Computer-assisted assignment of 2D1H NMR spectra of proteins: Basic algorithms and application to phoratoxin B

Abstract

A suite of computer programs (CLAIRE) is described which can be of assistance in the process of assigning 2D 1H NMR spectra of proteins. The programs embody a software implementation of the sequential assignment approach first developed by Wüthrich and co-workers (K. Wüthrich, G. Wider, G. Wagner and W. Braun (1982) J. Mol. Biol. 155, 311). After data-abstraction (peakpicking), the software can be used to detect patterns (spin systems), to find cross peaks between patterns in 2D NOE data sets and to generate assignments that are consistent with all available data and which satisfy a number of constraints imposed by the user. An interactive graphics program called CONPAT is used to control the entire assignment process as well as to provide the essential feedback from the experimental NMR spectra. The algorithms are described in detail and the approach is demonstrated on a set of spectra from the mistletoe protein phoratoxin B, a homolog of crambin. The results obtained compare well with those reported earlier based entirely on a manual assignment process.

Plant thionins – the structural perspective

“…The structures of several members of the thionin family were determined by NMR (Table 2), i.e. phoratoxin-A [69], crambin [70], viscotoxin A3 and C1 [71,72], α-hordothionin [73], purothionin [74], and hellethionin [75]. These structures showed high similarity with those determined by X-ray crystallography.…”

Evaluation of an algorithm for the automated sequential assignment of protein backbone resonances: A demonstration of the connectivity tracing assignment tools (CONTRAST) software package

“…When working with real spectra, one cannot be certain of the amount of scatter in the data, and thus the question of what tolerances to use for the program becomes important. For many automated assignment algorithms this choice is critical (Eads and Kuntz, 1989;Ikura et al, 1990;Kleywegt et al, 1991). However, the performance of the basic CONTRAST SBA algorithm is relatively insensitive to the tolerance chosen, as long as it is larger than the sum of the scatter levels and the alignment offset between the spectra being compared.…”

“…Shuffle, which proved to be the most succesful algorithm (see the Results and Discussion section), uses a 'best first' approach to finding the correct arrangement of fragments that is similar to the 2D NOESY-based approach used by Kleywegt et al (1991). In the call to Shuffle (Shuffle hnco L), the name of the source spectrum (HNCO) and the number of highest scoring neighbors that are to be remembered (L), are the only input parameters.…”

“…Semi-automated approaches for obtaining assignments from homonuclear 1H 2D NMR data for small proteins (Mr < 10 kDa) have required what can only be assumed to be clean, precise data sets and have met with modest success (Billeter et al, 1988;Cieslar et al, 1988;Eads and Kuntz, 1989;Kraulis, 1989;Weber et al, 1989;Catasti et al, 1990;Pf~indler and Bodenhausen, 1990; Van de Ven, 1990;Eccles et al, 1991;Kleywegt et al, 1991). These methods are less efficient for larger proteins (Mr > 10 kDa), owing to their increased spectral overlap.…”

Recognition of spatial motifs in protein structures 1 1Edited by J. Thornton

“…If this number is smaller than a preset cut-off value, the corresponding set of residues constitutes a match or hit. The algorithm is essentially the same as that used previously for the automatic assignment of 2D (two-dimensional) and 3D 1 H NMR spectra of proteins (where spin systems detected in the spectra must be matched to residues in the sequence; Kleywegt et al, 1989Kleywegt et al, , 1991Kleywegt et al, , 1993, and in the foldrecognition program DEJAVU (where secondary structure elements of one protein must be matched to those of another; . The major difference lies in the fact that SPASM does not attempt to identify a single, optimal solution.…”