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An estimate of the numbers and density of low-energy structures (or decoys) in the conformational landscape of proteins.

Vadivel K, Namasivayam G - PLoS ONE (2009)

Bottom Line: We show that the number of native-like structures for a polypeptide is, in general, an exponential function of its sequence length.The density of these structures in conformational space remains more or less constant and all the increase appears to come from an expansion in the volume of the space.These results are consistent with earlier reports that were based on other models and techniques.

View Article: PubMed Central - PubMed

Affiliation: Centre of Advanced Study in Crystallography & Biophysics, University of Madras, Tamilnadu, India.

ABSTRACT

Background: The conformational energy landscape of a protein, as calculated by known potential energy functions, has several minima, and one of these corresponds to its native structure. It is however difficult to comprehensively estimate the actual numbers of low energy structures (or decoys), the relationships between them, and how the numbers scale with the size of the protein.

Methodology: We have developed an algorithm to rapidly and efficiently identify the low energy conformers of oligo peptides by using mutually orthogonal Latin squares to sample the potential energy hyper surface. Using this algorithm, and the ECEPP/3 potential function, we have made an exhaustive enumeration of the low-energy structures of peptides of different lengths, and have extrapolated these results to larger polypeptides.

Conclusions and significance: We show that the number of native-like structures for a polypeptide is, in general, an exponential function of its sequence length. The density of these structures in conformational space remains more or less constant and all the increase appears to come from an expansion in the volume of the space. These results are consistent with earlier reports that were based on other models and techniques.

Show MeSH
Unique structures identified with AMBER force field.The number of mutually dissimilar structures found at different rmsd cutoffs for each peptide in 10,000 MOLS structures using the AMBER force field.
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pone-0005148-g006: Unique structures identified with AMBER force field.The number of mutually dissimilar structures found at different rmsd cutoffs for each peptide in 10,000 MOLS structures using the AMBER force field.

Mentions: To evaluate the effect of the force field, all the calculations were repeated with the AMBER potential function [38]. The results were remarkably similar to those obtained above with ECEPP/3. The numbers of unique structures identified for each sequence length with AMBER parameters at different rmsd cut-off values are shown in Figure 6. The plot is a replica of Figure 4. Once again, the increase in the number of low energy structures at lower rmsd cutoff (<1.3 Å) is linear, while at larger cutoff (>1.3 Å) the number increases exponentially with sequence length. We thus conclude that the conformational landscape of a protein consists of approximately exp(n) low energy structures, or decoys, where n is the sequence length.


An estimate of the numbers and density of low-energy structures (or decoys) in the conformational landscape of proteins.

Vadivel K, Namasivayam G - PLoS ONE (2009)

Unique structures identified with AMBER force field.The number of mutually dissimilar structures found at different rmsd cutoffs for each peptide in 10,000 MOLS structures using the AMBER force field.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2663821&req=5

pone-0005148-g006: Unique structures identified with AMBER force field.The number of mutually dissimilar structures found at different rmsd cutoffs for each peptide in 10,000 MOLS structures using the AMBER force field.
Mentions: To evaluate the effect of the force field, all the calculations were repeated with the AMBER potential function [38]. The results were remarkably similar to those obtained above with ECEPP/3. The numbers of unique structures identified for each sequence length with AMBER parameters at different rmsd cut-off values are shown in Figure 6. The plot is a replica of Figure 4. Once again, the increase in the number of low energy structures at lower rmsd cutoff (<1.3 Å) is linear, while at larger cutoff (>1.3 Å) the number increases exponentially with sequence length. We thus conclude that the conformational landscape of a protein consists of approximately exp(n) low energy structures, or decoys, where n is the sequence length.

Bottom Line: We show that the number of native-like structures for a polypeptide is, in general, an exponential function of its sequence length.The density of these structures in conformational space remains more or less constant and all the increase appears to come from an expansion in the volume of the space.These results are consistent with earlier reports that were based on other models and techniques.

View Article: PubMed Central - PubMed

Affiliation: Centre of Advanced Study in Crystallography & Biophysics, University of Madras, Tamilnadu, India.

ABSTRACT

Background: The conformational energy landscape of a protein, as calculated by known potential energy functions, has several minima, and one of these corresponds to its native structure. It is however difficult to comprehensively estimate the actual numbers of low energy structures (or decoys), the relationships between them, and how the numbers scale with the size of the protein.

Methodology: We have developed an algorithm to rapidly and efficiently identify the low energy conformers of oligo peptides by using mutually orthogonal Latin squares to sample the potential energy hyper surface. Using this algorithm, and the ECEPP/3 potential function, we have made an exhaustive enumeration of the low-energy structures of peptides of different lengths, and have extrapolated these results to larger polypeptides.

Conclusions and significance: We show that the number of native-like structures for a polypeptide is, in general, an exponential function of its sequence length. The density of these structures in conformational space remains more or less constant and all the increase appears to come from an expansion in the volume of the space. These results are consistent with earlier reports that were based on other models and techniques.

Show MeSH