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Prediction, modeling, and refinement of protein structure
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
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.
Keyword [en]
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
Biochemistry
Identifiers
URN: urn:nbn:se:su:diva-38253ISBN: 978-91-7447-036-9 (print)OAI: oai:DiVA.org:su-38253DiVA: diva2:308468
Public defence
2010-05-12, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 16 B, Stockholm, 10:00 (English)
Opponent
Supervisors
Note
At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 4: In press.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
List of papers
1. Using multiple templates to improve quality of homology models in automated homology modeling.
Open this publication in new window or tab >>Using multiple templates to improve quality of homology models in automated homology modeling.
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
Keyword
Automation, Models; Molecular, Protein Conformation, Protein Folding, Proteins/chemistry, Sequence Homology; Amino Acid
Identifiers
urn:nbn:se:su:diva-14852 (URN)000256166600004 ()18441233 (PubMedID)
Available from: 2008-11-20 Created: 2008-11-20 Last updated: 2014-11-10Bibliographically approved
2. Assessment of global and local model quality in CASP8 using Pcons and ProQ
Open this publication in new window or tab >>Assessment of global and local model quality in CASP8 using Pcons and ProQ
2009 (English)In: Proteins: Structure, Function, and Genetics, ISSN 0887-3585, E-ISSN 1097-0134, Vol. 77, no 9, 167-172 p.Article in journal (Refereed) Published
Abstract [en]

Model Quality Assessment Programs (MQAPs) are programs developed to rank protein models. These methods can be trained to predict the overall global quality of a model or what local regions in a model that are likely to be incorrect. In CASP8, we participated with two predictors that predict both global and local quality using either consensus information, Pcons, or purely structural information, ProQ. Consistently with results in previous CASPs, the best performance in CASP8 was obtained using the Pcons method. Furthermore, the results show that the modification introduced into Pcons for CASP8 improved the predictions against GDT_TS and now a correlation coefficient above 0.9 is achieved, whereas the correlation for ProQ is about 0.7. The correlation is better for the easier than for the harder targets, but it is not below 0.5 for a single target and below 0.7 only for three targets. The correlation coefficient for the best local quality MQAP is 0.68 showing that there is still clear room for improvement within this area. We also detect that Pcons still is not always able to identify the best model. However, we show that using a linear combination of Pcons and ProQ it is possible to select models that are better than the models from the best single server. In particular, the average quality over the hard targets increases by about 6% compared with using Pcons alone.

Keyword
quality assessment, MQAP, consensus
National Category
Bioinformatics and Systems Biology
Research subject
Biochemistry with Emphasis on Theoretical Chemistry
Identifiers
urn:nbn:se:su:diva-34572 (URN)10.1002/prot.22476 (DOI)000272244700019 ()19544566 (PubMedID)
Available from: 2010-01-11 Created: 2010-01-11 Last updated: 2017-12-12Bibliographically approved
3. Implementation of the CHARMM Force Field in GROMACS: Analysis of Protein Stability Effects from Correction Maps, Virtual Interaction Sites, and Water Models
Open this publication in new window or tab >>Implementation of the CHARMM Force Field in GROMACS: Analysis of Protein Stability Effects from Correction Maps, Virtual Interaction Sites, and Water Models
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2010 (English)In: Journal of Chemical Theory and Computation, ISSN 1549-9618, E-ISSN 1549-9626, Vol. 6, no 2, 459-466 p.Article in journal (Refereed) Published
Abstract [en]

CHARMM27 is a widespread and popular force field for biomolecular simulation, and several recent algorithms such as implicit solvent models have been developed specifically for it. We have here implemented the CHARMM force field and all necessary extended functional forms in the GROMACS molecular simulation package, to make CHARMM-specific features available and to test them in combination with techniques for extended time steps, to make all major force fields available for comparison studies in GROMACS, and to test various solvent model optimizations, in particular the effect of Lennard-Jones interactions on hydrogens. The implementation has full support both for CHARMM-specific features such as multiple potentials over the same dihedral angle and the grid-based energy correction map on the , ψ protein backbone dihedrals, as well as all GROMACS features such as virtual hydrogen interaction sites that enable 5 fs time steps. The medium-to-long time effects of both the correction maps and virtual sites have been tested by performing a series of 100 ns simulations using different models for water representation, including comparisons between CHARMM and traditional TIP3P. Including the correction maps improves sampling of near native-state conformations in our systems, and to some extent it is even able to refine distorted protein conformations. Finally, we show that this accuracy is largely maintained with a new implicit solvent implementation that works with virtual interaction sites, which enables performance in excess of 250 ns/day for a 900-atom protein on a quad-core desktop computer.

Place, publisher, year, edition, pages
Washington: American Chemical Society, 2010
National Category
Chemical Sciences
Identifiers
urn:nbn:se:su:diva-38245 (URN)10.1021/ct900549r (DOI)000274838800012 ()
Available from: 2010-04-06 Created: 2010-04-06 Last updated: 2017-12-12Bibliographically approved
4. A High-Performance Parallel-Generalized Born Implementation Enabled by Tabulated Interaction Rescaling
Open this publication in new window or tab >>A High-Performance Parallel-Generalized Born Implementation Enabled by Tabulated Interaction Rescaling
2010 (English)In: Journal of Computational Chemistry, ISSN 0192-8651, E-ISSN 1096-987X, Vol. 31, no 14, 2593-2600 p.Article in journal (Refereed) Published
Abstract [en]

Implicit solvent representations, in general, and generalized Born models, in particular, provide an attractive way to reduce the number of interactions and degrees of freedom in a system. The instantaneous relaxation of the dielectric shielding provided by an implicit solvent model can be extremely efficient for high-throughput and Monte Carlo studies, and a reduced system size can also remove a lot of statistical noise. Despite these advantages, it has been difficult for generalized Born implementations to significantly outperform optimized explicit-water simulations due to more complex functional forms and the two extra interaction stages necessary to calculate Born radii and the derivative chain rule terms contributing to the force. Here, we present a method that uses a rescaling transformation to make the standard generalized Born expression a function of a single variable, which enables an efficient tabulated implementation on any modern CPU hardware. The total performance is within a factor 2 of simulations in vacuo. The algorithm has been implemented in Gromacs, including single-instruction multiple-data acceleration, for three different Born radius models and corresponding chain rule terms. We have also adapted the model to work with the virtual interaction sites commonly used for hydrogens to enable long-time steps, which makes it possible to achieve a simulation performance of 0.86 μs/day for BBA5 with 1-nm cutoff on a single quad-core desktop processor. Finally, we have also implemented a set of streaming kernels without neighborlists to accelerate the non-cutoff setup occasionally used for implicit solvent simulations of small systems.

Keyword
generalized born, tabulation, molecular dynamics
National Category
Natural Sciences
Identifiers
urn:nbn:se:su:diva-38246 (URN)10.1002/jcc.21552 (DOI)000282309800007 ()
Available from: 2010-04-06 Created: 2010-04-06 Last updated: 2017-12-12Bibliographically approved
5. Comparison of the efficiency of different protein structure refinement techniques
Open this publication in new window or tab >>Comparison of the efficiency of different protein structure refinement techniques
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2010 (English)Manuscript (preprint) (Other academic)
Identifiers
urn:nbn:se:su:diva-38247 (URN)
Available from: 2010-04-06 Created: 2010-04-06 Last updated: 2014-11-10Bibliographically approved

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