title: Free energy landscape of a biomolecule in dihedral principal component space: sampling convergence and correspondence between structures and minima.
abstract: Dihedral principal component analysis (dPCA) has recently been developed and shown to display complex features of the free energy landscape of a biomolecule that may be absent in the free energy landscape plotted in principal component space due to mixing of internal and overall rotational motion that can occur in principal component analysis (PCA) [Mu et al., Proteins: Struct Funct Bioinfo 2005;58:45-52]. Another difficulty in the implementation of PCA is sampling convergence, which we address here for both dPCA and PCA using a tetrapeptide as an example. We find that for both methods the sampling convergence can be reached over a similar time. Minima in the free energy landscape in the space of the two largest dihedral principal components often correspond to unique structures, though we also find some distinct minima to correspond to the same structure.
authors.affiliation: Department of Chemistry, University of Nevada, Reno, Nevada 89557, USA.
authors.forename: Gia G
authors.initials: GG
authors.lastname: Maisuradze
authors.forename: David M
authors.initials: DM
authors.lastname: Leitner
mesh_terms: D003198:Computer Simulation; D008958:Models, Molecular; D010455:Peptides / Q000737:chemistry; D025341:Principal Component Analysis / Q000379:methods; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*; D013816:Thermodynamics
chemical_list: D010455:Peptides; D011506:Proteins