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How to guarantee optimal stability for most representative structures in the protein data bank
Author(s) -
Bastolla Ugo,
Farwer Jochen,
Knapp Ernst Walter,
Vendruscolo Michele
Publication year - 2001
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.1075
Subject(s) - protein data bank , threading (protein sequence) , protein folding , protein data bank (rcsb pdb) , energy landscape , protein structure prediction , computer science , protein structure , statistical potential , maximization , stability (learning theory) , simple (philosophy) , statistical physics , chemistry , physics , mathematical optimization , mathematics , machine learning , thermodynamics , stereochemistry , biochemistry , philosophy , epistemology
Abstract We proposed recently an optimization method to derive energy parameters for simplified models of protein folding. The method is based on the maximization of the thermodynamic average of the overlap between protein native structures and a Boltzmann ensemble of alternative structures. Such a condition enforces protein models whose ground states are most similar to the corresponding native states. We present here an extensive testing of the method for a simple residue‐residue contact energy function and for alternative structures generated by threading. The optimized energy function guarantees high stability and a well‐correlated energy landscape to most representative structures in the PDB database. Failures in the recognition of the native structure can be attributed to the neglect of interactions between different chains in oligomeric proteins or with cofactors. When these are taken into account, only very few X‐ray structures are not recognized. Most of them are short inhibitors or fragments and one is a structure that presents serious inconsistencies. Finally, we discuss the reasons that make NMR structures more difficult to recognize. Proteins 2001;44:79–96. © 2001 Wiley‐Liss, Inc.