International
Tables for
Crystallography
Volume F
Crystallography of biological macromolecules
Edited by M. G. Rossmann and E. Arnold

International Tables for Crystallography (2006). Vol. F, ch. 25.2, pp. 717-718   | 1 | 2 |

Section 25.2.4.3.2. Refinement should run quickly and use as little memory as possible

D. E. Tronrudm* and L. F. Ten Eycky

25.2.4.3.2. Refinement should run quickly and use as little memory as possible

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The most time-consuming calculations in refinement are the calculation of structure factors from atomic coordinates and the calculation of derivatives of the part of the residual dependent upon the diffraction data with respect to the atomic parameters. The quickest means of performing these calculations requires the use of space-group-optimized fast Fourier transforms (FFTs). The initial implementation of TNT used FFTs to calculate structure factors, but the much slower direct summation method to calculate the derivatives. Within a few years, Agarwal's method (Agarwal, 1978[link]; Agarwal et al., 1981[link]) was incorporated into TNT and from then on all crystallographic calculations were performed with FFTs.

The FFT programs of Ten Eyck (1973[link], 1977[link]) made very efficient use of computer memory. Another means of saving memory was to recognize that the code for calculating stereochemical restraints did not need to be in the memory when the crystallographic calculations were being performed and vice versa. There were two ways to save memory using this information. One could create a series of `overlays' or one could break the calculation into a series of separate programs. The means for defining an overlay structure were never standardized and could not be ported from one type of computer to another and were, therefore, never attempted in TNT. For this reason, and a number of others mentioned here, TNT is not a single program but a collection of programs, each with a well defined and specialized purpose.

References

Agarwal, R. C. (1978). A new least-squares technique based on the fast Fourier transform algorithm. Acta Cryst. A34, 791–809.Google Scholar
Agarwal, R. C., Lifchitz, A. & Dodson, E. (1981). Block diagonal least squares refinement using fast Fourier techniques. In Refinement of protein structures, edited by P. A. Machin, J. W. Campbell & M. Elder. Warrington: Daresbury Laboratory.Google Scholar
Ten Eyck, L. F. (1973). Crystallographic fast Fourier transforms. Acta Cryst. A29, 183–191.Google Scholar
Ten Eyck, L. F. (1977). Efficient structure-factor calculation for large molecules by the fast Fourier transform. Acta Cryst. A33, 486–492.Google Scholar








































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