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Using multiple templates to improve quality of homology models in automated homology modeling.
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.ORCID iD: 0000-0002-7115-9751
2008 (English)In: Protein Science, ISSN 0961-8368, Vol. 17, no 6, 990-1002 p.Article in journal (Refereed) Published
Abstract [en]

When researchers build high-quality models of protein structure from sequence homology, it is today common to use several alternative target-template alignments. Several methods can, at least in theory, utilize information from multiple templates, and many examples of improved model quality have been reported. However, to our knowledge, thus far no study has shown that automatic inclusion of multiple alignments is guaranteed to improve models without artifacts. Here, we have carried out a systematic investigation of the potential of multiple templates to improving homology model quality. We have used test sets consisting of targets from both recent CASP experiments and a larger reference set. In addition to Modeller and Nest, a new method (Pfrag) for multiple template-based modeling is used, based on the segment-matching algorithm from Levitt's SegMod program. Our results show that all programs can produce multi-template models better than any of the single-template models, but a large part of the improvement is simply due to extension of the models. Most of the remaining improved cases were produced by Modeller. The most important factor is the existence of high-quality single-sequence input alignments. Because of the existence of models that are worse than any of the top single-template models, the average model quality does not improve significantly. However, by ranking models with a model quality assessment program such as ProQ, the average quality is improved by approximately 5% in the CASP7 test set.

Place, publisher, year, edition, pages
Wiley-Blackwell Publishing, Inc. , 2008. Vol. 17, no 6, 990-1002 p.
Keyword [en]
Automation, Models; Molecular, Protein Conformation, Protein Folding, Proteins/chemistry, Sequence Homology; Amino Acid
URN: urn:nbn:se:su:diva-14852ISI: 000256166600004PubMedID: 18441233OAI: diva2:181372
Available from: 2008-11-20 Created: 2008-11-20 Last updated: 2014-11-10Bibliographically approved
In thesis
1. Prediction, modeling, and refinement of protein structure
Open this publication in new window or tab >>Prediction, modeling, and refinement of protein structure
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Accurate predictions of protein structure are important for understanding many processes in cells. The interactions that govern protein folding and structure are complex, and still far from completely understood. However, progress is being made in many areas. Here, efforts to improve the overall quality of protein structure models are described. From a pure evolutionary perspective, in which proteins are viewed in the light of gradually accumulated mutations on the sequence level, it is shown how information from multiple sources helps to create more accurate models. A very simple but surprisingly accurate method for assigning confidence measures for protein structures is also tested. In contrast to models based on evolution, physics based methods view protein structures as the result of physical interactions between atoms. Newly implemented methods are described that both increase the time-scales accessible for molecular dynamics simulations almost 10-fold, and that to some extent might be able to refine protein structures. Finally, I compare the efficiency and properties of different techniques for protein structure refinement.

Place, publisher, year, edition, pages
Stockholm: Department of Biochemistry and Biophysics, Stockholm University, 2010. 64 p.
Protein structure prediction, Multiple alignments, Quality assessment, Molecular dynamics, Implicit solvent, Refinement
National Category
Bioinformatics and Systems Biology Bioinformatics (Computational Biology) Theoretical Chemistry
Research subject
urn:nbn:se:su:diva-38253 (URN)978-91-7447-036-9 (ISBN)
Public defence
2010-05-12, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 16 B, Stockholm, 10:00 (English)
At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 4: In press. Paper 5: Manuscript. Available from: 2010-04-20 Created: 2010-04-06 Last updated: 2010-04-09Bibliographically approved

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Larsson, PerWallner, BjörnLindahl, ErikElofsson, Arne
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