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Formalizing life: Towards an improved understanding of the sequence-structure relationship in alpha-helical transmembrane proteins
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
2007 (English)Doctoral thesis, monograph (Other academic)
Abstract [en]

Genes coding for alpha-helical transmembrane proteins constitute roughly 25% of the total number of genes in a typical organism. As these proteins are vital parts of many biological processes, an improved understanding of them is important for achieving a better understanding of the mechanisms that constitute life.

All proteins consist of an amino acid sequence that fold into a three-dimensional structure in order to perform its biological function. The work presented in this thesis is directed towards improving the understanding of the relationship between sequence and structure for alpha-helical transmembrane proteins. Specifically, five original methods for predicting the topology of alpha-helical transmembrane proteins have been developed: PRO-TMHMM, PRODIV-TMHMM, OCTOPUS, Toppred III and SCAMPI.

A general conclusion from these studies is that approaches that use multiple sequence information achive the best prediction accuracy. Further, the properties of reentrant regions have been studied, both with respect to sequence and structure. One result of this study is an improved definition of the topological grammar of transmembrane proteins, which is used in OCTOPUS and shown to further improve topology prediction. Finally, Z-coordinates, an alternative system for representation of topological information for transmembrane proteins that is based on distance to the membrane center has been introduced, and a method for predicting Z-coordinates from amino acid sequence, Z-PRED, has been developed.

Place, publisher, year, edition, pages
Stockholm: Institutionen för biokemi och biofysik , 2007. , 55 p.
Keyword [en]
bioinformatics, protein, topology, hidden Markov model, prediction
National Category
Bioinformatics (Computational Biology)
Research subject
URN: urn:nbn:se:su:diva-7144ISBN: 978-91-7155-504-5OAI: diva2:197719
Public defence
2007-11-23, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 12 A, Stockholm, 09:30
Available from: 2007-11-01 Created: 2007-10-24Bibliographically approved

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Department of Biochemistry and Biophysics
Bioinformatics (Computational Biology)

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