OpenStructure: an integrated software framework for computational structural biology.

Research projects in structural biology increasingly rely on combinations of heterogeneous sources of information, e.g. evolutionary information from multiple sequence alignments, experimental evidence in the form of density maps and proximity constraints from proteomics experiments. The OpenStructure software framework, which allows the seamless integration of information of different origin, has previously been introduced. The software consists of C++ libraries which are fully accessible from the Python programming language. Additionally, the framework provides a sophisticated graphics module that interactively displays molecular structures and density maps in three dimensions. In this work, the latest developments in the OpenStructure framework are outlined. The extensive capabilities of the framework will be illustrated using short code examples that show how information from molecular-structure coordinates can be combined with sequence data and/or density maps. The framework has been released under the LGPL version 3 license and is available for download from http://www.openstructure.org.

Tandem mass spectrometry protein identification on a PC grid.

We present a method to grid-enable tandem mass spectrometry protein identification. The implemented parallelization strategy embeds the open-source x!tandem tool in a grid-enabled workflow. This allows rapid analysis of large-scale mass spectrometry experiments on existing heterogeneous hardware. We have explored different data-splitting schemes, considering both splitting spectra datasets and protein databases, and examine the impact of the different schemes on scoring and computation time. While resulting peptide e-values exhibit fluctuation, we show that these variations are small, caused by statistical rather than numerical instability, and are not specific to the grid environment. The correlation coefficient of results obtained on a standalone machine versus the grid environment is found to be better than 0.933 for spectra and 0.984 for protein identification, demonstrating the validity of our approach. Finally, we examine the effect of different splitting schemes of spectra and protein data on CPU time and overall wall clock time, revealing that judicious splitting of both data sets yields best overall performance.

Novel missense mutations of TMPRSS3 in two consanguineous Tunisian families with non-syndromic autosomal recessive deafness.

Recently the TMPRSS3 gene, which encodes a transmembrane serine protease, was found to be responsible for two non-syndromic recessive deafness loci located on human chromosome 21q22.3, DFNB8 and DFNB10. We found evidence for linkage to the DFNB8/10 locus in two unrelated consanguineous Tunisian families segregating congenital autosomal recessive sensorineural deafness. The audiometric tests showed a loss of hearing greater than 70 dB, in all affected individuals of both families. Mutation screening of TMPRSS3 revealed two novel missense mutations, W251C and P404L, altering highly conserved amino acids of the serine protease domain. Both mutations were not found in 200 control Tunisian chromosomes. The detection of naturally-occurring TMPRSS3 missense mutations in deafness families identifies functionally important amino acids. Comparative protein modeling of the TMPRSS3 protease domain predicted that W251C might lead to a structural rearrangement affecting the active site H257 and that P404L might alter the geometry of the active site loop and therefore affect the serine protease activity.

Automated protein modelling--the proteome in 3D.

Functional analysis of the proteins discovered in fully sequenced genomes represent the next major challenge of life science research. Computational methods play an increasingly important role in this activity. Among them, comparative protein modelling will play a major role in this challenge, especially in the light of the Structural Genomics programmes about to be started around the world. In recent years, much progress has been made in automating these methods, enabling the production of models for genome scale problems. In this review we discuss how protein models can be applied to functional analysis, as well as some of the current issues and limitations inherent to these methods.

Protein structure computing in the genomic era.

Functional analysis of the proteins discovered in fully sequenced genomes represents the next major challenge of life science research. Computational methods play a crucial role in this activity and, among them, comparative protein modelling is of great assistance during the rational design of mutagenesis experiments. Our aim over the last several years has been to further the use of 3-D model structures in this field. Therefore, we have developed a comparative protein modelling environment composed of the Swiss-PdbViewer (sequence to structure workbench and viewing program), SWISS-MODEL (internet-based server for model generation) and a database of a model generated with 3DCrunch.

Crystal structure of histidine ammonia-lyase revealing a novel polypeptide modification as the catalytic electrophile.

Histidine ammonia-lyase (EC 4.3.1.3) catalyzes the nonoxidative elimination of the alpha-amino group of histidine and is closely related to the important plant enzyme phenylalanine ammonia-lyase. The crystal structure of histidase from Pseudomonas putida was determined at 2.1 A resolution revealing a homotetramer with D2 symmetry, the molecular center of which is formed by 20 nearly parallel alpha-helices. The chain fold, but not the sequence, resembles those of fumarase C and related proteins. The structure shows that the reactive electrophile is a 4-methylidene-imidazole-5-one, which is formed autocatalytically by cyclization and dehydration of residues 142-144 with the sequence Ala-Ser-Gly. With respect to the first dehydration step, this modification resembles the chromophore of the green fluorescent protein. The active center is clearly established by the modification and by mutations. The observed geometry allowed us to model the bound substrate at a high confidence level. A reaction mechanism is proposed.

Homogenization and crystallization of histidine ammonia-lyase by exchange of a surface cysteine residue.

Histidase (histidine ammonia-lyase, EC 4.3.1.3) from Pseudomonas putida was expressed in Escherichia coli and purified. In the absence of thiols the tetrameric enzyme gave rise to undefined aggregates and suitable crystals could not be obtained. The solvent accessibility along the chain was predicted from the amino acid sequence. Among the seven cysteines, only one was labeled as 'solvent-exposed'. The exchange of this cysteine to alanine abolished all undefined aggregations and yielded readily crystals diffracting to 1.8 A resolution.