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Normal Mode Flexible Fitting of High-Resolution Structures of Biological Molecules Toward SAXS Data.

Gorba C, Tama F - Bioinform Biol Insights (2010)

Bottom Line: We present a method to reconstruct a three-dimensional protein structure from an atomic pair distribution function derived from the scattering intensity profile from SAXS data by flexibly fitting known x-ray structures.For computational efficiency, the protein and water molecules included in the protein first hydration shell are coarse-grained.Illustrative results of our flexible fitting studies on simulated SAXS data from five different proteins are presented.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry and Biochemistry, The University of Arizona, 1041 E. Lowell Street, Tucson, AZ, 85721.

ABSTRACT
We present a method to reconstruct a three-dimensional protein structure from an atomic pair distribution function derived from the scattering intensity profile from SAXS data by flexibly fitting known x-ray structures. This method uses a linear combination of low-frequency normal modes from an elastic network description of the molecule in an iterative manner to deform the structure to conform optimally to the target pair distribution function derived from SAXS data. For computational efficiency, the protein and water molecules included in the protein first hydration shell are coarse-grained. In this paper, we demonstrate the validity of our coarse-graining approach to study SAXS data. Illustrative results of our flexible fitting studies on simulated SAXS data from five different proteins are presented.

No MeSH data available.


The initial structure of the maltodextrin binding protein (blue), the structure from which the simulated experimental data is created (silver), and the modeled structure predicted from the fitting algorithm (red) are shown. For this system, since the difference between the initial and target PDFs is small, the modeled structure does not exactly agree with the target structure; however, trends of the conformational change are predicted.
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f6-bbi-2010-043: The initial structure of the maltodextrin binding protein (blue), the structure from which the simulated experimental data is created (silver), and the modeled structure predicted from the fitting algorithm (red) are shown. For this system, since the difference between the initial and target PDFs is small, the modeled structure does not exactly agree with the target structure; however, trends of the conformational change are predicted.

Mentions: Overall, the performance of the prediction depends on the difference between initial and target P(r). Lactoferrin, is a case for which the fitting was unsuccessful. For Lactoferrin, the maxima of both P(r)s are approximately the same and only slight differences in the shape of the P(r) are noticeable (see Figure 5). Consequently, for Lactoferrin as opposed to Adenylate Kinase, for which the initial RMSD is also ∼7 Å, the information provided by the target P(r) as compared to the initial P(r) is so small that the refinement fails. Normal modes that describe the conformational change are not selected, instead, random modes are chosen leading to a faulty model. In the case of the Maltodextrin binding protein, the difference between initial and target structures measured by RMSD is rather small. In such a case, the difference in the P(r) between the two conformations is also rather minimal, and therefore one would expect that only limited information can be extracted from the refinement. Nonetheless, as illustrated by Figure 6 the overall domain motion of the protein is well captured by our approach. The direction of the displacement obtained is accurate; however, there is not sufficient information from the low-resolution data to fully reproduce the full conformational change. It indicates that even though our approach may fail to construct a model close to the final structure, insights on the directionality of conformational changes can be reliably obtained.


Normal Mode Flexible Fitting of High-Resolution Structures of Biological Molecules Toward SAXS Data.

Gorba C, Tama F - Bioinform Biol Insights (2010)

The initial structure of the maltodextrin binding protein (blue), the structure from which the simulated experimental data is created (silver), and the modeled structure predicted from the fitting algorithm (red) are shown. For this system, since the difference between the initial and target PDFs is small, the modeled structure does not exactly agree with the target structure; however, trends of the conformational change are predicted.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2901630&req=5

f6-bbi-2010-043: The initial structure of the maltodextrin binding protein (blue), the structure from which the simulated experimental data is created (silver), and the modeled structure predicted from the fitting algorithm (red) are shown. For this system, since the difference between the initial and target PDFs is small, the modeled structure does not exactly agree with the target structure; however, trends of the conformational change are predicted.
Mentions: Overall, the performance of the prediction depends on the difference between initial and target P(r). Lactoferrin, is a case for which the fitting was unsuccessful. For Lactoferrin, the maxima of both P(r)s are approximately the same and only slight differences in the shape of the P(r) are noticeable (see Figure 5). Consequently, for Lactoferrin as opposed to Adenylate Kinase, for which the initial RMSD is also ∼7 Å, the information provided by the target P(r) as compared to the initial P(r) is so small that the refinement fails. Normal modes that describe the conformational change are not selected, instead, random modes are chosen leading to a faulty model. In the case of the Maltodextrin binding protein, the difference between initial and target structures measured by RMSD is rather small. In such a case, the difference in the P(r) between the two conformations is also rather minimal, and therefore one would expect that only limited information can be extracted from the refinement. Nonetheless, as illustrated by Figure 6 the overall domain motion of the protein is well captured by our approach. The direction of the displacement obtained is accurate; however, there is not sufficient information from the low-resolution data to fully reproduce the full conformational change. It indicates that even though our approach may fail to construct a model close to the final structure, insights on the directionality of conformational changes can be reliably obtained.

Bottom Line: We present a method to reconstruct a three-dimensional protein structure from an atomic pair distribution function derived from the scattering intensity profile from SAXS data by flexibly fitting known x-ray structures.For computational efficiency, the protein and water molecules included in the protein first hydration shell are coarse-grained.Illustrative results of our flexible fitting studies on simulated SAXS data from five different proteins are presented.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemistry and Biochemistry, The University of Arizona, 1041 E. Lowell Street, Tucson, AZ, 85721.

ABSTRACT
We present a method to reconstruct a three-dimensional protein structure from an atomic pair distribution function derived from the scattering intensity profile from SAXS data by flexibly fitting known x-ray structures. This method uses a linear combination of low-frequency normal modes from an elastic network description of the molecule in an iterative manner to deform the structure to conform optimally to the target pair distribution function derived from SAXS data. For computational efficiency, the protein and water molecules included in the protein first hydration shell are coarse-grained. In this paper, we demonstrate the validity of our coarse-graining approach to study SAXS data. Illustrative results of our flexible fitting studies on simulated SAXS data from five different proteins are presented.

No MeSH data available.