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Determination of three‐dimensional protein structures from nuclear magnetic resonance data using fragments of known structures
Author(s) -
Krauli Per J.,
Jones T. Alwyn
Publication year - 1987
Publication title -
proteins: structure, function, and bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.699
H-Index - 191
eISSN - 1097-0134
pISSN - 0887-3585
DOI - 10.1002/prot.340020304
Subject(s) - nuclear overhauser effect , chemistry , protein structure , biological system , two dimensional nuclear magnetic resonance spectroscopy , data set , nuclear magnetic resonance spectroscopy , cluster (spacecraft) , crystallography , algorithm , computer science , artificial intelligence , stereochemistry , biochemistry , biology , programming language
A method to build a three‐dimensional protein model from nuclear magnetic resonance (NMR) data using fragments from a data base of crystallographically determined protein structures is presented. The interproton distances derived from the nuclear Overhauser effect (NOE) data are compared to the precalculated distances in the known protein structures. An efficient search algorithm is used, which arranges the distancs in matrices akin to a Cα diagonal distance plot, and compares the NOE distance matrices for short sequential zones of the protein to the data base matrices. After cluster analysis of the fragments found in this way, the structure is built by aligning fragments in overlapping zones. The sequentially long‐range NOEs cannot be used in the initial fragments search but are vital to discriminate between several possible combinations of different groups of fragments. The method has been tested on one simulated NOE data set derived from a crystal structure and one experimental NMR data set. The method produces models that have good local structure, but may contain larger global errors. These models can be used as the starting point for further refinement, e.g., by restrained molecular dynamics or interactive graphics.