Structure Calculation Using Automated Techniques

It has been recognized that many of the time-consuming interactive tasks carried out by an expert during the process of spectral analysis could be done more efficiently by automated computational systems [6]. Over the past few years, this potential has been realized to some degree. Today automated methods for NMR structure determination are playing a more and more prominent role and can be expected to largely supersede the conventional manual approaches to solving three-dimensional protein structures in solution. 

The structure of this chapter is as follows Section 2.2 introduces the various types of conformational constraints used in NMR structure calculations. Section 2.3 is devoted to modern structure calculation algorithms. Section 2.4 gives an account of the general principles and the practice of automated NOESY assignment. 

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Since transition-structure calculations are so sensitive to the starting geometry, a number of automated techniques for finding reasonable starting geometries have been proposed. One very useful technique is to start from the reactant and product structures. 

Nuclear magnetic resonance (NMR) spectroscopy is the most informative analytical technique and is widely applied in combinatorial chemistry. However, an automated interpretation of the NMR spectral results is difficult (3,4). Usually the interpretation can be supported by use of spectrum calculation (5-18) and structure generator programs (8,12,18-21). Automated structure validation methods rely on NMR signal comparison using substructure/ subspectra correlated databases or shift prediction methods (8,15,22,23). We have recently introduced a novel NMR method called AutoDROP (Automated Definition and Recognition of Patterns) to rapidly analyze compounds libraries (24-29). The method is based on experimental data obtained from the measured ID or 2D iH,i C correlated (HSQC) spectra. 

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