CMM-An enhanced platform for interactive validation of metal binding sites

Abstract

Metal ions bound to macromolecules play an integral role in many cellular processes. They can directly participate in catalytic mechanisms or be essential for the structural integrity of proteins and nucleic acids. However, their unique nature in macromolecules can make them difficult to model and refine, and a substantial portion of metal ions in the PDB are misidentified or poorly refined. CheckMyMetal (CMM) is a validation tool that has gained widespread acceptance as an essential tool for researchers working on metal-macromolecule complexes. CMM can be used during structure determination or to validate metal binding sites in structural models within the PDB. The functionalities of CMM have recently been greatly enhanced and provide researchers with additional information that can guide modeling decisions. The new version of CMM shows metals in the context of electron density maps and allows for on-the-fly refinement of metal binding sites. The improvements should increase the reproducibility of biomedical research. The web server is available at https://cmm.minorlab.org.

Keywords: drug discovery; metal binding sites validation; metalloprotein; reproducibility; structure refinement.

FIGURE 1

The metal site quality as judged by the RSCC parameter (Smart et al., 2018). The descriptors of the vertical axis are metal site, number of metal sites, and the number of deposits in the PDB.

FIGURE 2

Distribution of the valence parameter for Zn binding sites in PDB deposits of proteins with resolution better than 1.5 Å derived from x‐ray and neutron diffraction only. The acceptable (79%), borderline (14%), and dubious (7%) cases are shown in green, yellow, and red, respectively. The intervals are defined according to data in Table 1.

FIGURE 3

New functionalities of CMM. (a) The CMM validation analysis after uploading a structural model. On the top, a user can switch between the validation and model modules. Below is a table with parameters per each metal binding site. The NGL viewer renders the view of the selected metal binding site. The distribution of distances between metal and binding atoms is shown on the right side. Under the viewer window, the crystallization conditions are displayed, if available. (b) In the model tab, the ranking of alternative metal ions is presented for each metal binding site. Metal ions reported in crystallization conditions are underlined, and the currently modeled ion is in bold. For each metal binding site, a user can change the metal ion, adjust the radius of refinement, change the occupancy, and apply all these changes with or without structure refinement.

FIGURE 4

Examples of metal binding sites included (a‐c) and excluded (d‐f) from the test set of structures. (a) 1PJ5, (b) 7ESB, (c) 1HN4, (d) 1G8H (metal not bound to the protein), (e) 5R66 (no density for Zn, PanDDA structure (Jaskolski et al., 2022)), (f) 1AON (poor resolution, 3.0 Å)

FIGURE 5

Metal ion binding site (residue: 401, chain: a) of 1PVF before and after refinement of the manganese substitution. The difference map is shown. (a) Site with originally modeled magnesium ion with significant density in difference map. (b) After modeling with manganese and refinement, there is no density in the difference map.