AJP - Cell Physiology, Vol 261, Issue 2 C376-C386, Copyright © 1991 by American Physiological Society
Constrained optimization and protein structure determination
J. Eisenfeld, S. Vajda, I. Sugar and C. DeLisi
Department of Biomathematical Sciences, Mount Sinai School of Medicine, New York, New York 10029.
Energy minimization is one of the main approaches to the computational
determination of macromolecular structure. Due to the approximations in the
empirical free-energy functions and due to the computational difficulties
in locating their global minima, the problem is at present intractable when
the only information available is the sequence of subunits forming the
molecule. A less-demanding problem in terms of both physics and mathematics
is constrained optimization, which uses additional but incomplete
experimental information such as distances between certain atoms. This
paper reviews methods for generating molecular structure using bond lengths
and angles as variables and shows how the structure can be fully specified
in terms of local geometry. The analysis permits precise statements to be
made about the minimum set of distances that specify a unique structure
without recourse to energy minimization. We then discuss the complementary
situation, i.e., structure prediction with energy minimization based only
on sequence information. Finally, we show how distance constraints can be
incorporated into energy minimization methods.
