ABSTRACT
During the COVID-19 pandemic, structural biologists rushed to solve the structures of the 28 proteins encoded by the SARS-CoV-2 genome in order to understand the viral life cycle and enable structure-based drug design. In addition to the 204 previously solved structures from SARS-CoV-1, 548 structures covering 16 of the SARS-CoV-2 viral proteins have been released in a span of only 6 months. These structural models serve as the basis for research to understand how the virus hijacks human cells, for structure-based drug design, and to aid in the development of vaccines. However, errors often occur in even the most careful structure determination - and may be even more common among these structures, which were solved quickly and under immense pressure. The Coronavirus Structural Task Force has responded to this challenge by rapidly categorizing, evaluating and reviewing all of these experimental protein structures in order to help downstream users and original authors. In addition, the Task Force provided improved models for key structures online, which have been used by Folding@Home, OpenPandemics, the EU JEDI COVID-19 challenge and others.
ABSTRACT
The interpretation of crystal structures in terms of intermolecular interaction energies enables phase stability and polymorphism to be rationalized in terms of quantitative thermodynamic models, while also providing insight into the origin of physical and chemical properties including solubility, compressibility and host-guest formation. The Pixel method is a semi-empirical procedure for the calculation of intermolecular interactions and lattice energies based only on crystal structure information. Molecules are represented as blocks of undistorted ab initio molecular electron and nuclear densities subdivided into small volume elements called pixels. Electrostatic, polarization, dispersion and Pauli repulsion terms are calculated between pairs of pixels and nuclei in different molecules, with the accumulated sum equating to the intermolecular interaction energy, which is broken down into physically meaningful component terms. The MrPIXEL procedure enables Pixel calculations to be carried out with minimal user intervention from the graphical interface of Mercury, which is part of the software distributed with the Cambridge Structural Database (CSD). Following initial setup of a crystallographic model, one module assigns atom types and writes necessary input files. A second module then submits the required electron-density calculation either locally or to a remote server, downloads the results, and submits the Pixel calculation itself. Full lattice energy calculations can be performed for structures with up to two molecules in the crystallographic asymmetric unit. For more complex cases, only molecule-molecule energies are calculated. The program makes use of the CSD Python API, which is also distributed with the CSD.
ABSTRACT
Crystal packing energy calculations are applied to the [Fe(PM-L)2(NCS)2] family of spin crossover (SCO) complexes (PM-L = 4-substituted derivatives of the N-(2-pyridylmethylene)-4-aminobiphenyl ligand) with the aim of relating quantitatively the cooperativity of observed SCO transitions to intermolecular interactions in the crystal structures. This approach reveals a linear variation of the transition abruptness with the sum of the magnitudes of the interaction energy changes within the first molecular coordination sphere in the crystal structure. Abrupt transitions are associated with the presence of significant stabilising and destabilising changes in intermolecular interaction energies. While the numerical trend established for the PM-L family does not directly extend to other classes of SCO complex in which the intermolecular interactions may be very different, a plot of transition abruptness against the range of interaction energy changes normalised by the largest change shows a clustering of complexes with similar transition abruptness. The changes in intermolecular interactions are conveniently visualised using energy difference frameworks, which illustrate the cooperativity pathways of an SCO transition.
ABSTRACT
The Cambridge Structural Database (CSD) currently contains over 400 000 transition-metal-containing entries, however many entries still lack curated oxidation-state assignments. Surveying and editing the remaining entries would be far too resource- and time-intensive to be carried out manually. Here, a highly reliable automated workflow for oxidation-state assignment in transition-metal coordination complexes via CSD Python API (application programming interface) scripts is presented. The strengths and limitations of the bond-valence sum (BVS) method are discussed and the use of complementary methods for improved assignment confidence is explored. In total, four complementary techniques have been implemented in this study. The resulting workflow overcomes the limitations of the BVS approach, widening the applicability of an automated procedure to more CSD entries. Assignments are successful for 99% of the cases where a high consensus between different methodologies is observed. Out of a total number of 54 999 unique metal atoms in a test dataset, the procedure yielded the correct oxidation state in 47 072 (86%) of cases.
