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How do side chains orient globally in protein structures?

ABSTRACT: An angle Omega is defined to serve as a metric for global side-chain orientations, which reflects the orientation of the side chain relative to the radial vector from the center of the protein to an amino acid. The side-chain orientations of buried residues exhibit characteristically different orientations than do exposed residues, in both monomeric and dimeric structures. Overall, buried side chains point mostly inward, whereas surface side chains tend to point outward from the surface. This difference in behavior also correlates well with the residue hydrophobicity; so a global side-chain orientation can be viewed as a direct structural manifestation of hydrophobicity. When various solvent-accessible layers are considered, the behavior is relatively continuous between centrally located and exposed residues. In the case of interfacial residues between subunits, there are statistically significant differences between exposed residues and interface residues for ALA, ARG, ASN, ASP, GLU, HIS, LYS, THR, VAL, MET, PRO, and overall the interface residues have an increased tendency to point inward. Presumably, these substantial differences in orientations of side chains may be a manifestation of hydrophobic forces.

SUBMITTER: Yan A

PROVIDER: S-EPMC4417611 | biostudies-literature | 2005 Nov

REPOSITORIES: biostudies-literature

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How do side chains orient globally in protein structures?

Yan Aimin A Jernigan Robert L RL

Proteins 20051101 3

An angle Omega is defined to serve as a metric for global side-chain orientations, which reflects the orientation of the side chain relative to the radial vector from the center of the protein to an amino acid. The side-chain orientations of buried residues exhibit characteristically different orientations than do exposed residues, in both monomeric and dimeric structures. Overall, buried side chains point mostly inward, whereas surface side chains tend to point outward from the surface. This di ...[more]

PMID: 16152644

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Project description:INTRODUCTION: The accurate packing of protein side chains is important for many computational biology problems, such as ab initio protein structure prediction, homology modelling, and protein design and ligand docking applications. Many of existing solutions are modelled as a computational optimisation problem. As well as the design of search algorithms, most solutions suffer from an inaccurate energy function for judging whether a prediction is good or bad. Even if the search has found the lowest energy, there is no certainty of obtaining the protein structures with correct side chains. METHODS: We present a side-chain modelling method, pacoPacker, which uses a parallel ant colony optimisation strategy based on sharing a single pheromone matrix. This parallel approach combines different sources of energy functions and generates protein side-chain conformations with the lowest energies jointly determined by the various energy functions. We further optimised the selected rotamers to construct subrotamer by rotamer minimisation, which reasonably improved the discreteness of the rotamer library. RESULTS: We focused on improving the accuracy of side-chain conformation prediction. For a testing set of 442 proteins, 87.19% of X1 and 77.11% of X12 angles were predicted correctly within 40° of the X-ray positions. We compared the accuracy of pacoPacker with state-of-the-art methods, such as CIS-RR and SCWRL4. We analysed the results from different perspectives, in terms of protein chain and individual residues. In this comprehensive benchmark testing, 51.5% of proteins within a length of 400 amino acids predicted by pacoPacker were superior to the results of CIS-RR and SCWRL4 simultaneously. Finally, we also showed the advantage of using the subrotamers strategy. All results confirmed that our parallel approach is competitive to state-of-the-art solutions for packing side chains. CONCLUSIONS: This parallel approach combines various sources of searching intelligence and energy functions to pack protein side chains. It provides a frame-work for combining different inaccuracy/usefulness objective functions by designing parallel heuristic search algorithms.

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How do side chains orient globally in protein structures?

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How do side chains orient globally in protein structures?

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