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Stochastic reconstruction of protein structures from effective connectivity profiles.

Wolff K, Vendruscolo M, Porto M - PMC Biophys (2008)

Bottom Line: Structure information thus enters the folding dynamics via the effective connectivity, but the interaction is not restricted to pairs of amino acids that form native contacts, resulting in a free energy landscape which does not rely on the assumption of minimal frustration.Moreover, effective connectivity vectors can be predicted more readily from the amino acid sequence of proteins than the corresponding contact maps, thus suggesting that the stochastic protocol presented here could be effectively combined with other current methods for predicting native structures.PACS codes: 87.14.Ee.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institut für Festkörperphysik, Technische Universität Darmstadt, Hochschulstrasse 6, 64289 Darmstadt, Germany. porto@fkp.tu-darmstadt.de.

ABSTRACT
We discuss a stochastic approach for reconstructing the native structures of proteins from the knowledge of the "effective connectivity", which is a one-dimensional structural profile constructed as a linear combination of the eigenvectors of the contact map of the target structure. The structural profile is used to bias a search of the conformational space towards the target structure in a Monte Carlo scheme operating on a Calpha-chain of uniform, finite thickness. Structure information thus enters the folding dynamics via the effective connectivity, but the interaction is not restricted to pairs of amino acids that form native contacts, resulting in a free energy landscape which does not rely on the assumption of minimal frustration. Moreover, effective connectivity vectors can be predicted more readily from the amino acid sequence of proteins than the corresponding contact maps, thus suggesting that the stochastic protocol presented here could be effectively combined with other current methods for predicting native structures. PACS codes: 87.14.Ee.

No MeSH data available.


Cooperative contacts in 1e0g. Comparison between the cooperative contacts in the LYSM domain from E. coli MLTD (PDB code 1e0g) and the secondary structure assignment by STRIDE [22] (as implemented in VMD [23]). Red: β-sheet, yellow: α-helix, orange: regions in proximity of secondary structure elements, grey: other residues.
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Figure 1: Cooperative contacts in 1e0g. Comparison between the cooperative contacts in the LYSM domain from E. coli MLTD (PDB code 1e0g) and the secondary structure assignment by STRIDE [22] (as implemented in VMD [23]). Red: β-sheet, yellow: α-helix, orange: regions in proximity of secondary structure elements, grey: other residues.

Mentions: The contact map is restricted to those residues that show cooperative contacts by deleting all rows and columns without such contacts. In the EC the corresponding entries are similarly set to zero (see Figs. 1 and 2) and also ignored in the computation of the averages ⟨v(j)⟩. As amino acids that do not show the cooperative behaviour described above are disregarded, their contacts in a successful reconstruction are also not constrained and their positions restricted only by the requirement of maintaining the chain connectivity (and angles adopting allowed values). For single non-cooperative amino acids in the protein core these conditions are sufficient to provide relatively high resolution. To reduce the number of such non-cooperative amino acids an additional "secondary structure" assignment is introduced for regions in the proximity of a-helices that have the same contact pattern but lack correct chirality. This assignment method, when compared to DSSP [21] or STRIDE [22] (as implemented in VMD [23], see Fig. 1), tends to slightly overestimate the size of secondary structure elements. This effect, at least in the present context, is convenient for the reasons just mentioned. It should also be emphasised that the main objective of these admittedly ad hoc definitions lies not in the accurate assignment of secondary structure to a chain of Cα-atoms but in the capture of characteristic features of protein folds to permit the effective calculation and comparison of ECs. The actual information about specific secondary structure (i.e. whether α-helix or β-sheet) from the target is not used in the reconstruction respectively folding dynamics.


Stochastic reconstruction of protein structures from effective connectivity profiles.

Wolff K, Vendruscolo M, Porto M - PMC Biophys (2008)

Cooperative contacts in 1e0g. Comparison between the cooperative contacts in the LYSM domain from E. coli MLTD (PDB code 1e0g) and the secondary structure assignment by STRIDE [22] (as implemented in VMD [23]). Red: β-sheet, yellow: α-helix, orange: regions in proximity of secondary structure elements, grey: other residues.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2666633&req=5

Figure 1: Cooperative contacts in 1e0g. Comparison between the cooperative contacts in the LYSM domain from E. coli MLTD (PDB code 1e0g) and the secondary structure assignment by STRIDE [22] (as implemented in VMD [23]). Red: β-sheet, yellow: α-helix, orange: regions in proximity of secondary structure elements, grey: other residues.
Mentions: The contact map is restricted to those residues that show cooperative contacts by deleting all rows and columns without such contacts. In the EC the corresponding entries are similarly set to zero (see Figs. 1 and 2) and also ignored in the computation of the averages ⟨v(j)⟩. As amino acids that do not show the cooperative behaviour described above are disregarded, their contacts in a successful reconstruction are also not constrained and their positions restricted only by the requirement of maintaining the chain connectivity (and angles adopting allowed values). For single non-cooperative amino acids in the protein core these conditions are sufficient to provide relatively high resolution. To reduce the number of such non-cooperative amino acids an additional "secondary structure" assignment is introduced for regions in the proximity of a-helices that have the same contact pattern but lack correct chirality. This assignment method, when compared to DSSP [21] or STRIDE [22] (as implemented in VMD [23], see Fig. 1), tends to slightly overestimate the size of secondary structure elements. This effect, at least in the present context, is convenient for the reasons just mentioned. It should also be emphasised that the main objective of these admittedly ad hoc definitions lies not in the accurate assignment of secondary structure to a chain of Cα-atoms but in the capture of characteristic features of protein folds to permit the effective calculation and comparison of ECs. The actual information about specific secondary structure (i.e. whether α-helix or β-sheet) from the target is not used in the reconstruction respectively folding dynamics.

Bottom Line: Structure information thus enters the folding dynamics via the effective connectivity, but the interaction is not restricted to pairs of amino acids that form native contacts, resulting in a free energy landscape which does not rely on the assumption of minimal frustration.Moreover, effective connectivity vectors can be predicted more readily from the amino acid sequence of proteins than the corresponding contact maps, thus suggesting that the stochastic protocol presented here could be effectively combined with other current methods for predicting native structures.PACS codes: 87.14.Ee.

View Article: PubMed Central - HTML - PubMed

Affiliation: Institut für Festkörperphysik, Technische Universität Darmstadt, Hochschulstrasse 6, 64289 Darmstadt, Germany. porto@fkp.tu-darmstadt.de.

ABSTRACT
We discuss a stochastic approach for reconstructing the native structures of proteins from the knowledge of the "effective connectivity", which is a one-dimensional structural profile constructed as a linear combination of the eigenvectors of the contact map of the target structure. The structural profile is used to bias a search of the conformational space towards the target structure in a Monte Carlo scheme operating on a Calpha-chain of uniform, finite thickness. Structure information thus enters the folding dynamics via the effective connectivity, but the interaction is not restricted to pairs of amino acids that form native contacts, resulting in a free energy landscape which does not rely on the assumption of minimal frustration. Moreover, effective connectivity vectors can be predicted more readily from the amino acid sequence of proteins than the corresponding contact maps, thus suggesting that the stochastic protocol presented here could be effectively combined with other current methods for predicting native structures. PACS codes: 87.14.Ee.

No MeSH data available.