RECOGNITION OF ERRORS IN 3-DIMENSIONAL STRUCTURES OF PROTEINS

A major problem in the determination of the three-dimensional structur e of proteins concerns the quality of the structural models obtained f rom the interpretation of experimental data. New developments in X-ray crystallography and nuclear magnetic resonance spectroscopy have acce lerated the process of structure determination and the biological comm unity is confronted with a steadily increasing number of experimentall y determined protein folds. However, in the recent past several experi mentally determined protein structures have been proven to contain maj or errors, indicating that in some cases the interpretation of experim ental data is difficult and may yield incorrect models. Such problems can be avoided when computational methods are employed which complemen t experimental structure determinations. A prerequisite of such comput ational tools is that they are independent of the parameters obtained from a particular experiment. In addition such techniques are able to support and accelerate experimental structure determinations. Here we present techniques based on knowledge based mean fields which can be u sed to judge the quality of protein folds. The methods can be used to identify misfolded structures as well as faulty parts of structural mo dels. The techniques are even applicable in cases where only the C. tr ace of a protein conformation is available. The capabilities of the te chnique are demonstrated using correct and incorrect protein folds. (C ) 1993 Wiley-Liss, Inc.