HELANAL-Plus: a web server for analysis of helix geometry in protein structures

A methodology to analyze and characterize small- and large-scale shape and structural features in a macromolecule is presented. The procedure involves the construction of a continuum of spherical shape maps. This continuum is built by analyzing the overcrossing pattern of a molecular space curve from every direction in 3-space as seen by a viewer with a reduced vision field. The method derives global shape descriptors (shape maps) that characterize the backbone as a whole (large-scale structure), but also allows one to focus the analysis on details of the backbone's small-scale structure. A continuous function is proposed as a simplified descriptor derived from the shape maps. This function discriminates reasonably well among elements of secondary structure and supersecondary structural motifs in proteins. The procedure is applied to α-helices, β-sheets, and models of α-helical packing.

As the number of available three dimensional coordinates of proteins increases, it is now recognized that proteins from different families and topologies are constructed from independent motifs. Detection of specific structural motifs within proteins aids in understanding their role and the mechanism of their operation. To aid in identification and use of these motifs it has become necessary to develop efficient methods for systematic scanning of structural databases. To date, methods of structural protein comparison suffer from at least one of the following limitations: (1) are not fully automated (require human intervention), (2) are limited to relatively similar structures, (3) are constrained to linear alignments of the structures, (4) are sensitive to insertions, deletions or gaps in the sequences or (5) are very time consuming. We present a method to overcome the above limitations. The method discovers and ranks every piece of structural similarity between the structures compared, thus allowing the simultaneous detection of real 3-D motifs in different domains, between domains, in active sites, surfaces etc. The method uses the Geometric Hashing Paradigm which is an efficient technique originally developed for Computer Vision. The algorithm exploits the geometrical constraints of rigid objects, it is especially geared towards recognition of partial structures in rigid objects belonging to large data bases and is straightforwardly parallelizable. Computer Vision techniques are for the first time applied to molecular structure comparison, resulting in an efficient, fully automated tool. The method has been tested in a number of cases, including comparisons of the haemoglobins, immunoglobulins, serine proteinases, calcium binding proteins, DNA binding proteins and others. In all examples our results were equivalent to the published results from previous methods and in some cases additional structural information was obtained by our method.

9] Profile analysis

A specific treatment of recurrent structural motifs that represent the local bias information has been proven to be an important ingredient in de novo protein structure predication. Significant majority of methods for local structure are based on building blocks, which still suffer from its inherent discrete nature. Instead of using building blocks, this work presents a new protocol framework for local structural motifs prediction based on the direct locating along protein sequence and probabilistic sampling in a continuous (φ, ψ) space. The protein sequence was first scanned by an algorithm of sliding window with variable length of 7 to 19 residues, to match local segments to one of 82 motifs patterns in the fragment library. Identified segments were then labeled and modeled as the correlations of backbone torsion angles with mixture of bivariate cosine distributions in continuous (φ, ψ) space. 3D conformations of corresponding segments were finally sampled by using a backtrack algorithm to the hidden Markov model with single output of (φ, ψ). For local motifs in 50 proteins of testing set, about 62% of eight-residue segments located with high confidence value were predicted within 1.5 Å of their native structures by the method. Majority of local structural motifs were identified and sampled, which indicates the proposed protocol may at least serve as the foundation to obtain better protein tertiary structure prediction.

Chapter 111 - Nonlinear spectroscopy study of vibrational self-trapping in hydrogen bonded crystals

The number of gamma-turns in a representative protein dataset selected from the current Protein Data Bank has increased almost seven times during the past decade. Eighty percent classic gamma-turns and 57% inverse gamma-turns are associated as multiple turns with either another y-turn or a beta-turn. We refer to these as multiple turns of the (gammabeta)1,2,3 or (betagamma)1,2,3 type, depending upon whether the gamma-turn is before or after the beta-turn along the protein chain, respectively. However, for multiple turns involving only gamma-turns, we follow the nomenclature analogous to that proposed earlier for the multiple (or double) beta-turns. Fifty-eight per cent beta-turns are associated as multiple turns with another beta-turn. We extracted multiple turns from the protein dataset and classified them on the basis of individual gamma- or beta-turn types and the number of overlapping residues. Furthermore, we evaluated the amino acid positional potentials and determined the statistically significant amino acid preferences, hydrogen bond/side-chain interaction preferences in the multiple turns and secondary structure preferences for residues immediately flanking these turns. The results of our analysis would be useful in the modeling, prediction or design of multiple turns in proteins. The amino acid sequence corresponding to the multiple turn, position in the protein chain, PDB Code/chain in which multiple turn is present and the individual turn types constituting the multiple turns are available from our website and this information would also be integrated in our Database of Structural Motifs in Proteins (http://www.cdfd.org.in/dsmp.html).

ObjectiveThe coiled coil is a superhelical structural protein motif that has been thoroughly investigated in recent years and coiled-coil domain-containing proteins have exhibited a large diversity of function in biological systems (e.g., gene regulation, cell division, membrane fusion, drug extrusion). The aim of this study was to investigate the critical role of coiled-coil domain-containing protein 34 (CCDC34) in bladder carcinogenesis, which has never been reported to date.MethodsImmunohistochemical staining and western blot were used to detect CCDC34 expression in bladder cancers specimens and cell lines. Lentivirus-mediated small interfering RNA (siRNA) against CCDC34 was designed and the silencing effect was examined by quantitative RT-PCR in bladder cancer cell lines T24 and 5637. The biological functions of CCDC34 knockdown on bladder cancer cells were investigated by examining cell proliferation using a high content screening (HCS) assay, BrdU incorporation assay and colony formation assay, as well as cell migration by in vitro wound healing assay. Cell cycle distribution and apoptosis were detected by flow cytometric analysis. The expressions of c-Raf and c-Jun as well as the phosphorylation of MEK, ERK1/2, JNK, P38 and AKT were also measured using Western blot. We further investigated the effect of therapeutic siRNA targeting CCDC34 on T24 xenograft tumor growth in nude mice.ResultsCCDC34 level was significantly increased in human bladder cancer tissues and cell lines. CCDC34 knockdown significantly suppressed bladder cancer cells proliferation and migration, and induced cell cycle arrest at G2/M phase and increased apoptosis in vitro. In addition, intratumor delivery of therapeutic siRNA targeting CCDC34 elicited delayed tumor growth of bladder cancer xenograft in nude mice. Moreover, CCDC34 knockdown decreased the phosphorylation of MEK, ERK1/2, JNK, p38 and Akt, and the expressions of c-Raf and c-Jun, indicating MAPK and AKT pathways (ERK/MAPK, p38/MAPK, JNK/MAPK and PI3K/Akt) might be involved in CCDC34 modulation of bladder cancer cell proliferation and migration.ConclusionsOur findings revealed for the first time a potential oncogenic role for CCDC34 in bladder carcinoma pathogenesis and it may serve as a biomarker or even a therapeutic target for bladder cancer.

Fragment-based drug design relies heavily on structural information for the elaboration and optimisation of hits. The ability to identify neighbouring binding hot spots, energetically favourable interactions and conserved binding motifs in protein structures through X-ray crystallography can inform the evolution of fragments into lead-like compounds through structure-based design. The composition of fragment libraries can be designed and curated to fit this purpose and herein, we describe and compare screening libraries containing compounds comprising between 2 and 18 heavy atoms. We evaluate the properties of the compounds in these libraries and assess their ability to probe protein surfaces for binding hot spots.

Databases are the computerized platform where information is stored and can be retrieved easily by public users. Biological databases are the repositories of biological data. These biological data libraries contain facts and figures related to various disciplines of research including genomics, proteomics, microarray technology, metabolomics and phylogenetics. By using biological databases, a broad collection of essential biological information can be exploited ranging from function, structure and localization of gene, clinical consequences of mutation to similarity index among biological sequences and structures. Nowadays, different kinds of biological databases are available on the web. The present write up focuses on biological databases and bioinformatics tools for protein structure analysis. This review also aims to elaborate the searching schemes, available in different structural databases. The wide variety of different levels and types of information content related to 3D protein structures are available on web-based databases. Regarding the biological functions and 3D structures of various proteins, these databases provide a huge range of useful links, schematic diagrams as well as strategies for detailed analysis of proteins and other macromolecules structures. 3D structural illustration of proteins stored in structural databases is determined and visualized by X-ray crystallography, electron microscopy and NMR spectroscopy. On regular basis, a large number of protein structures are submitted by structural biologists, updated and curated by subject experts. Most familiar biological databases that store 3D protein and other macromolecules structures include, PDB, 3D Genomics, CATH, & SCOP. These databases contain valuable information of overall protein structures, domains and motif structures, protein-protein complex systems and complex of protein with other biomolecules.

Novel high-throughput experimental techniques produce a large amount of data on the 3D structure of proteins and their structural motifs. These motifs can be used as patterns in drug discovery [1], can help to understand the relationship between a protein’s structure and its function [2] and to classify proteins [3]. In order to extract as much information as possible from this data, new techniques and tools are necessary, and among them fast approaches to perform the multiple superimposition of large sets of protein structural motifs. We report here on the development of such a tool. We have implemented our newly developed multiple superimposition methodology in the web application SiteBinder, which is able to process hundreds of protein structural motifs in a very short time and provides an intuitive and user-friendly interface. We also demonstrate the applicability of SiteBinder using three case studies, focused on biologically important protein motifs. In the first case study, we compared the structures of 67 PA-IIL sugar binding sites containing 9 different sugars and we found that the sugar binding sites of PA-IIL and its mutants have a conserved structure despite their binding different sugars. The second case study focused on more than 300 zinc finger central motifs and revealed that the molecular structure in the vicinity of the Zn atom in Cys2His2 zinc fingers is highly conserved. In the last case study, we superimposed 12 BH3 domains from pro-apoptotic proteins, and found that there is a structural basis for the functional segregation of these proteins into activators and enablers.

Camelina sativa stands out among oilseed crops due to its remarkable resilience to challenging environmental conditions and its significant potential for biodiesel production. The MADS-box transcription factors play a pivotal role in numerous biological processes within plants, encompassing growth, development, and responses to environmental stressors. In this research, by employing the BLAST, we have successfully identified 325 MADS-box genes within Camelina sativa genome. These genes were systematically categorized into two principal groups: type I (comprising Mα, Mβ, and Mγ) and type II (including MI-KCC and MIKC*) predicated upon their phylogenetic relationships, structural protein motifs, and exon-intron configurations. Our findings reveal that type II MADS-box genes have, in general, experienced a more profound expansion relative to type I genes. Specifically, the TM3 subgroup within type II MADS-box genes exhibited the highest degree of gene expansion, comprising 21 TM3 genes. The amino acid sequences encoded by these genes exhibited a length variation ranging from 150 to 820 aa. The predicted molecular weights (MW) of the CsMADS-box proteins displayed a range from 17.01 to 94.06 kDa, while the isoelectric points (pI) were observed to span from 4.13 to 10.09. Evolutionary analysis predicated on the Ka/Ks ratios indicates that the evolutionary pathway of MADS-box genes in Camelina sativa has been predominantly driven by the mechanisms of purifying selection. Moreover, an investigation of cis-acting elements has elucidated the participation of MADS-box genes in the adaptive responses to abiotic stressors. The expression profiles of six Type I and three MIKCC genes across diverse organs and under varying drought treatment conditions demonstrated that these genes are expressed in both reproductive and vegetative structures, displaying uniform expression patterns throughout several developmental phases of flowering. The expression levels of CsMADS035, CsMADS115, CsMADS131, and CsMADS181 were notably modified in reaction to drought stress conditions. The detailed annotation and comprehensive transcriptome profiling provided in this research yield essential insights into the functional roles that MADS-box genes perform in stress resistance, as well as their contributions to growth and developmental processes. This acquired understanding establishes a foundational framework for the functional characterization and potential genetic engineering initiatives pertaining to Camelina sativa, thereby augmenting the prospective application of these candidate genes.

The ubiquitous thioredoxin fold proteins catalyze oxidation, reduction, or disulfide exchange reactions depending on their redox properties. They also play vital roles in protein folding, redox control, and disease. Here, we have shown that a single residue strongly modifies both the redox properties of thioredoxin fold proteins and their ability to interact with substrates. This residue is adjacent in three-dimensional space to the characteristic CXXC active site motif of thioredoxin fold proteins but distant in sequence. This residue is just N-terminal to the conservative cis-proline. It is isoleucine 75 in the case of thioredoxin. Our findings support the conclusion that a very small percentage of the amino acid residues of thioredoxin-related proteins are capable of dictating the functions of these proteins.

Protein structure motif detection is one of the fundamental problems in Structural Bioinformatics. Compared with sequence motifs, structural motifs are more sensitive in detecting the evolutionary relationships among proteins. A variety of algorithms have been proposed to attack this problem. However, they are either heuristic without theoretical performance guarantee, or inefficient for employing an exhaustive search strategy. Here, we study a reasonably restricted version of this problem: the compact structural motif problem. In this paper, we prove that this restricted version is still NP-hard, and we present a polynomial-time approximation scheme to solve it. To the best of our knowledge, this is the first approximation algorithm with a guarantee ratio for the protein structural motif problem.

Two generalizations can be drawn from the recent rapid progress in understanding RNA-protein interactions. First, there is a great diversity of observed protein and RNA structural motifs. Second, formation of almost every RNA-protein complex that has been characterized involves conformational changes in the protein, the RNA, or both. The role of these conformational changes in the biological function of RNA-protein complexes is not at all clear. Whether or not conformational changes are a critical feature of ribonucleoprotein complex assembly or are an unimportant mechanistic detail, the ubiquity of these changes warrants careful consideration of their implications.

tRNA-guanine transglycosylase (TGT) from Escherichia coli catalyzes the exchange of the queuine precursor, preQ1, into tRNA as part of the biosynthetic pathway for the posttranscriptionally modified base, queuine. No significant sequence homologies exist between TGT and any of the proteins in the GenBank database. However, an unusual arrangement of cysteine residues was observed upon manual examination of the TGT sequence. Comparison of this sequence (residues 302-321) revealed similarities to structural zinc-binding motifs in proteins of known structure [Jaffe (1993) Comments Inorg. Chem. 15, 67-93]. Within this region of the TGT sequence, there are six residues (four cysteines and two histidines), any four of which could serve as the ligands to the zinc. We report here that wild-type TGT contains ca. 0.8 mol of zinc/mol of subunit, determined by atomic emission spectrometry. In order to determine which enzyme residues are serving as the ligands to the zinc, site-directed mutagenesis studies have been performed. Gross structural probes (native PAGE and CD spectra), enzyme activity assays, and tRNA-binding assays indicate that cysteines 302, 304, and 307 and histidine 317 are the ligands to the zinc. These results also suggest that the zinc site is necessary for TGT homotrimer formation and for tRNA binding.