title: Density-cluster NMA: A new protein decomposition technique for coarse-grained normal mode analysis.
abstract: Normal mode analysis has emerged as a useful technique for investigating protein motions on long time scales. This is largely due to the advent of coarse-graining techniques, particularly Hooke's Law-based potentials and the rotational-translational blocking (RTB) method for reducing the size of the force-constant matrix, the Hessian. Here we present a new method for domain decomposition for use in RTB that is based on hierarchical clustering of atomic density gradients, which we call Density-Cluster RTB (DCRTB). The method reduces the number of degrees of freedom by 85-90% compared with the standard blocking approaches. We compared the normal modes from DCRTB against standard RTB using 1-4 residues in sequence in a single block, with good agreement between the two methods. We also show that Density-Cluster RTB and standard RTB perform well in capturing the experimentally determined direction of conformational change. Significantly, we report superior correlation of DCRTB with B-factors compared with 1-4 residue per block RTB. Finally, we show significant reduction in computational cost for Density-Cluster RTB that is nearly 100-fold for many examples.
authors.affiliation: Medical Scientist Training Program, University of Wisconsin-Madison, Madison, Wisconsin, USA.
authors.forename: Omar N A
authors.initials: ON
authors.lastname: Demerdash
authors.forename: Julie C
authors.initials: JC
authors.lastname: Mitchell
mesh_terms: D016000:Cluster Analysis; D019295:Computational Biology; D030562:Databases, Protein; D008956:Models, Chemical; D008958:Models, Molecular; D011487:Protein Conformation; D017434:Protein Structure, Tertiary; D011506:Proteins / Q000737:chemistry*
chemical_list: D011506:Proteins