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Understanding the dynamics of ligands bound to proteins is an important task in medicinal chemistry and drug design. However, the dominant technique for determining protein-ligand structures, X-ray crystallography, does not fully account for dynamics and cannot accurately describe the movements of ligands in protein binding sites. In this article, an alternative method, ensemble refinement, is used on six protein-ligand complexes with the aim of understanding the conformational diversity of ligands in protein crystal structures. The results show that ensemble refinement sometimes indicates that the flexibility of parts of the ligand and some protein side chains is larger than that which can be described by a single conformation and atomic displacement parameters. However, since the electron-density maps are comparable and R free values are slightly increased, the original crystal structure is still a better model from a statistical point of view. On the other hand, it is shown that molecular-dynamics simulations and automatic generation of alternative conformations in crystallographic refinement confirm that the flexibility of these groups is larger than is observed in standard refinement. Moreover, the flexible groups in ensemble refinement coincide with groups that give high atomic displacement parameters or non-unity occupancy if optimized in standard refinement. Therefore, the conformational diversity indicated by ensemble refinement seems to be qualitatively correct, indicating that ensemble refinement can be an important complement to standard crystallographic refinement as a tool to discover which parts of crystal structures may show extensive flexibility and therefore are poorly described by a single conformation. However, the diversity of the ensembles is often exaggerated (probably partly owing to the rather poor force field employed) and the ensembles should not be trusted in detail., (open access.)

X-ray crystallography is the main source of atomistic information on the structure of proteins. Normal crystal structures are obtained as a compromise between the X-ray scattering data and a set of empirical restraints that ensure chemically reasonable bond lengths and angles. However, such restraints are not always available or accurate for nonstandard parts of the structure, for example substrates, inhibitors and metal sites. The method of quantum refinement, in which these empirical restraints are replaced by quantum-mechanical (QM) calculations, has previously been suggested for small but interesting parts of the protein. Here, this approach is extended to allow for multiple conformations in the QM region by performing separate QM calculations for each conformation. This approach is shown to work properly and leads to improved structures in terms of electron-density maps and real-space difference density Z-scores. It is also shown that the quality of the structures can be gauged using QM strain energies. The approach, called ComQumX-2QM, is applied to the P-cluster in two different crystal structures of the enzyme nitrogenase, i.e. an Fe 8 S 7 Cys 6 cluster, used for electron transfer. One structure is at a very high resolution (1.0 Å) and shows a mixture of two different oxidation states, the fully reduced P N state (Fe 8 2+ , 20%) and the doubly oxidized P 2+ state (80%). In the original crystal structure the coordinates differed for only two iron ions, but here it is shown that the two states also show differences in other atoms of up to 0.7 Å. The second structure is at a more modest resolution, 2.1 Å, and was originally suggested to show only the one-electron oxidized state, P 1+ . Here, it is shown that it is rather a 50/50% mixture of the P 1+ and P 2+ states and that many of the Fe-Fe and Fe-S distances in the original structure were quite inaccurate (by up to 0.8 Å). This shows that the new ComQumX-2QM approach can be used to sort out what is actually seen in crystal structures with dual conformations and to give locally improved coordinates., (open access.)

The structure and function of proteins are strongly affected by the surrounding solvent water, for example through hydrogen bonds and the hydrophobic effect. These interactions depend not only on the position, but also on the orientation, of the water molecules around the protein. Therefore, it is often vital to know the detailed orientations of the surrounding ordered water molecules. Such information can be obtained by neutron crystallography. However, it is tedious and time-consuming to determine the correct orientation of every water molecule in a structure (there are typically several hundred of them), which is presently performed by manual evaluation. Here, a method has been developed that reliably automates the orientation of a water molecules in a simple and relatively fast way. Firstly, a quantitative quality measure, the real-space correlation coefficient, was selected, together with a threshold that allows the identification of water molecules that are oriented. Secondly, the refinement procedure was optimized by varying the refinement method and parameters, thus finding settings that yielded the best results in terms of time and performance. It turned out to be favourable to employ only the neutron data and a fixed protein structure when reorienting the water molecules. Thirdly, a method has been developed that identifies and reorients inadequately oriented water molecules systematically and automatically. The method has been tested on three proteins, galectin-3C, rubredoxin and inorganic pyrophosphatase, and it is shown that it yields improved orientations of the water molecules for all three proteins in a shorter time than manual model building. It also led to an increased number of hydrogen bonds involving water molecules for all proteins.

Corrections are published for the article by Caldararu et al. [(2019), Acta Cryst. D75, 368-380].

Neutron crystallography is a powerful method to determine the positions of H atoms in macromolecular structures. However, it is sometimes hard to judge what would constitute a chemically reasonable model, and the geometry of H atoms depends more on the surroundings (for example the formation of hydrogen bonds) than heavy atoms, so that the empirical geometry information for the H atoms used to supplement the experimental data is often less accurate. These problems may be reduced by using quantum-mechanical calculations. A method has therefore been developed to combine quantum-mechanical calculations with joint crystallographic refinement against X-ray and neutron data. A first validation of this method is provided by re-refining the structure of the galectin-3 carbohydrate-recognition domain in complex with lactose. The geometry is improved, in particular for water molecules, for which the method leads to better-resolved hydrogen-bonding interactions. The method has also been applied to the active copper site of lytic polysaccharide monooxygenase and shows that the protonation state of the amino-terminal histidine residue can be determined., (open access.)