Delaunay Tessellation of Proteins: Four Body Nearest-Neighbor Propensities of Amino Acid Residues

Singh, Raj Kumar; Tropsha, Alexander; Vaisman, Iosif I.

doi:10.1089/cmb.1996.3.213

Cited by 160 publications

(136 citation statements)

References 29 publications

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“…It is also applied to binding site identification (Peters et al, 1996), molecular mesh generation (Akkiraju & Edelsbrunner, 1996), and electrostatics calculations based on boundary elements (Liang & Subramaniam, 1997). Other computational geometry methods applied to biological questions include unweighted Delaunay tetrahedra for analysis of protein structures (Singh et al, 1996) and for recognition of protein folds in sequence threading (Munson & Singh, 1997). A recent advance in characterization of protein pockets is the discrete flow method used in conjunction with alphashape theory ; it has been applied to estimation of hydration changes due to osmotic stress of antithrombin , identification of potential binding sites for calcium ions in the Gla domain of prothrombin , and identification of the D-site binding pocket thought to contain the proton acceptor of tyrosine radical in photosystem I1 (Kim et al, 1997).…”

Section: Pocket and Cavity Analysismentioning

confidence: 99%

Anatomy of protein pockets and cavities: Measurement of binding site geometry and implications for ligand design

1998

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Identification and size characterization of surface pockets and occluded cavities are initial steps in protein structurebased ligand design. A new program, CAST, for automatically locating and measuring protein pockets and cavities, is based on precise computational geometry methods, including alpha shape and discrete flow theory. CAST identifies and measures pockets and pocket mouth openings, as well as cavities. The program specifies the atoms lining pockets, pocket openings, and buried cavities; the volume and area of pockets and cavities; and the area and circumference of mouth openings. CAST analysis of over 100 proteins has been carried out; proteins examined include a set of SI monomeric enzyme-ligand structures, several elastase-inhibitor complexes, the pockets and cavities in protein crystal structures and quantifying their size. The method is a computational geometry treatment of complex shapes, based on alpha shape and discrete flow theory, and a related suite of programs,

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Section: Pocket and Cavity Analysismentioning

confidence: 99%

Anatomy of protein pockets and cavities: Measurement of binding site geometry and implications for ligand design

1998

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“…Using a geometric accounting based on the Delaunay tessellation for three-and four-body interactions, Singh et al (1996) suggested that four-body interactions may indeed be important. Such multi-body contributions to protein potentials are reasonable from a geometric point of view, if we approximate each residue as a sphere centered on its C" location.…”

Section: P J Munson and R K Singhmentioning

confidence: 99%

Statistical significance of hierarchical multi‐body potentials based on Delaunay tessellation and their application in sequence‐structure alignment

Munson

Singh

1997

Protein Science

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Statistical potentials based on pairwise interactions between C" atoms are commonly used in protein threadindfoldrecognition attempts. Inclusion of higher order interaction is a possible means of improving the specificity of these potentials. Delaunay tessellation of the C"-atom representation of protein structure has been suggested as a means of defining multi-body interactions.A large number of parameters are required to define all four-body interactions of 20 amino acid types (204 = 160,000). Assuming that residue order within a four-body contact is irrelevant reduces this to a manageable 8,855 parameters, using a nonredundant dataset of 608 protein structures.Three lines of evidence support the significance and utility of the four-body potential for sequence-structure matching. First, compared to the four-body model, all lower-order interaction models (three-body, two-body, one-body) are found statistically inadequate to explain the frequency distribution of residue contacts.Second, coherent patterns of interaction are seen in a graphic presentation of the four-body potential. Many patterns have plausible biophysical explanations and are consistent across sets of residues sharing certain properties (e.g., size, hydrophobicity, or charge).Third, the utility of the multi-body potential is tested on a test set of 12 same-length pairs of proteins of known structure for two protocols: Sequence-recognizes-structure, where a query sequence is threaded (without gap) through the native and a non-native structure; and structure-recognizes-sequence, where a query structure is threaded by its native and another non-native sequence. Using cross-validated training, protein sequences correctly recognized their native structure in all 24 cases. Conversely, structures recognized the native sequence in 23 of 24 cases. Further, the score differences between correct and decoy structures increased significantly using the three-or four-body potential compared to potentials of lower order.Keywords: Delaunay tessellation; fold-recognition; high-order interactions; multi-body potential; protein folding; threading potential Increasing attention has been paid to developing empirical potentials for use in de novo folding of a protein sequence and recognition of its correct fold in a library of folds. With a few exceptions, these efforts seek to measure the suitability of the three-dimensional (3D) environment of each residue or to evaluate contributions of pairwise interactions between residues based on their fixed backbone positions. Using such potentials, it is possible to scan a large database of folds with an amino-acid sequence and generate reasonable predictions of the 3D structure for that sequence. The ability of these threading methods to accurately distinguish the Reprint requests to: Peter J.

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“…For the first time, we have used Delaunay triangulation for tessellation of protein surface atoms to measure surface complementarity. Delaunay's triangulation has been previously used on proteins in a different application for creation of simplices to evaluate four-body nearest neighbor propensities of amino acids [25]. A related tessellation technique, Voronoi polyhedra and alpha-complex have been used to measure atom packing, but the implementation is different.…”

Section: Discussionmentioning

confidence: 99%

New measures for estimating surface complementarity and packing at protein–protein interfaces

Mitra¹,

Pal²

2010

FEBS Letters

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a b s t r a c tA number of methods exist that use different approaches to assess geometric properties like the surface complementarity and atom packing at the protein-protein interface. We have developed two new and conceptually different measures using the Delaunay tessellation and interface slice selection to compute the surface complementarity and atom packing at the protein-protein interface in a straightforward manner. Our measures show a strong correlation among themselves and with other existing measures, and can be calculated in a highly time-efficient manner. The measures are discriminative for evaluating biological, as well as non-biological protein-protein contacts, especially from large protein complexes and large-scale structural studies (http://pallab. serc.iisc.ernet.in/nip_nsc).

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Delaunay Tessellation of Proteins: Four Body Nearest-Neighbor Propensities of Amino Acid Residues

Cited by 160 publications

References 29 publications

Anatomy of protein pockets and cavities: Measurement of binding site geometry and implications for ligand design

Anatomy of protein pockets and cavities: Measurement of binding site geometry and implications for ligand design

Statistical significance of hierarchical multi‐body potentials based on Delaunay tessellation and their application in sequence‐structure alignment

New measures for estimating surface complementarity and packing at protein–protein interfaces

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