many more indels. These reduce the strength of the repeat signal in the SAP matrix, making repeat detection more difficult.

Domain Insertions in Protein Structures

Domains are the structural, functional or evolutionary units of proteins. Proteins can comprise a single domain or a combination of domains. In multi-domain proteins, the domains almost always occur end-to-end, i.e., one domain follows the C-terminal end of another domain. However, there are exceptions to this common pattern, where multi-domain proteins are formed by insertion of one domain (insert) into another domain (parent). Here, we provide a quantitative description of known insertions in the Protein Data Bank (PDB). We found that 9% of domain combinations observed in non-redundant PDB are insertions. Although 90% of all insertions involve only one insert, proteins can clearly have multiple (nested, two-domain and three-domain) inserts. We also observed correlations between the structure and function of a domain and its tendency to be found as a parent or an insert. There is a bias in insert position towards the C terminus of parents. We observed that the atomic distance between the N and C terminus of an insert is significantly smaller when compared to the N-to-C distance in a parent context or a single domain context. Insertions are found always to occur in loop regions of parent domains. Our observations regarding the relationship between domain insertions and the structure, function and evolution of proteins have implications for protein engineering.

Genetic analysis of the chromosome of alkaliphilic Bacillus halodurans C-125.

Seventeen Sse8387I linking clones isolated from the chromosome of Bacillus halodurans C-125 for the purpose of constructing a physical map were sequenced and analyzed by comparison with the BSORF database and the nonredundant protein databank. The orientations of Sse8387I or AscI linking clones serving to join adjacent fragments were determined by southern blot analysis using specific DNA probes. One-third of the open reading frames (ORFs) identified in the Sse8387I linking clones showed no significant similarity to any protein so far reported. The ORFs showing significant similarities to those of Bacillus subtilis were mapped in the chromosome of strain C-125, and the locations of the putative genes on the map were not well conserved between B. halodurans C-125 and B. subtilis.