Errors in structural biology are not the exception

Abstract

During the COVID-19 pandemic, the structural biology community swung into action quickly and efficiently, and many urgent questions were solved by macromolecular structure determination. The Coronavirus Structural Task Force evaluated all structures from SARS-CoV-1 and SARS-CoV-2, but errors in measurement, data processing and modelling are present beyond these structures and throughout the structures deposited in the Protein Data Bank. Identifying them is only the first step; in order to minimize the impact that errors have in structural biology, error culture needs to change. It should be emphasized that the atomic model which is published is an interpretation of the measurement. Furthermore, risks should be minimized by addressing issues early and by investigating the source of a given problem, so that it may be avoided in the future. If we as a community can do this, it will greatly benefit experimental structural biologists as well as downstream users who are using structural models to deduce new biological and medical answers in the future.

Principles of ion binding to RNA inferred from the analysis of a 1.55 Å resolution bacterial ribosome structure – Part I: Mg2+

“…Larger Mg 2+ numbers result habitually from specific buffer conditions or from an excess of faith in the amount of information contained in experimental data. For RNA and other metal containing biomolecular systems, the latter bias has been documented (14)(15)(16)(17)(18)(19)(20)(21)(22)(23) and some tools to identify assignment errors have been developed (24)(25)(26) but none specific to nucleic acids besides the MgRNA attempt (27) that has been critically evaluated (14,15). Thus, it is essential to advance our understanding of the binding stereochemistry of Mg 2+ and K + ions to rRNA to correctly assign these ions to the peaks derived from experimental cryo-EM/X-ray density maps and to get more insights into their biological functions.…”

Automated model building and protein identification in cryo-EM maps

“…At resolutions better than 3 Å, experts can build atomic models with few errors, whereas at resolutions below 4 Å, avoiding mistakes is challenging. It is therefore not uncommon for atomic models of biological complexes to contain errors ( 7 ), with potentially grievous consequences ( 8 ).…”

Automated benchmarking of combined protein structure and ligand conformation prediction

“…Previous research has shown that the quality of experimentally resolved structures can vary significantly 17 . Efforts have been made to establish criteria for assessing the quality of such structures, like the Iridium criteria 18 .…”