Mielke SP, Krishnan VV.
Abstract: Knowledge of the three-dimensional structure
of proteins is integral to understanding their functions, and a necessity
in the era of proteomics. A wide range of computational methods is employed
to estimate the secondary, tertiary, and quaternary structures of proteins.
Comprehensive experimental methods, on the other hand, are limited to
nuclear magnetic resonance (NMR) and X-ray crystallography. The full characterization
of individual structures, using either of these techniques, is extremely
time intensive. The demands of high throughput proteomics necessitate
the development of new, faster experimental methods for providing structural
information. As a first step toward such a method, we explore the possibility
of determining the structural classes of proteins directly from their NMR
spectra, prior to resonance assignment, using averaged chemical shifts.
This is achieved by correlating NMR-based information with empirical structure-based
information available in widely used electronic databases. The results
are analyzed statistically for their significance. The robustness of the
method as a structure predictor is probed by applying it to a set of proteins
of unknown structure. Our results show that this NMR-based method can be
used as a low-resolution tool for protein structural class identification.