Particles in micrographs were selected with the EMAN2 boxer (45) and Gautomatch (www.mrc-lmb.cam.ac.uk/kzhang/Gautomatch/) programs. During the initial processing, 2176 particles were automatically selected from 100 preselected images with reference-free Gautomatch localization. The selected particles were inspected with the e2boxer.py script and 2D classified in Relion 2.1 (46). A few high-resolution 2D classes were low-pass–filtered to 30 Å and used as templates for Gautomatch particle selection on all aligned images. This larger dataset of particles was 2D classified in Relion 2.1, and 30 high-resolution class averages covering a broader range of views were selected as templates for another round of Gautomatch particle selection. The final particle selection resulted in a total of 197,171 particles, which were reprocessed with Relion 2.1. After seven rounds of 2D classification, a 2D class average representing the face-view of PDE6 (fig. S3D) was used to create a rotationally symmetric starting model for 3D processing. The Fourier transform of the selected projection was low-pass–filtered to 60 Å and rotated around the long axis of the class average. The created 3D Fourier volume was back-transformed to obtain the initial real-space 3D model.

The 2D class averages comprising 85,929 particles were subjected to three rounds of 3D classification with the 60-Å rotationally symmetric model as a reference (fig. S6A). The resulting five 3D classes were used to generate the initial map of PDE6 at a resolution of 8.2 Å, which was subjected to the e2project.py script of EMAN2 to compute 30 reprojections covering views from all directions to serve as templates for the final round of Gautomatch particle selection. The final dataset comprising 199,658 particles was processed by Relion 2.1. Five rounds of 2D classification reduced the dataset to 82,558 particles, which were subjected to three rounds of 3D classification (with seven, five, and five 3D classes, respectively) with the rotationally symmetric initial 3D model as a reference (fig. S6A). Two identical 3D classes displaying a resolution of 8.3 Å and comprising a total of 43,597 particles were combined into a single dataset. The combined dataset was then refined against one of the two 8.3-Å 3D classes, which was low-pass–filtered to 35 Å. Upon masking and modulation transfer function correction, the reconstructions reached a resolution of 4.1 Å, as measured by Fourier shell correlation (FSC) of a refinement in which two halves of the dataset were refined separately and combined only when building the final map (fig. S6A). The same dataset was then reprocessed with the cisTEM program (47) that uses per-particle CTF refinement and B-factor particle weighting. The final 3D reconstruction reached a resolution of 3.4 Å at an FSC of 0.143 (fig. S6B) (48). Local resolution distribution of the final map was determined by ResMap (49). The data acquisition and processing of PDE6αβ2γ treated with sildenafil was done under identical conditions as the untreated PDE6αβ2γ holoenzyme. In total, 4780 images were acquired, from which 223,656 particles were isolated and subjected to 2D classification.

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