Determinants of backbone packing in globular proteins: an analysis of spatial neighbours

Amino acid interaction preferences in proteins

Understanding the key factors that influence the interaction preferences of amino acids in the folding of proteins have remained a challenge. Here we present a knowledge-based approach for determining the effective interactions between amino acids based on amino acid type, their secondary structure, and the contact based environment that they find themselves in the native state structure as measured by their number of neighbors. We find that the optimal information is approximately encoded in a 60 x 60 matrix describing the 20 types of amino acids in three distinct secondary structures (helix, beta strand, and loop). We carry out a clustering scheme to understand the similarity between these interactions and to elucidate a nonredundant set. We demonstrate that the inferred energy parameters can be used for assessing the fit of a given sequence into a putative native state structure.

Accessibility and partner number of protein residues, their relationship and a webserver, ContPlot for their display

Background

Depending on chemical features residues have preferred locations – interior or exterior – in protein structures, which also determine how many other residues are found around them. The close packing of residues is the hallmark of protein interior and protein-protein interaction sites.

Results

The average values of accessible surface area (ASA) and partner number (PN, the number of other residues within a distance of 4.5 Å from any atom of a given residue) of different residues have been determined and a webserver, ContPlot has been designed to display these values (relative to the average values) along the protein sequence. This would be useful to visually identify residues that are densely packed, or those involved in protein-protein interactions. The skewness observed in the distribution of PNs is indicative of the hydrophobic or hydrophilic nature of the residue. The variation of ASA with PN can be analytically expressed in terms of a cubic equation. These equations (one for each residue) can be used to estimate the ASA of a polypeptide chain using the PNs of the individual residues in the structure.

Conclusion

The atom-based PNs (obtained by counting surrounding atoms) are highly correlated to the residue-based PN, indicating that the latter can adequately capture the atomic details of packing. The average values of ASA and PN associated with each residue should be useful in protein structure prediction or fold-recognition algorithm. ContPlot would provide a handy tool to assess the importance of a residue in the protein structure or interaction site.

Quantifying the accessible surface area of protein residues in their local environment

The quantification of the packing of residues in proteins and docking of ligands to macromolecules is important in understanding protein stability and drug design. The number of atoms in contact (within a distance of 4.5 A) can be used to describe the local environment of a residue. As this number increases, the accessible surface area (ASA) of the residue decreases exponentially and the variation can be described in terms of an exponential equation of the form y = a(1)exp(-x/a(2)), each residue having its own set of parameters a(1) and a(2), which also depend on whether the whole residue or just the side chain is considered. Hydrophobic and hydrophilic residues can be distinguished on the basis of both the average number of surrounding atoms and the variation of ASA. For a given number of partner atoms, a comparison of the observed ASA with the expected value obtained from the equation provides a method of assessing the goodness of packing of the residue in a protein structure or its importance in the binding of a ligand. The equation provides a method to estimate the ASA of a protein molecule and the average relative accessibilities of different residues, the latter being inversely correlated with hydrophobicity values.

Hydrophilic framework in proteins?

The spatial neighborhood composition of residues was determined in a 511-structure set by taking only side-chain atoms into account to generate a hydrophobicity scale. This scale is symmetrical and has been divided into seven functional groups. Hydrophobic (LIVFMCAWYG) and hydrophilic (PTHSQRNKED) residues obey an equipartition rule: not only are they found in equal proportions, but they play equivalent roles in many of their properties. The nearest neighbors of all residues are always hydrophilic. However, hydrophobic residues are mostly surrounded by other hydrophobic residues located at a peak at 3.9 A, while hydrophilic residues show three peaks at 5.0, 6.5, and 8.0 A, suggesting a hydrophilic structural framework. This leads us to question the importance of hydrophobic cores believed to be at the origin of protein folding.