PubMed · 7634065
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C D Surridge. 1994. Advancing in a dynamic field.. https://doi.org/10.1038/nsb1094-664
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Full-matrix least squares is taken as the basis for an examination of protein structure precision. A two-atom protein model is used to compare the precisions of unrestrained and restrained refinements. In this model, restrained refinement determines a bond length which is the weighted mean of the unrestrained diffraction-only length and the geometric dictionary length. Data of 0.94 A resolution for the 237-residue protein concanavalin A are used in unrestrained and restrained full-matrix inversions to provide standard uncertainties sigma(r) for positions and sigma(l) for bond lengths. sigma(r) is as small as 0.01 A for atoms with low Debye B values but increases strongly with B. The results emphasize the distinction between unrestrained and restrained refinements and between sigma(r) and sigma(l). Other full-matrix inversions are reported. Such inversions require massive calculations. Several approximate methods are examined and compared critically. These include a Fourier map formula [Cruickshank (1949). Acta Cryst. 2, 65-82], Luzzati plots [Luzzati (1952). Acta Cryst. 5, 802-810] and a new diffraction-component precision index (DPI). The DPI estimate of sigma(r, Bavg) is given by a simple formula. It uses R or Rfree and is based on a very rough approximation to the least-squares method. Many examples show its usefulness as a precision comparator for high- and low-resolution structures. The effect of restraints as resolution varies is examined. More regular use of full-matrix inversion is urged to establish positional precision and hence the precision of non-dictionary distances in both high- and low-resolution structures. Failing this, parameter blocks for representative residues and their neighbours should be inverted to gain a general idea of sigma(r) as a function of B. The whole discussion is subject to some caveats about the effects of disordered regions in the crystal.
A protein structure comparison method is described that allows the generation of large populations of high-scoring alternate alignments. This was achieved by incorporating a random element into an iterative double dynamic programming algorithm. The maximum scores from repeated comparisons of a pair of structures converged on a value that was taken as the global maximum. This lay 15% over the score obtained from the single fixed (unrandomized) calculation. The effect of the gap penalty was observed through the shift of the alignment populations, characterized by their alignment length and root-mean-square deviation (RMSD). The best (lowest RMSD) values found in these populations provided a base-line against which other methods were compared.
It is now possible to design small proteins capable of folding into compact structures with well-packed cores. Given the present state of knowledge of protein folding and design, it is possible to extract a set of engineering guidelines that may assist in future de novo protein design.