Information content of molecular structures.
For a completely enumerated set of conformers of a macromolecule or for exhaustive lattice walks of model polymers it is straightforward to use Shannon information theory to deduce the information content of the ensemble. It is also practicable to develop numerical measures of the information content of sets of exact distance constraints applied to specific conformational ensembles. We examine the effects of experimental uncertainties by considering "noisy" constraints. The introduction of noise requires additional assumptions about noise distribution and conformational clustering protocols that make the problem of measuring information content more complex. We make use of a standard concept in communication theory, the "noise sphere," to link uncertainty in measurements to information loss. Most of our numerical results are derived from two-dimensional lattice ensembles. Expressing results in terms of information per degree of freedom removes almost all of the chain length dependence. We also explore off-lattice polyalanine chains that yield surprisingly similar results.
Sullivan
David C
DC
Department of Pharmaceutical Chemistry, University of California, San Francisco, California 94143-2240, USA.
Aynechi
Tiba
T
Voelz
Vincent A
VA
Kuntz
Irwin D
ID
D000595:Amino Acid Sequence; D001665:Binding Sites; D003461:Crystallography / Q000379:methods*; D030562:Databases, Protein; D019281:Dimerization; D016247:Information Storage and Retrieval / Q000379:methods*; D046911:Macromolecular Substances; D008956:Models, Chemical; D008958:Models, Molecular; D015233:Models, Statistical; D008968:Molecular Conformation; D008969:Molecular Sequence Data; D015394:Molecular Structure; D010455:Peptides / Q000737:chemistry*; D011487:Protein Conformation; D011506:Proteins / Q000737:chemistry*
D046911:Macromolecular Substances; D010455:Peptides; D011506:Proteins; C019529:polyalanine