title: Dihedral angle principal component analysis of molecular dynamics simulations.
abstract: It has recently been suggested by Mu et al. [Proteins 58, 45 (2005)] to use backbone dihedral angles instead of Cartesian coordinates in a principal component analysis of molecular dynamics simulations. Dihedral angles may be advantageous because internal coordinates naturally provide a correct separation of internal and overall motion, which was found to be essential for the construction and interpretation of the free energy landscape of a biomolecule undergoing large structural rearrangements. To account for the circular statistics of angular variables, a transformation from the space of dihedral angles {phi(n)} to the metric coordinate space {x(n)=cos phi(n),y(n)=sin phi(n)} was employed. To study the validity and the applicability of the approach, in this work the theoretical foundations underlying the dihedral angle principal component analysis (dPCA) are discussed. It is shown that the dPCA amounts to a one-to-one representation of the original angle distribution and that its principal components can readily be characterized by the corresponding conformational changes of the peptide. Furthermore, a complex version of the dPCA is introduced, in which N angular variables naturally lead to N eigenvalues and eigenvectors. Applying the methodology to the construction of the free energy landscape of decaalanine from a 300 ns molecular dynamics simulation, a critical comparison of the various methods is given.
authors.affiliation: Institute of Physical and Theoretical Chemistry, J. W. Goethe University, Max-von-Laue-Strasse 7, D-60438 Frankfurt, Germany.
authors.forename: Alexandros
authors.initials: A
authors.lastname: Altis
authors.forename: Phuong H
authors.initials: PH
authors.lastname: Nguyen
authors.forename: Rainer
authors.initials: R
authors.lastname: Hegger
authors.forename: Gerhard
authors.initials: G
authors.lastname: Stock
mesh_terms: D000409:Alanine / Q000737:chemistry; D000465:Algorithms; D001703:Biophysics / Q000379:methods; D002627:Chemistry, Physical / Q000379:methods*; D003198:Computer Simulation; D008956:Models, Chemical; D008958:Models, Molecular; D015233:Models, Statistical; D008962:Models, Theoretical; D008968:Molecular Conformation; D010455:Peptides / Q000737:chemistry; D025341:Principal Component Analysis; D011487:Protein Conformation; D013816:Thermodynamics
chemical_list: D010455:Peptides; D000409:Alanine