TNT refinement package.

Publisher Summary The scope of TNT is to optimize atomic coordinates with respect to a series of observations, usually diffraction data and ideal stereochemistry. It also provides information to aid in the examination and correction of the refined model. These include the difference maps to be displayed along with the model, the automatic location of peaks in these maps, and indicators of the problem spots in the refined model that should be examined directly by the crystallographer. Although TNT is an excellent package for everyday refinement, its flexibility allows it to be used as a tool for the development of new refinement techniques. The TNT components can be recorded, new components to implement the refinement of the model against a novel set of observations can be added, or other kinds of changes without having to modify the existing programs can be made. To solve any computational problem, one establishes a protocol that is based on a collection of assumptions about the nature of the problem.

[1]  K. D. Watenpaugh,et al.  Refinement of the model of a protein: rubredoxin at 1.5 Å resolution , 1973 .

[2]  L. T. Eyck,et al.  Crystallographic fast Fourier transforms , 1973 .

[3]  H. Schenk,et al.  Computing in Crystallography , 1978 .

[4]  J. S. Rollett,et al.  Statistical descriptors in crystallography: Report of the IUCr Subcommittee on Statistical Descriptors , 1989 .

[5]  George M. Church,et al.  A structure-factor least-squares refinement procedure for macromolecular structures using constrained and restrained parameters , 1977 .

[6]  B. Matthews,et al.  Binding of hydroxamic acid inhibitors to crystalline thermolysin suggests a pentacoordinate zinc intermediate in catalysis. , 1982, Biochemistry.

[7]  T. Eyck,et al.  Efficient structure-factor calculation for large molecules by the fast Fourier transform , 1977 .

[8]  D. Tronrud,et al.  Knowledge-Based B-Factor Restraints for the Refinement of Proteins , 1996 .

[9]  Michael S. Chapman,et al.  Restrained real-space macromolecular atomic refinement using a new resolution-dependent electron-density function , 1995 .

[10]  D. Tronrud.  Conjugate-direction minimization: an improved method for the refinement of macromolecules. , 1992, Acta crystallographica. Section A, Foundations of crystallography.

[11]  J. Konnert,et al.  A restrained-parameter structure-factor least-squares refinement procedure for large asymmetric units , 1976 .

[12]  G. Bricogne,et al.  Maximum-Likelihood Refinement of Incomplete Models with BUSTER + TNT , 1998 .

[13]  R. Kretsinger,et al.  Refinement of the structure of carp muscle calcium-binding parvalbumin by model building and difference Fourier analysis. , 1976, Journal of molecular biology.

[14]  R. Huber,et al.  Accurate Bond and Angle Parameters for X-ray Protein Structure Refinement , 1991 .

[15]  R. Read,et al.  Improved Structure Refinement Through Maximum Likelihood , 1996 .

[16]  Brian W. Matthews,et al.  An efficient general-purpose least-squares refinement program for macromolecular structures , 1987 .

[17]  G. J.,et al.  Refinement of Large Structures by Simultaneous Minimization of Energy and R Factor , 1978 .

[18]  H M Holden,et al.  Structures of two thermolysin-inhibitor complexes that differ by a single hydrogen bond. , 1987, Science.

[19]  M. J. D. Powell,et al.  Restart procedures for the conjugate gradient method , 1977, Math. Program..

[20]  Tronrud.  The efficient calculation of the normal matrix in least-squares refinement of macromolecular structures. , 1999, Acta crystallographica. Section A, Foundations of crystallography.

[21]  Barry C. Finzel,et al.  Software for macromolecular crystallography: a user's overview , 1993 .

[22]  W. Press,et al.  Numerical Recipes: The Art of Scientific Computing , 1987 .

[23]  M. Karplus,et al.  Crystallographic R Factor Refinement by Molecular Dynamics , 1987, Science.

[24]  C. M. Reeves,et al.  Function minimization by conjugate gradients , 1964, Comput. J..