Acta Crystallographica Section D - Structural Biology welcomes the submission of articles covering all aspects of structural biology, with a particular emphasis on the structures of biological macromolecules or the methods used to determine them.

The key criterion is that articles should present significant new insights into biological, chemical or medical sciences. Reports on new structures of biological importance may address the smallest macromolecules to the largest complex molecular machines. These structures may have been determined using any structural biology technique including crystallography, NMR, cryoEM and/or other methods. The inclusion of complementary data that support the conclusions drawn from the structural studies (such as binding studies, mass spectrometry, enzyme assays, or analysis of mutants or other modified forms of biological macromolecule) is encouraged. Multimedia additions to articles are welcomed.

In-depth reports on the latest software, equipment and methods are also welcome. These articles may include new approaches to any aspect of biological structure determination or structure analysis but will only be accepted when they focus on new methods that are demonstrated to be of general applicability and importance to structural biology. Articles describing particularly difficult problems in structural biology are also encouraged, if the analysis would provide useful insights to others facing similar problems.

This learned society journal has an international Editorial Board with trusted expert reviewers.

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Forthcoming special issues

CCP4SW 2025 - Using software, AI and other methods to advance crystallographic models

CCP-EM Spring Symposium 2025

CCP4SW 2024 - Decision making in MX - how to be a productive structural biologist

CCP-EM Spring Symposium 2024

Image Processing for CryoEM

Radiation Damage to Biological Samples

Articles from the Seventh International Symposium on Diffraction Structural Biology

Published special issues

CCP-EM Spring Symposium 2023

CCP4SW 2023 - Data - subtle details to big insights

Machine Learning in Crystallography and Structural Science

Full details are available on the special issues page.

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