Generation of atomic four-body statistical potentials derived from the delaunay tessellation of protein structures.
Delaunay tessellation of the atomic coordinates for a crystallographic protein structure yields an aggregate of non-overlapping and space-filling irregular tetrahedral simplices. The vertices of each simplex objectively identify a quadruplet of nearest neighbor atoms in the protein. Here we apply Delaunay tessellation to 1417 high-resolution structures of single chains that share low sequence identity, for the purpose of determining the relative frequencies of occurrence for all possible nearest neighbor atomic quadruplet types. Alternative distributions are explored by varying two fundamental parameters: atomic alphabet selection and cutoff length for admissible simplex edges. The distributions are then converted to four-body potential functions by implementing the inverted Boltzmann principle, which requires calculating the distribution of the reference state. Two alternative definitions for the reference state are presented, which introduces a third parameter, and we derive and compare an array of such potential functions. These knowledge-based statistical potentials based on higher-order interactions complement and generalize the more commonly encountered atom-pair potentials, for which a number of approaches are described in the literature.
Laboratory for Structural Bioinformatics, School of Systems Biology, George Mason University, Manassas, VA 20110, USA. mmasso@gmu.edu
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D008956:Models, Chemical; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*
D011506:Proteins