Physical interactions between proteins are essential for most biological processes governing life1. However, the molecular determinants of such interactions have been challenging to understand, even as genomic, proteomic and structural data increase. This knowledge gap has been a major obstacle for the comprehensive understanding of cellular protein–protein interaction networks and for the de novo design of protein binders that are crucial for synthetic biology and translational applications2–9. Here we use a geometric deep-learning framework operating on protein surfaces that generates fingerprints to describe geometric and chemical features that are critical to drive protein–protein interactions10. We hypothesized that these fingerprints capture the key aspects of molecular recognition that represent a new paradigm in the computational design of novel protein interactions. As a proof of principle, we computationally designed several de novo protein binders to engage four protein targets: SARS-CoV-2 spike, PD-1, PD-L1 and CTLA-4. Several designs were experimentally optimized, whereas others were generated purely in silico, reaching nanomolar affinity with structural and mutational characterization showing highly accurate predictions. Overall, our surface-centric approach captures the physical and chemical determinants of molecular recognition, enabling an approach for the de novo design of protein interactions and, more broadly, of artificial proteins with function.
Polysaccharides play critical roles in bacteria, including the formation of protective capsules and biofilms and for establishing specific host cell interactions. Their transport across membranes is often mediated by ABC transporters, which utilize ATP to translocate diverse molecules. Cyclic b-glucans (CbGs) are critical for host interaction of the Rhizobiales, including the zoonotic pathogen Brucella. CbGs are exported into the periplasmic space by the cyclic glucan transporter (Cgt). The interaction of an ABC transporter with a polysaccharide substrate has not been visualized so far. Here we use single-particle cryo-electron microscopy (cryo-EM) to elucidate the structures of Cgt from Brucella abortus in four conformational states. The substrate-bound structure reveals an unusual binding pocket at the height of the cytoplasmic leaflet, while ADP-vanadate models hint to an alternative mechanism of substrate release. Our work provides insights into the translocation of large, heterogenous substrates and sheds light on protein-polysaccharide interactions in general.
The CRISPR-guided caspase (Craspase) complex is an assembly of the target-specific RNA nuclease known as Cas7-11 bound to CRISPR RNA (crRNA) and an ancillary protein known as TPR-CHAT (tetratricopeptide repeats (TPR) fused with a CHAT domain). The Craspase complex holds promise as a tool for gene therapy and biomedical research, but its regulation is poorly understood. TPR-CHAT regulates Cas7-11 nuclease activity via an unknown mechanism. In the present study, we use cryoelectron microscopy to determine structures of the Desulfonema magnum (Dm) Craspase complex to gain mechanistic insights into its regulation. We show that DmTPR-CHAT stabilizes crRNA-bound DmCas7-11 in a closed conformation via a network of interactions mediated by the DmTPR-CHAT N-terminal domain, the DmCas7-11 insertion finger and Cas11-like domain, resulting in reduced target RNA accessibility and cleavage.
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