A close look onto structural models and primary ligands of metallo-ß-lactamases.

ß-Lactamases are hydrolytic enzymes capable of opening the ß-lactam ring of antibiotics such as penicillin, thus endowing the bacteria that produce them with antibiotic resistance. Of particular medical concern are metallo-ß-lactamases (MBLs), with an active site built around coordinated Zn cations. MBLs are pan-reactive enzymes that can break down almost all classes of ß-lactams, including such last-resort antibiotics as carbapenems. They are not only broad-spectrum-reactive but are often plasmid-borne (e.g., the New Delhi enzyme, NDM), and can spread horizontally even among unrelated bacteria. Acquired MBLs are encoded by mobile genetic elements, which often include other resistance genes, making the microbiological situation particularly alarming. There is an urgent need to develop MBL inhibitors in order to rescue our antibiotic armory. A number of such efforts have been undertaken, most notably using the 3D structures of various MBLs as drug-design targets. Structure-guided drug discovery depends on the quality of the structures that are collected in the Protein Data Bank (PDB) and on the consistency of the information in dedicated ß-lactamase databases. We conducted a careful review of the crystal structures of class B ß-lactamases, concluding that the quality of these structures varies widely, especially in the regions where small molecules interact with the macromolecules. In a number of examples the interpretation of the bound ligands (e.g., inhibitors, substrate/product analogs) is doubtful or even incorrect, and it appears that in some cases the modeling of ligands was not supported by electron density. For ten MBL structures, alternative interpretations of the original diffraction data could be proposed and the new models have been deposited in the PDB. In four cases, these models, prepared jointly with the authors of the original depositions, superseded the previous deposits. This review emphasizes the importance of critical assessment of structural models describing key drug design targets at the level of the raw experimental data. Since the structures reviewed here are the basis for ongoing design of new MBL inhibitors, it is important to identify and correct the problems with ambiguous crystallographic interpretations, thus enhancing reproducibility in this highly medically relevant area.

The young person's guide to the PDB.

The Protein Data Bank (PDB), created in 1971 when merely seven protein crystal structures were known, today holds over 120, 000 experimentally-determined three-dimensional models of macromolecules, including gigantic structures comprised of hundreds of thousands of atoms, such as ribosomes and viruses. Most of the deposits come from X-ray crystallography experiments, with important contributions also made by NMR spectroscopy and, recently, by the fast growing Cryo-Electron Microscopy. Although the determination of a macromolecular crystal structure is now facilitated by advanced experimental tools and by sophisticated software, it is still a highly complicated research process requiring specialized training, skill, experience and a bit of luck. Understanding the plethora of structural information provided by the PDB requires that its users (consumers) have at least a rudimentary initiation. This is the purpose of this educational overview.

Crystallography and chemistry should always go together: a cautionary tale of protein complexes with cisplatin and carboplatin.

The anticancer activity of platinum-containing drugs such as cisplatin and carboplatin is considered to primarily arise from their interactions with nucleic acids; nevertheless, these drugs, or the products of their hydrolysis, also bind to proteins, potentially leading to the known side effects of the treatments. Here, over 40 crystal structures deposited in the Protein Data Bank (PDB) of cisplatin and carboplatin complexes of several proteins were analysed. Significant problems of either a crystallographic or a chemical nature were found in most of the presented atomic models and they could be traced to less or more serious deficiencies in the data-collection and refinement procedures. The re-evaluation of these data and models was possible thanks to their mandatory or voluntary deposition in publicly available databases, emphasizing the point that the availability of such data is critical for making structural science reproducible. Based on this analysis of a selected group of macromolecular structures, the importance of deposition of raw diffraction data is stressed and a procedure for depositing, tracking and using re-refined crystallographic models is suggested.

Correcting the record of structural publications requires joint effort of the community and journal editors.

Seriously flawed and even fictional models of biomolecular crystal structures, although rare, still persist in the record of structural repositories and databases. The ensuing problems of database contamination and persistence of publications based on incorrect structure models must be effectively addressed. The burden cannot be simply left to the critical voices who take the effort to contribute dissenting comments that are mostly ignored. The entire structural biology community, and particularly the journal editors who exercise significant power in this respect, must engage in a constructive dialog lest structural biology lose its credibility as an evidence-based empirical science.