Ten things I `hate' about refinement

Abstract

Macromolecular refinement is an optimization process that aims to produce the most likely macromolecular structural model in the light of experimental data. As such, macromolecular refinement is one of the most complex optimization problems in wide use. Macromolecular refinement programs have to deal with the complex relationship between the parameters of the atomic model and the experimental data, as well as a large number of types of prior knowledge about chemical structure. This paper draws attention to areas of unfinished business in the field of macromolecular refinement. In it, we describe ten refinement topics that we think deserve attention and discuss directions leading to macromolecular refinement software that would make the best use of modern computer resources to meet the needs of structural biologists of the twenty-first century.

Crystal polymorphism in fragment-based lead discovery of ligands of the catalytic domain of UGGT, the glycoprotein folding quality control checkpoint

“…The best approach to the problem would, therefore, require a single integrated piece of software that refines two classes of parameters against unprocessed X-ray diffraction images: the first class of parameters are the ones traditionally refined during X-ray data processing, and the second class are the parameters traditionally refined during macromolecular refinement. To be most useful for the purpose of polymorph choice, such a program would likely need to deal at least with some of the correlations between parameters belonging to either class ( Roversi and Tronrud, 2021 ). Each refinement of the atomic structures of one of the possible polymorphs directly against the diffraction images would compute a R free , a free likelihood or another model comparison metric, ( Babcock et al, 2018 ) and presumably enable the choice of the best polymorph as the one that uses only as few parameters as are needed to fit the signal but not the noise in the data, and no more.…”

Lone Pair…π Contacts and Structure Signatures of r(UNCG) Tetraloops, Z-Turns, and Z-Steps: A WebFR3D Survey

“…For instance, without careful inspection of electron densities, one could be inclined to consider that the syn conformation of the 3rd residue of the 5OB3 tetraloop and other minor structural deviations are the result of natural hairpin dynamics. However, they more likely result from poor local modeling due to an incomplete refinement process combined or not with insufficient experimental data [74,75,[78][79][80][81]. 1d for two tetraloops extracted from the 7K00 cryo-EM structure.…”

A database overview of metal-coordination distances in metalloproteins

“…The experimentally available data always come with uncertainties regarding the structural features that depend on the sample preparation (Ne ´meth et al, 2014;Foster et al, 2022), the data-collection protocol (McPherson, 2017) and the quality of the diffraction data, for example the resolution obtained (Zheng et al, 2014). Since not all refinement programs apply geometric restrictions between the metal ion and its ligands by default, errors may occur during model generation and refinement of metal-binding sites (Zheng et al, 2008;Roversi & Tronrud, 2021). This is particularly important for low-resolution structures (Touw et al, 2016;Nicholls et al, 2021).…”