Refinement of severely incomplete structures with maximum likelihood in BUSTER-TNT.

By E. Blanc, P. Roversi, Clemens Vonrhein, C. Flensburg, S. Lea, Gerard Bricogne. 2004

722 citations recorded by the source corpus.

BUSTER-TNT is a maximum-likelihood macromolecular refinement package. BUSTER assembles the structural model, scales observed and calculated structure-factor amplitudes and computes the model likelihood, whilst TNT handles the stereochemistry and NCS restraints/constraints and shifts the atomic coordinates, B factors and occupancies. In real space, in addition to the traditional atomic and bulk-solvent models, BUSTER models the parts of the structure for which an atomic model is not yet available ('missing structure') as low-resolution probability distributions for the random positions of the missing atoms. In reciprocal space, the BUSTER structure-factor distribution in the complex plane is a two-dimensional Gaussian centred around the structure factor calculated from the atomic, bulk-solvent and missing-structure models. The errors associated with these three structural components are added to compute the overall spread of the Gaussian. When the atomic model is very incomplete, modelling of the missing structure and the consistency of the BUSTER statistical model help structure building and completion because (i) the accuracy of the overall scale factors is increased, (ii) the bias affecting atomic model refinement is reduced by accounting for some of the scattering from the missing structure, (iii) the addition of a spatial definition to the source of incompleteness improves on traditional Luzzati and sigmaA-based error models and (iv) the program can perform selective density modification in the regions of unbuilt structure alone.

Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computational Theory and Mathematics

In Materials Chemistry

In Molecular Biology

Citations in the corpus

Features and development of Coot (2010, neutral): “Currently, suitable ﬁles are generated by the following software: Phaser (Storoni et al. , 2004), REFMAC (Murshudov et al. , 1997), phenix.reﬁne (Adams et al. , 2002), DM (Zhang et al. , 1997), Parrot (Cowtan, 2010), Pirate (Cowtan, 2000) and BUSTER (Blanc et al. , 2004).”
Crystal structures (2004, neutral): “These include BUSTER/TNT (Blanc et al., 2004), CNS (Brünger et al., 1998), MAIN (Turk, 2008), MOPRO (Guillot et al., 2001), phenix. refine (Adams et al., 2010), REFMAC5 (Murshudov et al., 1997), SHELXL (Sheldrick, 2008) and TNT (Tronrud et al., 1987).”
Polder maps: improving OMIT maps by excluding bulk solvent (2017, background): “Furthermore, statistical treatment of non-uniformity of bulk solvent or as yet unmodeled regions has been discussed (Blanc et al., 2004; Perrakis et al., 1999; Roversi et al., 2000).”
Crystal Structure of the β2Adrenergic Receptor-Gs protein complex (2011, neutral): “Following the determination of the initial structure by molecular replacement, rigid body refinement and simulated annealing were performed in Phenix 41 and BUSTER 42 , followed by restrained refinement and manual rebuilding in Coot 43 .”
phenix.mr_rosetta: molecular replacement and model rebuilding with Phenix and Rosetta (2012, methodology): “Improvements in methods for obtaining phase information from a preliminary model include developments in algorithms for creating maps that optimally show unmodeled density [15] and developments in density modiﬁcation procedures that reduce model bias [16].”
The Phenix Software for Automated Determination of Macromolecular Structures (2011, methodology): “Such procedures have become standard in many structural genomics and industrial labs that rely on high-throughput crystallography, and are also being built into other software such as Coot[31], ARP/wARP[9], and BUSTER[16].”
Unexpected Receptor Functional Mimicry Elucidates Activation of Coronavirus Fusion (2020, neutral): “The coordinates were subsequently improved and completed using Buccaneer (Cowtan, 2006) and COOT (Brown et al., 2015; Emsley et al., 2010) and refined with BUSTER-TNT (Blanc et al., 2004) and REFMAC5 (Vagin et al., 2004).”
Structure of the protein core of the glypican Dally-like and localization of a region important for hedgehog signaling (2011, methodology): “The program COOT was used for model building (49), and refinement was performed with the programs PHENIX (50) and BUSTER (51).”
D3R Grand Challenge 2: Blind Prediction of Protein-Ligand Poses, Affinity Rankings, and Relative Binding Free Energies (2017, methodology): “FXR structures were determined at Roche by molecular replacement with PHASER [23], using a set of previously determined in-house FXR structures as models, and the solution with the best log-likelihood gain was used as starting model for rebuilding and refinement in Refmac5 [24] or BUSTER [25].”
Unique carbohydrate–carbohydrate interactions are required for high affinity binding between FcγRIII and antibodies lacking core fucose (2011, methodology): “Programs from the CCP4 suite (36) and BUSTER (37) have been used to subsequently refine the data.”