Improving Protein Expression, Stability, and Function with ProteinMPNN.

Natural proteins are highly optimized for function but are often difficult to produce at a scale suitable for biotechnological applications due to poor expression in heterologous systems, limited solubility, and sensitivity to temperature. Thus, a general method that improves the physical properties of native proteins while maintaining function could have wide utility for protein-based technologies. Here, we show that the deep neural network ProteinMPNN, together with evolutionary and structural information, provides a route to increasing protein expression, stability, and function. For both myoglobin and tobacco etch virus (TEV) protease, we generated designs with improved expression, elevated melting temperatures, and improved function. For TEV protease, we identified multiple designs with improved catalytic activity as compared to the parent sequence and previously reported TEV variants. Our approach should be broadly useful for improving the expression, stability, and function of biotechnologically important proteins.

Hallucination of closed repeat proteins containing central pockets.

In pseudocyclic proteins, such as TIM barrels, ß barrels, and some helical transmembrane channels, a single subunit is repeated in a cyclic pattern, giving rise to a central cavity that can serve as a pocket for ligand binding or enzymatic activity. Inspired by these proteins, we devised a deep-learning-based approach to broadly exploring the space of closed repeat proteins starting from only a specification of the repeat number and length. Biophysical data for 38 structurally diverse pseudocyclic designs produced in Escherichia coli are consistent with the design models, and the three crystal structures we were able to obtain are very close to the designed structures. Docking studies suggest the diversity of folds and central pockets provide effective starting points for designing small-molecule binders and enzymes.

De novo design of monomeric helical bundles for pH-controlled membrane lysis.

Targeted intracellular delivery via receptor-mediated endocytosis requires the delivered cargo to escape the endosome to prevent lysosomal degradation. This can in principle be achieved by membrane lysis tightly restricted to endosomal membranes upon internalization to avoid general membrane insertion and lysis. Here, we describe the design of small monomeric proteins with buried histidine containing pH-responsive hydrogen bond networks and membrane permeating amphipathic helices. Of the 30 designs that were experimentally tested, all expressed in Escherichia coli, 13 were monomeric with the expected secondary structure, and 4 designs disrupted artificial liposomes in a pH-dependent manner. Mutational analysis showed that the buried histidine hydrogen bond networks mediate pH-responsiveness and control lysis of model membranes within a very narrow range of pH (6.0-5.5) with almost no lysis occurring at neutral pH. These tightly controlled lytic monomers could help mediate endosomal escape in designed targeted delivery platforms.

De novo design of protein structure and function with RFdiffusion.

There has been considerable recent progress in designing new proteins using deep-learning methods1-9. Despite this progress, a general deep-learning framework for protein design that enables solution of a wide range of design challenges, including de novo binder design and design of higher-order symmetric architectures, has yet to be described. Diffusion models10,11 have had considerable success in image and language generative modelling but limited success when applied to protein modelling, probably due to the complexity of protein backbone geometry and sequence-structure relationships. Here we show that by fine-tuning the RoseTTAFold structure prediction network on protein structure denoising tasks, we obtain a generative model of protein backbones that achieves outstanding performance on unconditional and topology-constrained protein monomer design, protein binder design, symmetric oligomer design, enzyme active site scaffolding and symmetric motif scaffolding for therapeutic and metal-binding protein design. We demonstrate the power and generality of the method, called RoseTTAFold diffusion (RFdiffusion), by experimentally characterizing the structures and functions of hundreds of designed symmetric assemblies, metal-binding proteins and protein binders. The accuracy of RFdiffusion is confirmed by the cryogenic electron microscopy structure of a designed binder in complex with influenza haemagglutinin that is nearly identical to the design model. In a manner analogous to networks that produce images from user-specified inputs, RFdiffusion enables the design of diverse functional proteins from simple molecular specifications.

Stepwise design of pseudosymmetric protein hetero-oligomers.

Pseudosymmetric hetero-oligomers with three or more unique subunits with overall structural (but not sequence) symmetry play key roles in biology, and systematic approaches for generating such proteins de novo would provide new routes to controlling cell signaling and designing complex protein materials. However, the de novo design of protein hetero-oligomers with three or more distinct chains with nearly identical structures is a challenging problem because it requires the accurate design of multiple protein-protein interfaces simultaneously. Here, we describe a divide-and-conquer approach that breaks the multiple-interface design challenge into a set of more tractable symmetric single-interface redesign problems, followed by structural recombination of the validated homo-oligomers into pseudosymmetric hetero-oligomers. Starting from de novo designed circular homo-oligomers composed of 9 or 24 tandemly repeated units, we redesigned the inter-subunit interfaces to generate 15 new homo-oligomers and recombined them to make 17 new hetero-oligomers, including ABC heterotrimers, A2B2 heterotetramers, and A3B3 and A2B2C2 heterohexamers which assemble with high structural specificity. The symmetric homo-oligomers and pseudosymmetric hetero-oligomers generated for each system share a common backbone, and hence are ideal building blocks for generating and functionalizing larger symmetric assemblies.

Scaffolding protein functional sites using deep learning.

The binding and catalytic functions of proteins are generally mediated by a small number of functional residues held in place by the overall protein structure. Here, we describe deep learning approaches for scaffolding such functional sites without needing to prespecify the fold or secondary structure of the scaffold. The first approach, "constrained hallucination," optimizes sequences such that their predicted structures contain the desired functional site. The second approach, "inpainting," starts from the functional site and fills in additional sequence and structure to create a viable protein scaffold in a single forward pass through a specifically trained RoseTTAFold network. We use these two methods to design candidate immunogens, receptor traps, metalloproteins, enzymes, and protein-binding proteins and validate the designs using a combination of in silico and experimental tests.

Thermodynamically coupled biosensors for detecting neutralizing antibodies against SARS-CoV-2 variants.

We designed a protein biosensor that uses thermodynamic coupling for sensitive and rapid detection of neutralizing antibodies against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants in serum. The biosensor is a switchable, caged luciferase-receptor-binding domain (RBD) construct that detects serum-antibody interference with the binding of virus RBD to angiotensin-converting enzyme 2 (ACE-2) as a proxy for neutralization. Our coupling approach does not require target modification and can better distinguish sample-to-sample differences in analyte binding affinity and abundance than traditional competition-based assays.

Reconfigurable asymmetric protein assemblies through implicit negative design.

Asymmetric multiprotein complexes that undergo subunit exchange play central roles in biology but present a challenge for design because the components must not only contain interfaces that enable reversible association but also be stable and well behaved in isolation. We use implicit negative design to generate ß sheet-mediated heterodimers that can be assembled into a wide variety of complexes. The designs are stable, folded, and soluble in isolation and rapidly assemble upon mixing, and crystal structures are close to the computational models. We construct linearly arranged hetero-oligomers with up to six different components, branched hetero-oligomers, closed C4-symmetric two-component rings, and hetero-oligomers assembled on a cyclic homo-oligomeric central hub and demonstrate that such complexes can readily reconfigure through subunit exchange. Our approach provides a general route to designing asymmetric reconfigurable protein systems.

Detection of antibodies neutralizing historical and emerging SARS-CoV-2 strains using a thermodynamically coupled de novo biosensor system.

With global vaccination efforts against SARS-CoV-2 underway, there is a need for rapid quantification methods for neutralizing antibodies elicited by vaccination and characterization of their strain dependence. Here, we describe a designed protein biosensor that enables sensitive and rapid detection of neutralizing antibodies against wild type and variant SARS-CoV-2 in serum samples. More generally, our thermodynamic coupling approach can better distinguish sample to sample differences in analyte binding affinity and abundance than traditional competition based assays.

Protein sequence design by conformational landscape optimization.

The protein design problem is to identify an amino acid sequence that folds to a desired structure. Given Anfinsen's thermodynamic hypothesis of folding, this can be recast as finding an amino acid sequence for which the desired structure is the lowest energy state. As this calculation involves not only all possible amino acid sequences but also, all possible structures, most current approaches focus instead on the more tractable problem of finding the lowest-energy amino acid sequence for the desired structure, often checking by protein structure prediction in a second step that the desired structure is indeed the lowest-energy conformation for the designed sequence, and typically discarding a large fraction of designed sequences for which this is not the case. Here, we show that by backpropagating gradients through the transform-restrained Rosetta (trRosetta) structure prediction network from the desired structure to the input amino acid sequence, we can directly optimize over all possible amino acid sequences and all possible structures in a single calculation. We find that trRosetta calculations, which consider the full conformational landscape, can be more effective than Rosetta single-point energy estimations in predicting folding and stability of de novo designed proteins. We compare sequence design by conformational landscape optimization with the standard energy-based sequence design methodology in Rosetta and show that the former can result in energy landscapes with fewer alternative energy minima. We show further that more funneled energy landscapes can be designed by combining the strengths of the two approaches: the low-resolution trRosetta model serves to disfavor alternative states, and the high-resolution Rosetta model serves to create a deep energy minimum at the design target structure.

Selective Affimers Recognise the BCL-2 Family Proteins BCL-xL and MCL-1 through Noncanonical Structural Motifs*.

The BCL-2 family is a challenging group of proteins to target selectively due to sequence and structural homologies across the family. Selective ligands for the BCL-2 family regulators of apoptosis are useful as probes to understand cell biology and apoptotic signalling pathways, and as starting points for inhibitor design. We have used phage display to isolate Affimer reagents (non-antibody-binding proteins based on a conserved scaffold) to identify ligands for MCL-1, BCL-xL , BCL-2, BAK and BAX, then used multiple biophysical characterisation methods to probe the interactions. We established that purified Affimers elicit selective recognition of their target BCL-2 protein. For anti-apoptotic targets BCL-xL and MCL-1, competitive inhibition of their canonical protein-protein interactions is demonstrated. Co-crystal structures reveal an unprecedented mode of molecular recognition; where a BH3 helix is normally bound, flexible loops from the Affimer dock into the BH3 binding cleft. Moreover, the Affimers induce a change in the target proteins towards a desirable drug-bound-like conformation. These proof-of-concept studies indicate that Affimers could be used as alternative templates to inspire the design of selective BCL-2 family modulators and more generally other protein-protein interaction inhibitors.

De novo design of protein logic gates.

The design of modular protein logic for regulating protein function at the posttranscriptional level is a challenge for synthetic biology. Here, we describe the design of two-input AND, OR, NAND, NOR, XNOR, and NOT gates built from de novo-designed proteins. These gates regulate the association of arbitrary protein units ranging from split enzymes to transcriptional machinery in vitro, in yeast and in primary human T cells, where they control the expression of the TIM3 gene related to T cell exhaustion. Designed binding interaction cooperativity, confirmed by native mass spectrometry, makes the gates largely insensitive to stoichiometric imbalances in the inputs, and the modularity of the approach enables ready extension to three-input OR, AND, and disjunctive normal form gates. The modularity and cooperativity of the control elements, coupled with the ability to de novo design an essentially unlimited number of protein components, should enable the design of sophisticated posttranslational control logic over a wide range of biological functions.

Extrinsic conditions influence the self-association and structure of IF1, the regulatory protein of mitochondrial ATP synthase.

The endogenous inhibitor of ATP synthase in mitochondria, called IF1, conserves cellular energy when the proton-motive force collapses by inhibiting ATP hydrolysis. Around neutrality, the 84-amino-acid bovine IF1 is thought to self-assemble into active dimers and, under alkaline conditions, into inactive tetramers and higher oligomers. Dimerization is mediated by formation of an antiparallel α-helical coiled-coil involving residues 44-84. The inhibitory region of each monomer from residues 1-46 is largely α-helical in crystals, but disordered in solution. The formation of the inhibited enzyme complex requires the hydrolysis of two ATP molecules, and in the complex the disordered region from residues 8-13 is extended and is followed by an α-helix from residues 14-18 and a longer α-helix from residue 21, which continues unbroken into the coiled-coil region. From residues 21-46, the long α-helix binds to other α-helices in the C-terminal region of predominantly one of the ß-subunits in the most closed of the three catalytic interfaces. The definition of the factors that influence the self-association of IF1 is a key to understanding the regulation of its inhibitory properties. Therefore, we investigated the influence of pH and salt-types on the self-association of bovine IF1 and the folding of its unfolded region. We identified the equilibrium between dimers and tetramers as a potential central factor in the in vivo modulation of the inhibitory activity and suggest that the intrinsically disordered region makes its inhibitory potency exquisitely sensitive and responsive to physiological changes that influence the capability of mitochondria to make ATP.

Stereodivergent Evolution of Artificial Enzymes for the Michael Reaction.

Enzymes are valuable biocatalysts for asymmetric synthesis due to their exacting stereocontrol. Changing the selectivity of an existing catalyst for new applications is, however, challenging. Here we show that, in contrast, the stereoselectivity of an artificial enzyme created by design and directed evolution is readily tunable. We engineered a promiscuous artificial retro-aldolase into four stereocomplementary catalysts for the Michael addition of a tertiary carbanion to an unsaturated ketone. Notably, this selectivity is also preserved with alternative Michael nucleophiles. Complete stereodiversification of other designer enzymes should similarly be possible by extension of these approaches.

Affinity of IDPs to their targets is modulated by ion-specific changes in kinetics and residual structure.

Intrinsically disordered proteins (IDPs) are characterized by a lack of defined structure. Instead, they populate ensembles of rapidly interconverting conformations with marginal structural stabilities. Changes in solution conditions such as temperature and crowding agents consequently affect IDPs more than their folded counterparts. Here we reveal that the residual structure content of IDPs is modulated both by ionic strength and by the type of ions present in solution. We show that these ion-specific structural changes result in binding affinity shifts of up to sixfold, which happen through alteration of both association and dissociation rates. These effects follow the Hofmeister series, but unlike the well-established effects on the stability of folded proteins, they already occur at low, hypotonic concentrations of salt. We attribute this sensitivity to the marginal stability of IDPs, which could have physiological implications given the role of IDPs in signaling, the asymmetric ion profiles of different cellular compartments, and the role of ions in biology.

Fast Knoevenagel Condensations Catalyzed by an Artificial Schiff-Base-Forming Enzyme.

The simple catalytic motifs utilized by enzymes created by computational design and directed evolution constitute a potentially valuable source of chemical promiscuity. Here we show that the artificial retro-aldolase RA95.5-8 is able to use a reactive lysine in a hydrophobic pocket to accelerate promiscuous Knoevenagel condensations of electron-rich aldehydes and activated methylene donors. Optimization of this activity by directed evolution afforded an efficient enzyme variant with a catalytic proficiency of 5 × 10(11) M(-1) and a >10(8)-fold catalytic advantage over simple primary and secondary amines. Divergent evolution of de novo enzymes in this way could be a promising strategy for creating tailored biocatalysts for many synthetically useful reactions.

Insights into Coupled Folding and Binding Mechanisms from Kinetic Studies.

Intrinsically disordered proteins (IDPs) are characterized by a lack of persistent structure. Since their identification more than a decade ago, many questions regarding their functional relevance and interaction mechanisms remain unanswered. Although most experiments have taken equilibrium and structural perspectives, fewer studies have investigated the kinetics of their interactions. Here we review and highlight the type of information that can be gained from kinetic studies. In particular, we show how kinetic studies of coupled folding and binding reactions, an important class of signaling event, are needed to determine mechanisms.

Functional dissection of intersubunit interactions in the EspR virulence regulator of Mycobacterium tuberculosis.

The nucleoid-associated protein EspR, a chromosome organizer, has pleiotropic effects on expression of genes associated with cell wall function and pathogenesis in Mycobacterium tuberculosis. In particular, EspR binds to several sites upstream of the espACD locus to promote its expression, thereby ensuring full function of the ESX-1 secretion system, a major virulence determinant. The N terminus of EspR contains the helix-turn-helix DNA-binding domain, whereas the C-terminal dimerization domain harbors residues involved in intersubunit interactions. While direct binding to DNA appears to be mediated by an EspR dimer-of-dimers, where two helix-turn-helix motifs remain free for long-range interactions, the mechanism of EspR higher-order organization and its impact on chromosome structure and gene expression are not understood. To investigate these processes, we identified seven amino acid residues using molecular dynamics and replaced them with Ala in order to probe interactions at either the dimer or the dimer-of-dimers interfaces. Arg70, Lys72, and Arg101 were important for protein stability and optimal DNA-binding activity. Moreover, the Arg70 mutant showed decreased dimerization in a mycobacterial two-hybrid system. To correlate these defects with higher-order organization and transcriptional activity, we used atomic force microscopy to observe different EspR mutant proteins in complex with the espACD promoter region. In addition, complementation of an M. tuberculosis espR knockout mutant was performed to measure their impact on EspA expression. Our results pinpoint key residues required for EspR function at the dimer (Arg70) and the dimer-of-dimers (Lys72) interface and demonstrate that EspR dimerization and higher-order oligomerization modulate espACD transcriptional activity and hence pathogenesis.

TAL effectors specificity stems from negative discrimination.

Transcription Activator-Like (TAL) effectors are DNA-binding proteins secreted by phytopathogenic bacteria that interfere with native cellular functions by binding to plant DNA promoters. The key element of their architecture is a domain of tandem-repeats with almost identical sequences. Most of the polymorphism is located at two consecutive amino acids termed Repeat Variable Diresidue (RVD). The discovery of a direct link between the RVD composition and the targeted nucleotide allowed the design of TAL-derived DNA-binding tools with programmable specificities that revolutionized the field of genome engineering. Despite structural data, the molecular origins of this specificity as well as the recognition mechanism have remained unclear. Molecular simulations of the recent crystal structures suggest that most of the protein-DNA binding energy originates from non-specific interactions between the DNA backbone and non-variable residues, while RVDs contributions are negligible. Based on dynamical and energetic considerations we postulate that, while the first RVD residue promotes helix breaks--allowing folding of TAL as a DNA-wrapping super-helix--the second provides specificity through a negative discrimination of matches. Furthermore, we propose a simple pharmacophore-like model for the rationalization of RVD-DNA interactions and the interpretation of experimental findings concerning shared affinities and binding efficiencies. The explanatory paradigm presented herein provides a better comprehension of this elegant architecture and we hope will allow for improved designs of TAL-derived biotechnological tools.

Three bronze medals for Switzerland at the 45(th) International Chemistry Olympiad in Moscow, Russia.

A team of four students from Swiss high schools, selected in a national competition and accompanied by their mentors, represented their country at the 45(th) International Chemistry Olympiad (IChO) held in July 2013 in Moscow, Russia. The exceptional performances of Patrik Willi, Boris Stolz and Mario De Capitani in both practical and theoretical chemistry were rewarded by three bronze medals at the international level, reflecting their efforts during the year-long preparation prior to the competition.