Residue coordination in proteins conforms to the closest packing of spheres

Bagci, Elife Zerrin; Jernigan, Robert L.; Bahar, İvet

doi:10.1016/s0032-3861(01)00427-x

Cited by 33 publications

(26 citation statements)

References 36 publications

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“…It is known that the relative orientation of side chains is an important determinant of the local (secondary structure) geometry as well as three-dimensional (3-D) (tertiary structure) topology [5,15,16]. By analyzing various families of structures, we observed that certain orientational order parameters are prominent [17].…”

Section: Introductionmentioning

confidence: 90%

Continuous anisotropic representation of coarse-grained potentials for proteins by spherical harmonics synthesis

Buchete

Straub

Thirumalai

2004

Journal of Molecular Graphics and Modelling

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Section: Introductionmentioning

confidence: 90%

Continuous anisotropic representation of coarse-grained potentials for proteins by spherical harmonics synthesis

Buchete

Straub

Thirumalai

2004

Journal of Molecular Graphics and Modelling

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“…It lacks the parity problem and models real protein conformations with good quality (see [38], where it was shown, that the FCC lattice can model protein conformations with coordinate root mean square deviation of 1.78 Å , whereas the cubic lattice achieves a deviation of 2.84 Å there). Recently, [13,14] have shown that neighborhood of amino acids in proteins closely resembles a distorted FCC-lattice, and that the FCC is best suited for modeling proteins. This is an immediate effect of hydrophobic packing.…”

Section: Contribution Of the Paper: A Constraint-based Approachmentioning

confidence: 99%

A Constraint-Based Approach to Fast and Exact Structure Prediction in Three-Dimensional Protein Models

Backofen

Will

2006

Constraints

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Simplified protein models are used for investigating general properties of proteins and principles of protein folding. Furthermore, they are suited for hierarchical approaches to protein structure prediction. A well known protein model is the HP-model of Lau and Dill [Lau, K. F., & Dill, K. A. (1989)]. A lattice statistical mechanics model of the conformational and sequence spaces of proteins. Macromolecules, 22, 3986 -3997) which models the important aspect of hydrophobicity. One can define the HP-model for various lattices, among them two-dimensional and three-dimensional ones. Here, we investigate the three-dimensional case. The main motivation for studying simplified protein models is to be able to predict model structures much more quickly and more accurately than is possible for real proteins. However, up to now there was a dilemma: the algorithmically tractable, simple protein models can not model real protein structures with good quality and introduce strong artifacts.We present a constraint-based method that largely improves this situation. It outperforms all existing approaches for lattice protein folding in HP-models. This approach is the first one that can be applied to two three-dimensional lattices, namely the cubic lattice and the face-centered-cubic (FCC) lattice. Moreover, it is the only exact method for the FCC lattice. The ability to use the FCC lattice is a significant improvement over the cubic lattice. The key to our approach is the ability to compute maximally compact sets of points (used as hydrophobic cores), which we accomplish for the first time for the FCC lattice.

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“…Previous studies have shown that the relative orientation and packing of side chains in proteins is an important determinant of the local (secondary structure) geometry as well as three‐dimensional (tertiary structure) topology (Bahar and Jernigan 1996; Bagci et al 2002a,b). By analyzing various families of protein structures, we had previously shown that certain orientational order parameters are prominent (Buchete et al 2003).…”

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confidence: 99%

Orientational potentials extracted from protein structures improve native fold recognition

2004

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We develop coarse-grained, distance-and orientation-dependent statistical potentials from the growing protein structural databases. For protein structural classes (␣, ␤, and ␣/␤), a substantial number of backbone-backbone and backbone-side-chain contacts stabilize the native folds. By taking into account the importance of backbone interactions with a virtual backbone interaction center as the 21st anisotropic site, we construct a 21 × 21 interaction scheme. The new potentials are studied using spherical harmonics analysis (SHA) and a smooth, continuous version is constructed using spherical harmonic synthesis (SHS). Our approach has the following advantages: (1) The smooth, continuous form of the resulting potentials is more realistic and presents significant advantages for computational simulations, and (2) with SHS, the potential values can be computed efficiently for arbitrary coordinates, requiring only the knowledge of a few spherical harmonic coefficients. The performance of the new orientation-dependent potentials was tested using a standard database of decoy structures. The results show that the ability of the new orientationdependent potentials to recognize native protein folds from a set of decoy structures is strongly enhanced by the inclusion of anisotropic backbone interaction centers. The anisotropic potentials can be used to develop realistic coarse-grained simulations of proteins, with direct applications to protein design, folding, and aggregation.

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Residue coordination in proteins conforms to the closest packing of spheres

Cited by 33 publications

References 36 publications

Continuous anisotropic representation of coarse-grained potentials for proteins by spherical harmonics synthesis

Continuous anisotropic representation of coarse-grained potentials for proteins by spherical harmonics synthesis

A Constraint-Based Approach to Fast and Exact Structure Prediction in Three-Dimensional Protein Models

Orientational potentials extracted from protein structures improve native fold recognition

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