Available online 29 October 2022, 107915

HaPi (Handedness Pipeline) can automatically determine the hand of cyroEM maps.

HaPi is built by training two 3D Convolutional Neural Networks.

The hand can be determined for experimental cyroEM maps of up to 5Åof resolution.

11 structures with incorrect hand were identified in the EMDB database.

HaPi can be used as a validation tool to ensure correct handedness.

Single-Particle Analysis by Cryo-Electron Microscopy is a well-established technique to elucidate the three-dimensional (3D) structure of biological macromolecules. The orientation of the acquired projection images must be initially estimated without any reference to the final structure. In this step, algorithms may find a mirrored version of all the orientations resulting in a mirrored 3D map. It is as compatible with the acquired images as its unmirrored version from the image processing point of view, only that it is not biologically plausible.

In this article, we introduce HaPi (Handedness Pipeline), the first method to automatically determine the hand of electron density maps of macromolecules solved by CryoEM. HaPi is built by training two 3D convolutional neural networks. The first determines α-helices in a map, and the second determines whether the α-helix is left-handed or right-handed. A consensus strategy defines the overall map hand. The pipeline is trained on simulated and experimental data. The handedness can be detected only for maps whose resolution is better than 5Å. HaPi can identify the hand in 89% of new simulated maps correctly. Moreover, we evaluated all the maps deposited at the Electron Microscopy Data Bank and 11 structures uploaded with the incorrect hand were identified.

Electron microscopy

Single Particle Analysis

Validation

© 2022 The Author(s). Published by Elsevier Inc.