Improving Data Representation of Metalloproteins in the Protein Data Bank

TL;DR

This paper discusses efforts to improve the accuracy of metal-containing protein data in the Protein Data Bank to better support biological and biochemical research.

Contribution

The paper introduces a remediation project to correct metal ligand data and enhance metalloprotein annotation using community-developed software.

Findings

Metalloproteins make up over one-third of PDB structures but face challenges in consistent chemical description.

A new data model and software tools are being used to correct and annotate metal ligand data across the archive.

Accurate oxidation states and coordination geometries are critical for understanding metal function in proteins.

Abstract

The Protein Data Bank (PDB) was established in 1971 as the first open-access digital data resource in biology, initially comprising just seven X- ray crystal structures of proteins. Today, the archive houses more than 225,000 experimentally-determined three-dimensional (3D) structures of biological macromolecules that are freely used by many millions of PDB data consumers worldwide. This wealth of information serves as a cornerstone for research and education endeavors across fundamental biology, biomedicine, biotechnology, and the energy sciences. The Worldwide Protein Data Bank partnership (wwPDB, wwpdb.org) includes five core members (RCSB PDB, PDBe, PDBj, BMRB, and EMDB) and one associate member (PDBc). The wwPDB jointly manages the PDB, EMDB, and BMRB core archives, which adhere to the FAIR (Findability, Accessibility, Interoperability, Reusability) principles emblematic of responsible data stewardship.

Metalloproteins represent an important subset of the archive holdings, constituting more than one-third of PDB structures. Accurate chemical descriptions of metal-containing ligands and their interactions with proteins are valuable to researchers studying these metals in biological processes (e.g., respiration, photosynthesis, enzymatic catalysis). The wwPDB faces challenges in providing consistent chemical descriptions for metal ligands. Oxidation state cannot be determined from 3D structure alone, and coordination geometry can change between the compound initially incubated with a protein and the final protein-bound form of the molecule. However, these are key data for understanding the metal function and reactivity in the protein environment.

To uphold organizational imperatives of consistency and accuracy across the PDB, we are working to address challenges in metal ligand data representation through a “remediation” project spanning the entire archive. Here, we describe our efforts to improve metal ligand accuracy through correcting chemical definitions and to enhance metalloprotein annotation through a new data model. Both the corrections and the enhanced annotation are enabled by adoption of software developed by the metalloprotein research community.