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Biomedical subjects

T Schwede

Publications and source records attributed to T Schwede.

3 recordsLinked to original sources

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.

Amino Acid Sequence↗

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.

Computational Biology↗

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.

Animals↗