Errors in structural biology are not the exception. Issue 3 (27th February 2023)

• Record Type: Journal Article
• Authors: Gao, Yunyun; Thorn, Volker; Thorn, Andrea
• Is Part Of: Acta crystallographica. Volume 79:Issue 3(2023)
• Page Start: 206
• Page End: 211
• Publication Date: 2023-02-27
• Subjects: errors -- structural biology -- modelling -- quality indicators -- validation; X-ray crystallography -- Periodicals; Crystallography -- Periodicals; Molecular biology -- Periodicals; Molecular structure -- Periodicals; Biomolecules -- Structure -- Periodicals; Cytology -- Periodicals; Biomolecules -- Structure; Crystallography; Cytology; Molecular biology; Molecular structure; X-ray crystallography; Periodicals; 548
• DOI: 10.1107/S2059798322011901
• Languages: English
• ISSNs: 2059-7983

Abstract

Abstract : Errors from measurement, data processing and modelling are present throughout structures deposited in the Protein Data Bank. Identifying them is only the first step. What needs to change in order to minimize their impact? 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.