NetTurnP – Neural Network Prediction of Beta-turns by Use of Evolutionary Information and Predicted Protein Sequence Features

UNLABELLED: β-turns are the most common type of non-repetitive structures, and constitute on average 25% of the amino acids in proteins. The formation of β-turns plays an important role in protein folding, protein stability and molecular recognition processes. In this work we present the neural network method NetTurnP, for prediction of two-class β-turns and prediction of the individual β-turn types, by use of evolutionary information and predicted protein sequence features. It has been evaluated against a commonly used dataset BT426, and achieves a Matthews correlation coefficient of 0.50, which is the highest reported performance on a two-class prediction of β-turn and not-β-turn. Furthermore NetTurnP shows improved performance on some of the specific β-turn types. In the present work, neural network methods have been trained to predict β-turn or not and individual β-turn types from the primary amino acid sequence. The individual β-turn types I, I', II, II', VIII, VIa1, VIa2, VIba and IV have been predicted based on classifications by PROMOTIF, and the two-class prediction of β-turn or not is a superset comprised of all β-turn types. The performance is evaluated using a golden set of non-homologous sequences known as BT426. Our two-class prediction method achieves a performance of: MCC=0.50, Qtotal=82.1%, sensitivity=75.6%, PPV=68.8% and AUC=0.864. We have compared our performance to eleven other prediction methods that obtain Matthews correlation coefficients in the range of 0.17-0.47. For the type specific β-turn predictions, only type I and II can be predicted with reasonable Matthews correlation coefficients, where we obtain performance values of 0.36 and 0.31, respectively. CONCLUSION: The NetTurnP method has been implemented as a webserver, which is freely available at http://www.cbs.dtu.dk/services/NetTurnP/. NetTurnP is the only available webserver that allows submission of multiple sequences

In Vivo Systematic Analysis of Candida albicans Zn2-Cys6 Transcription Factors Mutants for Mice Organ Colonization

The incidence of fungal infections in immuno-compromised patients increased considerably over the last 30 years. New treatments are therefore needed against pathogenic fungi. With Candida albicans as a model, study of host-fungal pathogen interactions might reveal new sources of therapies. Transcription factors (TF) are of interest since they integrate signals from the host environment and participate in an adapted microbial response. TFs of the Zn2-Cys6 class are specific to fungi and are important regulators of fungal metabolism. This work analyzed the importance of the C. albicans Zn2-Cys6 TF for mice kidney colonization. For this purpose, 77 Zn2-Cys6 TF mutants were screened in a systemic mice model of infection by pools of 10 mutants. We developed a simple barcoding strategy to specifically detect each mutant DNA from mice kidney by quantitative PCR. Among the 77 TF mutant strains tested, eight showed a decreased colonization including mutants for orf19.3405, orf19.255, orf19.5133, RGT1, UGA3, orf19.6182, SEF1 and orf19.2646, and four an increased colonization including mutants for orf19.4166, ZFU2, orf19.1685 and UPC2 as compared to the isogenic wild type strain. Our approach was validated by comparable results obtained with the same animal model using a single mutant and the revertant for an ORF (orf19.2646) with still unknown functions. In an attempt to identify putative involvement of such TFs in already known C. albicans virulence mechanisms, we determined their in vitro susceptibility to pH, heat and oxidative stresses, as well as ability to produce hyphae and invade agar. A poor correlation was found between in vitro and in vivo assays, thus suggesting that TFs needed for mice kidney colonization may involve still unknown mechanisms. This large-scale analysis of mice organ colonization by C. albicans can now be extended to other mutant libraries since our in vivo screening strategy can be adapted to any preexisting mutants

VIBRATIONAL-SPECTRA AND NORMAL COORDINATE ANALYSIS OF (CH3)4SN4S6 WITH TETRAHEDRAL ADAMANTANE-TYPE STRUCTURE

Müller A, NOLTE W, CYVIN SJ, CYVIN BN, ALIX AJP. VIBRATIONAL-SPECTRA AND NORMAL COORDINATE ANALYSIS OF (CH3)4SN4S6 WITH TETRAHEDRAL ADAMANTANE-TYPE STRUCTURE. SPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY. 1978;34(4):383-386

MOLECULAR VIBRATIONS OF COMPLEX WITH TRIGONAL LIGANDS .12. NORMAL COORDINATE ANALYSIS OF [PD(NH3)4]2+

ALIX AJP, MANFAIT M, SCHMIDT K, CYVIN BN, CYVIN SJ, Müller A. MOLECULAR VIBRATIONS OF COMPLEX WITH TRIGONAL LIGANDS .12. NORMAL COORDINATE ANALYSIS OF [PD(NH3)4]2+. JOURNAL DE CHIMIE PHYSIQUE ET DE PHYSICO-CHIMIE BIOLOGIQUE. 1980;77(5):367-372

Structural features specific to plant metallothioneins

The metallothionein (MT) superfamily combines a large variety of small cysteine-rich proteins from nearly all phyla of life that have the ability to coordinate various transition metal ions, including Zn(II), Cd(II), and Cu(I). The members of the plant MT family are characterized by great sequence diversity, requiring further subdivision into four subfamilies. Very peculiar and not well understood is the presence of rather long cysteine-free amino acid linkers between the cysteine-rich regions. In light of the distinct differences in sequence to MTs from other families, it seems obvious to assume that these differences will also be manifested on the structural level. This was already impressively demonstrated with the elucidation of the three-dimensional structure of the wheat E(c)-1 MT, which revealed two metal cluster arrangements previously unprecedented for any MT. However, as this structure is so far the only one available for the plant MT family, other sources of information are in high demand. In this review the focus is thus set on any structural features known, deduced, or assumed for the plant MT proteins. This includes the determination of secondary structural elements by circular dichroism, IR, and Raman spectroscopy, the analysis of the influence of the long linker regions, and the evaluation of the spatial arrangement of the sequence separated cysteine-rich regions with the aid of, e.g., limited proteolytic digestion. In addition, special attention is paid to the contents of divalent metal ions as the metal ion to cysteine ratios are important for predicting and understanding possible metal-thiolate cluster structures