A Computational approach to predict contact potential and disulfide bond of proteins /

Contact map and disulfide bond information of a protein give crucial clues about 3-dimensional structure and function of a protein. In this study, we represent a computational approach to predict both contact maps and disulfide bonds of the residues inside of a protein and these studies are two of the essential steps of protein folding problem. In the first study, we predicted contacting residues of proteins using physical (ordering, length and volume), chemical (hydrophobicity), evolutionary (neighboring) and structural (secondary structure) information by implementing classification techniques, Neural Networks (NNs) and Support Vector Machines (SVMs). As a result, our method predicts 14% of the contacting residues with 0.6% false positive ratio and it performs 9 times better than a random predictor. In the second study, using the same parameters we predicted cysteine residues forming. In this study, we used SVMs, we obtained 63.76% accuracy in disulfide bond prediction

Characterization of Non-Trivial Neighborhood Fold Constraints from Protein Sequences using Generalized Topohydrophobicity

Prediction of key features of protein structures, such as secondary structure, solvent accessibility and number of contacts between residues, provides useful structural constraints for comparative modeling, fold recognition, ab-initio fold prediction and detection of remote relationships. In this study, we aim at characterizing the number of non-trivial close neighbors, or long-range contacts of a residue, as a function of its “topohydrophobic” index deduced from multiple sequence alignments and of the secondary structure in which it is embedded. The “topohydrophobic” index is calculated using a two-class distribution of amino acids, based on their mean atom depths. From a large set of structural alignments processed from the FSSP database, we selected 1485 structural sub-families including at least 8 members, with accurate alignments and limited redundancy. We show that residues within helices, even when deeply buried, have few non-trivial neighbors (0–2), whereas β-strand residues clearly exhibit a multimodal behavior, dominated by the local geometry of the tetrahedron (3 non-trivial close neighbors associated with one tetrahedron; 6 with two tetrahedra). This observed behavior allows the distinction, from sequence profiles, between edge and central β-strands within β-sheets. Useful topological constraints on the immediate neighborhood of an amino acid, but also on its correlated solvent accessibility, can thus be derived using this approach, from the simple knowledge of multiple sequence alignments

Prodepth: Predict Residue Depth by Support Vector Regression Approach from Protein Sequences Only

Residue depth (RD) is a solvent exposure measure that complements the information provided by conventional accessible surface area (ASA) and describes to what extent a residue is buried in the protein structure space. Previous studies have established that RD is correlated with several protein properties, such as protein stability, residue conservation and amino acid types. Accurate prediction of RD has many potentially important applications in the field of structural bioinformatics, for example, facilitating the identification of functionally important residues, or residues in the folding nucleus, or enzyme active sites from sequence information. In this work, we introduce an efficient approach that uses support vector regression to quantify the relationship between RD and protein sequence. We systematically investigated eight different sequence encoding schemes including both local and global sequence characteristics and examined their respective prediction performances. For the objective evaluation of our approach, we used 5-fold cross-validation to assess the prediction accuracies and showed that the overall best performance could be achieved with a correlation coefficient (CC) of 0.71 between the observed and predicted RD values and a root mean square error (RMSE) of 1.74, after incorporating the relevant multiple sequence features. The results suggest that residue depth could be reliably predicted solely from protein primary sequences: local sequence environments are the major determinants, while global sequence features could influence the prediction performance marginally. We highlight two examples as a comparison in order to illustrate the applicability of this approach. We also discuss the potential implications of this new structural parameter in the field of protein structure prediction and homology modeling. This method might prove to be a powerful tool for sequence analysis

Improved prediction of the number of residue contacts in proteins by recurrent neural networks

Knowing the number of residue contacts in a protein is crucial for deriving constraints useful in modeling protein folding, protein structure, and/or scoring remote homology searches. Here we use an ensemble of bidirectional recurrent neural network architectures and evolutionary information to improve the state-of-the-art in contact prediction using a large corpus of curated data. The ensemble is used to discriminate between two different states of residue contacts, characterized by a contact number higher or lower than the average value of the residue distribution. The ensemble achieves performances ranging from 70.1% to 73.1% depending on the radius adopted to discriminate contacts (6\uc3\u85 to 12\uc3\u85). These performances represent gains of 15% to 20% over the base line statistical predictors always assigning an aminoacid to the most numerous state, 3% to 7% better than any previous method. Combination of different radius predictors further improves the performance. \uc2\ua9 Oxford University Press 2001

Molecular contest between potato and the potato cyst nematode Globodera pallida: modulation of Gpa2-mediated resistance

Gpa2 recognition specificity Among all the multicellular animals, nematodes are the most numerous. In soil, a high variety of free living nematodes feeding on bacteria can be found as well as species that parasitize insects, animals or plants. The potato cyst nematode (PCN) Globodera pallida is an important pest of cultivated potato. Upon infection of the roots, the nematode induces a feeding cell complex or so-called syncytium, on which the immobilized nematode fully depends for its development and reproduction. Due to the sophisticated feeding manner and ability to survive for a long time in the absence of a host plant, the best way to control these soil-born pathogens is the exploitation host resistance. Natural resistance to nematodes is based on single dominant resistance genes (R) or quantitative trait loci (QTL). Several nematode resistance genes have been identified and mapped. This includes the potato gene Gpa2 (Van der Vossen et al., 2000) that confers resistance against the population D383 of G. pallida. The Gpa2 gene is highly homologous to Rx1, which confers resistance against potato virus X (Bendahmane et al., 1999). Both genes encode a protein with a nucleotide-binding leucinerich repeat (NB-LRR) domains and a short coiled-coil domain at the N-terminus, which are in 88% identical at the amino acid level. The vast majority of the differences between Gpa2 and Rx1 is found in the predicted solvent exposed regions of the LRR domain. In chapter 2, we have shown that the LRR domain is essential for the recognition specificities of Gpa2 and Rx1, whereas the CC-NBS domains can be exchanged without affecting the specificity. In chapter 5, we have used a series of chimeric constructs in which segments of the Gpa2 LRR were replaced by the corresponding segments from Rx1. These constructs allowed us to narrow down the region required for nematode recognition to a stretch of residues between 808 and 912 amino acid residues in Gpa2, including 10 amino acids that differ between Gpa2 and Rx1. Furthermore, a computer-aided 3D model of the LRR domain is presented in which 7 of the Gpa2 specific amino acid residues map in a cluster onto the concave surface of the horseshoe-like structure of the LRR domain. Gpa2-mediated nematode resistance The research described in chapter 3 aimed to understand the mechanisms underlying Gpa2- mediated resistance to the potato cyst nematode G. pallida. The extreme resistance response conferred by the close homologue Rx1 results in the blocking of the potato virus X (PVX) at the infection sites and hence, the prevention of systemic spreading throughout the plant. Surprisingly, an entirely different defense mechanism was observed for resistant potato plants infected with juveniles of the avirulent Globodera pallida population D383. In susceptible plants, both the virulent population Rookmaker and the avirulent population D383 formed normal developing syncytia and nematodes were able to complete their life cycle as described in previous studies. Infection of resistant plants with the avirulent population showed no differences between susceptible and resistant potato plants in the early stages of G.pallida parasitism (root entering, migration, syncytium initiation). Syncytium induction took place in parenchyma cells, but rarely in other tissues. In samples collected 7 days later, however, the first necrotic cells in the surrounding of the syncytium were noticed including symptoms of degradation in the ultra structure of the syncytium itself in case of resistant plants infected with avirulent nematodes. Samples collected 10 days post infection had already a layer of necrotic cells, which separates the syncytium from the vascular bundle. At 14 days post infection, it was observed that the parenchyma cells not incorporated directly in the syncytia started to divide fast. Groups of hyperplastic cells surrounding the degrading syncytium resulted in pushing it away to the outer part of the root. This unique phenomenon, which was not observed before, can be part of the Gpa2-mediated defense response or a secondary reaction to the presence of necrotic, dead cells and a way to exclude them from the healthy conductive tissue of the root. Transcriptional regulation of the Gpa2 promoter To look in more details into the transcriptional regulation and expression of Gpa2, the native promoter was fused to the reporter gene GUS and this construct was introduced into susceptible potato. In chapter 3, the activity of the Gpa2 promoter was observed and shown to be restricted to the vascular system and the root tips in uninfected plants. Roots were challenged with G.pallida and the localization of the GUS expression was observed at the infection sites at different parasitic stages. During infection with virulent nematodes - but not the avirulent ones - this activity seems to be down regulated in vicinity of the syncytium. Such a local inhibition of Gpa2 promoter activity is in line with observations made on resistant roots when necrotic cells were only present around the feeding cell complex, distantly from the feeding nematode. The effector protein RBP-1 elicits a Gpa2 dependent HR Recently, a RBP-1protein with strong similarity to the SPRY domain of the Ran-binding protein RanBPM in juveniles of G. pallida was identified as a putative Gpa2 elicitor. Transient expression of RBP-1 in N. benthamiana leaves elicits a Gpa2-dependent cell death typical for the R-gene associated hypersensitive response (HR). Total RNA isolated from two populations of G.pallida, D383 (avr to Gpa2) and Rookmaker (vir to Gpa2) was converted into cDNA and screened for the presence of RBP-1s. This screening allowed the identification of in total 10 classes of closely related homologs of RBP-1. All identified classes were tested for their ability to elicit the Gpa2-dependent HR in an agroinfiltration assay. The capacity to induce an Gpa2-dependent HR was shown to correlate with a single amino acid substitution in RBP-1. No response was observed for two classes, which were obtained from the virulent population (RBP-1ROOK2, RBP-1ROOK4). For the other homologous RBP-1 classes – both deriving from the virulent and avirulent population - the response was ranging from a mild to a strong and fast HR. Both in-active RBP-1 variants have a serine substitution at position 166 (S166P) within the SPRY domain. When this residue was projected on a computer aided 3D model of RBP, we noticed that this amino acid is in a loop extending from the protein core. Replacing the proline into a serine is predicted to change the shape of the loop and hence, to affect the potential surface for protein-protein interactions. Non-eliciting RBP-1 variants suppress RBP-induced Gpa2 activation It was shown that the non-eliciting variants (RBP-1ROOK2 and RBP-1ROOK4) can suppress the activation of a Gpa2-mediated HR by the eliciting RBP-1 variants. This effect was specific for the Gpa2-mediated HR, and not observed with a Rx1-induced HR. As autoactive mutants of Gpa2 and Rx1-mediated cell death are not blocked by the inactive variants of RBP-1, the mechanism of suppression or inhibition likely operates on a functional Gpa2 protein, instead of downstream Gpa2-activated signaling pathways. Further research is required to resolve the mechanism underlying the possible competitive interactions of the active and the inactive RBP-1 variants on the Gpa2-mediated HR. Essentially, two possible models that could explain this phenomenon. First, the inactive variants could physically out compete the active RBP-1s. The binding target of active and inactive variants of RBP-1 variants could be directly in the Gpa2 protein or in the virulence target monitored by Gpa2. Alternatively, the inactive variants of RBP-1 may intercept active RBP-1 variants by forming an inactive heterodimer complex rendering it essentially undetectable for the Gpa2 protein. <br/

Klonierung und funktionelle Charakterisierung der NTPDase3 aus der Ratte

Extrazelluläre Nukleotide fungieren als auto- und parakrine Signalstoffe aus. Im peripheren und zentralen Nervensystem dienen Nukleotide als Neurotransmitter und Neuro­modulatoren. Die nahezu ubiquitäre Expression von Purin-Rezeptoren läßt auf umfassende physiologische Funktionen schließen. Nukleotide konnen über ionotrope P2X-Rezeptoren oder metabotrobe P2Y-Rezeptoren ihre Signalwirkung vermitteln. Via P1-Rezeptoren kann Adenosin, ein Baustein bzw. Abbauprodukt von ATP, seine neuro­modulatorische und neuro­protektive Wirkung entfalten. Alkalische Phosphatasen, die Ekto-Nukleotid-Pyrophosphatase/Phosphodiesterase Familie (NPP-Familie) und die Ekto-Nukleosid-Triphosphat-Diphosphohydrolase-Familie (E-NTPDasen) können Nukleosiddiphosphate und Nukleosidtriphosphate hydrolysieren. Die E-NTPDasen sind die wahrscheinlichsten Kandidaten für die Moduluation purinerger Signale im Nervensystem. In dieser Arbeit wurde die Klonierung und Charakterisierung der NTPDase3 der Ratte beschrieben. Ein vollständiger cDNA-Klon der NTPDase3 wurde aus einer Rattenhirnbank isoliert, sequenziert und anhand der familientypischen Sequenzmuster (ACRŽs) als E-NTPDase identifiziert. Die Sequenz enthielt einen offenen Leserahmen der für ein 529 Aminosäuren großes Protein kodierte. Sequenzvergleiche zeigten eine große Ähnlichkeit des Proteins mit den NTPDasen 1, 2 und 8, welche plasma­membran­ständige Ekto-Enzyme sind. Eine plasma­membran­ständige Lokalisation konnte in NTPDase3-transfizierten CHO-Zellen und in PC12-Zellen mit endogener NTPDase3-Expression nachgewiesen werden. Anhand von Computeranalysen und Sequenz­vergleichen wurden Überlegungen zur Sekundär- und Tertiär­struktur angestellt und Ähnlichkeiten zur Zuckerkinase/ Hitzeschock-Protein 70/Aktin-Superfamilie aufgezeigt. Das Protein war entsprechend der in silico-Analyse glykosiliert und ließ sich über das Lektin ConcavalinA anreichern. Messungen an Membran­fraktionen heterelog transfizierter CHO-Zellen zeigten die Hydrolyse verschiedener Nukleosidtriphosphate und Nukleosid­diphosphate mit einer Präferenz für Nukleosid­triphosphate. Das Enzym ist primär Kalziumabhängig und a rbeitet optimal im physiologischen pH-Bereich von pH 7,5 bis pH 8,0. Mit einem ATPase:ADPase-Verhältnis von 5:1 liegt die NTPDase3 zwischen der NTPDase1 und der NTPDase2. Seine biochemischen Eigenschaften machen das Ekto-Enzym zu einem Kandidaten für die Modulation purinerger Signale. Nukleotid-vermittelte Signale können via Hydrolyse durch die NTPDase3, möglicherweise in Kombination mit anderen E-NTPDasen, beendet werden. Als Bestandteil einer Enzymkette mit der Ekto-5Ž-Nukleotidase kann das Enzym zur Produktion des neuro­modulatorisch und neuro­protektiv wirkenden Adenosins beitragen. Mögliche Rollen bei der Regulation autokriner, parakriner und synaptischer Signale in nicht­neuronalen wie neuronalen Geweben wurden für die Gewebe diskutiert, in denen die NTPDase3 per Westernblot nachgewiesen werden konnte. Neben Dünndarm, Prostata, Pancreas, Nebenhoden und Samenleiter wurde ein NTPDase3-Band vor allem im zentralen Nervensystem gefunden. In allen geprüften Hirnteilen (Bulbus olfactorius, Cerebellum, Cortex, Mesencephalon, Diencephalon, Hippocampus, Striatum, Medulla oblongata), dem Rückenmark und der Hypophyse wurde die NTPDase3 im Westernblot detektiert. Das Enzym könnte an der Regulation exokriner Drüsenfunktionen im Pancreas und am epithelialem Ionen­transport involviert sein oder auch bei endokrinen Funktionen des Pankreas und der Hypophyse mitwirken. Möglicherweise hat die NTPDase3 funktionelle Bedeutung bei der Termination und Modulation purinerger Neuro­transmission im enterischen Nervensystem, im Rückenmark und in verschiedenen Hirn­regionen. An verschiedenen zentral­nervösen Funktionen, wie Schmerz­wahrnehmung, Atmungs- und Kreislauf-Regulation sowie Gedächtnis- und Lernprozessen sind purinerge Signale maßgeblich beteiligt und es ist wahrscheinlich, daß E-NTPDasen an der Modulation dieser Signale mitwirken. Die in dieser Arbeit beschriebene NTPDase3 ist ein viel versprechender Kandidat für die Regulation purinerger Signale im peripheren und zentralen Nervensystem

Protein structure prediction: improving and automating knowledge-based approaches

This work presents a computational approach to improve the automatic prediction of protein structures from sequence. Its main focus was twofold. An automated method for guiding the modeling process was first developed. This was tested and found to be state of the art in the CASP4 structure prediction contest in 2000. The second focus was the development of a novel divide and conquer algorithm for modeling flexible loops in proteins. Implementation of the search procedure and subsequent ranking is presented. The results are again compared with state of the art methods