The dynamic ribosome–translocon complex, which resides at the endoplasmic reticulum (ER) membrane, produces a major fraction of the human proteome1,2. It governs the synthesis, translocation, membrane insertion, N-glycosylation, folding and disulfide-bond formation of nascent proteins. Although individual components of this machinery have been studied at high resolution in isolation3–7, insights into their interplay in the native membrane remain limited. Here we use cryo-electron tomography, extensive classification and molecular modelling to capture snapshots of mRNA translation and protein maturation at the ER membrane at molecular resolution. We identify a highly abundant classical pre-translocation intermediate with eukaryotic elongation factor 1a (eEF1a) in an extended conformation, suggesting that eEF1a may remain associated with the ribosome after GTP hydrolysis during proofreading. At the ER membrane, distinct polysomes bind to different ER translocons specialized in the synthesis of proteins with signal peptides or multipass transmembrane proteins with the translocon-associated protein complex (TRAP) present in both. The near-complete atomic model of the most abundant ER translocon variant comprising the protein-conducting channel SEC61, TRAP and the oligosaccharyltransferase complex A (OSTA) reveals specific interactions of TRAP with other translocon components. We observe stoichiometric and sub-stoichiometric cofactors associated with OSTA, which are likely to include protein isomerases. In sum, we visualize ER-bound polysomes with their coordinated downstream machinery.

Cellular functions are governed by molecular machines that assemble through protein-protein interactions. Their atomic details are critical to studying their molecular mechanisms. However, fewer than 5% of hundreds of thousands of human protein interactions have been structurally characterized. Here we test the potential and limitations of recent progress in deep-learning methods using AlphaFold2 to predict structures for 65,484 human protein interactions. We show that experiments can orthogonally confirm higher-confidence models. We identify 3,137 high-confidence models, of which 1,371 have no homology to a known structure. We identify interface residues harboring disease mutations, suggesting potential mechanisms for pathogenic variants. Groups of interface phosphorylation sites show patterns of co-regulation across conditions, suggestive of coordinated tuning of multiple protein interactions as signaling responses. Finally, we provide examples of how the predicted binary complexes can be used to build larger assemblies helping to expand our understanding of human cell biology.

Grana are a characteristic feature of higher plants’ thylakoid membranes, consisting of stacks of appressed membranes enriched in Photosystem II (PSII) and associated light-harvesting complex II (LHCII) proteins, together forming the PSII-LHCII supercomplex. Grana stacks undergo light-dependent structural changes, mainly by reorganizing the supramolecular structure of PSII-LHCII supercomplexes. LHCII is vital for grana formation, in which also PSII-LHCII supercomplexes are involved. By combining top-down and crosslinking mass spectrometry we uncover the spatial organization of paired PSII-LHCII supercomplexes within thylakoid membranes. The resulting model highlights a basic molecular mechanism whereby plants maintain grana stacking at changing light conditions. This mechanism relies on interactions between stroma-exposed N-terminal loops of LHCII trimers and Lhcb4 subunits facing each other in adjacent membranes. The combination of light-dependent LHCII N-terminal trimming and extensive N-terminal α-acetylation likely affects interactions between pairs of PSII-LHCII supercomplexes across the stromal gap, ultimately mediating membrane folding in grana stacks.

Cross-linking mass spectrometry (XL-MS) is an efficient technique for uncovering structural features and interactions of the in-solution state of the proteins under investigation. Distance constraints obtained by this technique are highly complementary to classical structural biology approaches like X-ray crystallography and cryo-EM and have successfully been leveraged to shed light on protein structures of increasing size and complexity. To accomplish this, small reagents are used that typically incorporate two amine reactive moieties connected by a spacer arm and that can be applied in solution to protein structures of any size. Over the years, many reagents initially developed for different applications were adopted, and others were specifically developed for XL-MS. This has resulted in a vast array of options, making it difficult to make the right choice for specific experiments. Here, we delve into the previous decade of published XL-MS literature to uncover which workflows have been predominantly applied. We focus on application papers as these represent proof that biologically valid results can be extracted. This ignores some more recent approaches that did not have sufficient time to become more widely applied, for which we supply a separate discussion. From our selection, we extract information on the types of samples, cross-linking reagent, prefractionation, instruments, and data analysis, to highlight widely used workflows. All of the results are summarized in an easy-to-use flow chart defined by selection points resulting from our analysis. Although potentially biased by our own experiences, we expect this overview to be useful for novices stepping into this rapidly expanding field.