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There has been considerable progress in the development of computational methods for designing protein-protein interactions, but engineering high-affinity binders without extensive screening and maturation remains challenging. Here, we test a protein design pipeline that uses iterative rounds of deep learning (DL)-based structure prediction (AlphaFold2) and sequence optimization (ProteinMPNN) to design autoinhibitory domains (AiDs) for a PD-L1 antagonist. Inspired by recent advances in therapeutic design, we sought to create autoinhibited (or masked) forms of the antagonist that can be conditionally activated by proteases. Twenty-threede novodesigned AiDs, varying in length and topology, were fused to the antagonist with a protease sensitive linker, and binding to PD-L1 was tested with and without protease treatment. Nine of the fusion proteins demonstrated conditional binding to PD-L1 and the top performing AiDs were selected for further characterization as single domain proteins. Without any experimental affinity maturation, four of the AiDs bind to the PD-L1 antagonist with equilibrium dissociation constants (KDs) below 150 nM, with the lowest KDequal to 0.9 nM. Our study demonstrates that DL-based protein modeling can be used to rapidly generate high affinity protein binders.Significance statementProtein-protein interactions are critical to most processes in biology, and improved methods for designing protein binders will enable the creation of new research reagents, diagnostics, and therapeutics. In this study, we show that a deep learning-based method for protein design can create high-affinity protein binders without the need for extensive screening or affinity maturation.

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Chimeric antigen receptor (CAR) tonic signaling, defined as spontaneous activation and release of proinflammatory cytokines by CAR-T cells, is considered a negative attribute because it leads to impaired antitumor effects. Here, we report that CAR tonic signaling is caused by the intrinsic instability of the mAb single-chain variable fragment (scFv) to promote self-aggregation and signaling via the CD3ζ chain incorporated into the CAR construct. This phenomenon was detected in a CAR encoding either CD28 or 4-1BB costimulatory endodomains. Instability of the scFv was caused by specific amino acids within the framework regions (FWR) that can be identified by computational modeling. Substitutions of the amino acids causing instability, or humanization of the FWRs, corrected tonic signaling of the CAR, without modifying antigen specificity, and enhanced the antitumor effects of CAR-T cells. Overall, we demonstrated that tonic signaling of CAR-T cells is determined by the molecular instability of the scFv and that computational analyses of the scFv can be implemented to correct the scFv instability in CAR-T cells with either CD28 or 4-1BB costimulation.

Many protein therapeutics are competitive inhibitors that function by binding to endogenous proteins and preventing them from interacting with native partners. One effective strategy for engineering competitive inhibitors is to graft structural motifs from a native partner into a host protein. Here, we develop and experimentally test a computational protocol for embedding binding motifs in de novo designed proteins. The protocol uses an “inside-out” approach: Starting with a structural model of the binding motif docked against the target protein, the de novo protein is built by growing new structural elements off the termini of the binding motif. During backbone assembly, a score function favors backbones that introduce new tertiary contacts within the designed protein and do not introduce clashes with the target binding partner. Final sequences are designed and optimized using the molecular modeling program Rosetta. To test our protocol, we designed small helical proteins to inhibit the interaction between Gαqand its effector PLC-β isozymes. Several of the designed proteins remain folded above 90°C and bind to Gαqwith equilibrium dissociation constants tighter than 80 nM. In cellular assays with oncogenic variants of Gαq, the designed proteins inhibit activation of PLC-β isozymes and Dbl-family RhoGEFs. Our results demonstrate that computational protein design, in combination with motif grafting, can be used to directly generate potent inhibitors without further optimization via high throughput screening or selection.statement for broader audienceEngineered proteins that bind to specific target proteins are useful as research reagents, diagnostics, and therapeutics. We used computational protein design to engineer de novo proteins that bind and competitively inhibit the G protein, Gαq, which is an oncogene for uveal melanomas. This computational method is a general approach that should be useful for designing competitive inhibitors against other proteins of interest.

Many proteins have low thermodynamic stability, which can lead to low expression yields and limit functionality in research, industrial and clinical settings. This article introduces two, web-based tools that use the high-resolution structure of a protein along with the Rosetta molecular modeling program to predict stabilizing mutations. The protocols were recently applied to three genetically and structurally distinct proteins and successfully predicted mutations that improved thermal stability and/or protein yield. In all three cases, combining the stabilizing mutations raised the protein unfolding temperatures by more than 20°C. The first protocol evaluates point mutations and can generate a site saturation mutagenesis heatmap. The second identifies mutation clusters around user-defined positions. Both applications only require a protein structure and are particularly valuable when a deep multiple sequence alignment is not available. These tools were created to simplify protein engineering and enable research that would otherwise be infeasible due to poor expression and stability of the native molecule.

Biomolecular structure drives function, and computational capabilities have progressed such that the prediction and computational design of biomolecular structures is increasingly feasible. Because computational biophysics attracts students from many different backgrounds and with different levels of resources, teaching the subject can be challenging. One strategy to teach diverse learners is with interactive multimedia material that promotes self-paced, active learning. We have created a hands-on education strategy with a set of 16 modules that teach topics in biomolecular structure and design, from fundamentals of conformational sampling and energy evaluation to applications, such as protein docking, antibody design, and RNA structure prediction. Our modules are based on PyRosetta, a Python library that encapsulates all computational modules and methods in the Rosetta software package. The workshop-style modules are implemented as Jupyter Notebooks that can be executed in the Google Colaboratory, allowing learners access with just a Web browser. The digital format of Jupyter Notebooks allows us to embed images, molecular visualization movies, and interactive coding exercises. This multimodal approach may better reach students from different disciplines and experience levels, as well as attract more researchers from smaller labs and cognate backgrounds to leverage PyRosetta in science and engineering research. All materials are freely available at https://github.com/RosettaCommons/PyRosetta.notebooks.

Chimeric antigen receptor (CAR) tonic signaling, defined as spontaneous activation and release of proinflammatory cytokines by CAR-T cells, is considered a negative attribute because it leads to impaired antitumor effects. Here, we report that CAR tonic signaling is caused by the intrinsic instability of the mAb single-chain variable fragment (scFv) to promote self-aggregation and signaling via the CD3ζ chain incorporated into the CAR construct. This phenomenon was detected in a CAR encoding either CD28 or 4-1BB costimulatory endodomains. Instability of the scFv was caused by specific amino acids within the framework regions (FWR) that can be identified by computational modeling. Substitutions of the amino acids causing instability, or humanization of the FWRs, corrected tonic signaling of the CAR, without modifying antigen specificity, and enhanced the antitumor effects of CAR-T cells. Overall, we demonstrated that tonic signaling of CAR-T cells is determined by the molecular instability of the scFv and that computational analyses of the scFv can be implemented to correct the scFv instability in CAR-T cells with either CD28 or 4-1BB costimulation.

Using the molecular modeling program Rosetta, we designed a de novo protein, called SEWN0.1, which binds the heterotrimeric G protein Gα(q.) The design is helical, well‐folded, and primarily monomeric in solution at a concentration of 10 μM. However, when we solved the crystal structure of SEWN0.1 at 1.9 Å, we observed a dimer in a conformation incompatible with binding Gα(q). Unintentionally, we had designed a protein that adopts alternate conformations depending on its oligomeric state. Recently, there has been tremendous progress in the field of protein structure prediction as new methods in artificial intelligence have been used to predict structures with high accuracy. We were curious if the structure prediction method AlphaFold could predict the structure of SEWN0.1 and if the prediction depended on oligomeric state. When AlphaFold was used to predict the structure of monomeric SEWN0.1, it produced a model that resembles the Rosetta design model and is compatible with binding Gα(q), but when used to predict the structure of a dimer, it predicted a conformation that closely resembles the SEWN0.1 crystal structure. AlphaFold's ability to predict multiple conformations for a single protein sequence should be useful for engineering protein switches.

The FastDesign protocol in the molecular modeling program Rosetta iterates between sequence optimization and structure refinement to stabilize de novo designed protein structures and complexes. FastDesign has been used previously to design novel protein folds and assemblies with important applications in research and medicine. To promote sampling of alternative conformations and sequences, FastDesign includes stages where the energy landscape is smoothened by reducing repulsive forces. Here, we discover that this process disfavors larger amino acids in the protein core because the protein compresses in the early stages of refinement. By testing alternative ramping strategies for the repulsive weight, we arrive at a scheme that produces lower energy designs with more native-like sequence composition in the protein core. We further validate the protocol by designing and experimentally characterizing over 4000 proteins and show that the new protocol produces higher stability proteins. This article is protected by copyright. All rights reserved.

Promiscuous enzymes that modify peptides and proteins are powerful tools for labeling biomolecules; however, directing these modifications to desired substrates can be challenging. Here, we use computational interface design to install a substrate recognition domain adjacent to the active site of a promiscuous enzyme, catechol O-methyltransferase. This design approach effectively decouples substrate recognition from the site of catalysis and promotes modification of peptides recognized by the recruitment domain. We determined the crystal structure of this novel multidomain enzyme, SH3-588, which shows that it closely matches our design. SH3-588 methylates directed peptides with catalytic efficiencies exceeding the wild-type enzyme by over 1,000-fold, whereas peptides lacking the directing recognition sequence do not display enhanced efficiencies. In competition experiments, the designer enzyme preferentially modifies directed substrates over undirected substrates, suggesting that we can use designed recruitment domains to direct post-translational modifications to specific sequence motifs on target proteins in complex multisubstrate environments.

Understanding protein folding is crucial for protein sciences. The conformational spaces and energy landscapes of cold (unfolded) protein states, as well as the associated transitions, are hardly explored. Furthermore, it is not known how structure relates to the cooperativity of cold transitions, if cold and heat unfolded states are thermodynamically similar, and if cold states play important roles for protein function. We created the cold unfolding 4-helix bundle DCUB1 with a de novo designed bipartite hydrophilic/hydrophobic core featuring a hydrogen bond network which extends across the bundle in order to study the relative importance of hydrophobic versus hydrophilic protein-water interactions for cold unfolding. Structural and thermodynamic characterization resulted in the discovery of a complex energy landscape for cold transitions, while the heat unfolded state is a random coil. Below ∼0 °C, the core of DCUB1 disintegrates in a largely cooperative manner, while a near-native helical content is retained. The resulting cold core-unfolded state is compact and features extensive internal dynamics. Below -5 °C, two additional cold transitions are seen, that is, (i) the formation of a water-mediated, compact, and highly dynamic dimer, and (ii) the onset of cold helix unfolding decoupled from cold core unfolding. Our results suggest that cold unfolding is initiated by the intrusion of water into the hydrophilic core network and that cooperativity can be tuned by varying the number of core hydrogen bond networks. Protein design has proven to be invaluable to explore the energy landscapes of cold states and to robustly test related theories.

Using the molecular modeling program Rosetta, we designed a de novo protein, called SEWN0.1, that binds the heterotrimeric G protein Gαq. The design is helical, well-folded, and primarily monomeric in solution at a concentration of 10 uM. However, when we solved the crystal structure of SEWN0.1, we observed a dimer in a conformation incompatible with binding Gαq. Unintentionally, we had designed a protein that adopts alternate conformations depending on its oligomeric state. Recently, there has been tremendous progress in the field of protein structure prediction as new methods in artificial intelligence have been used to predict structures with high accuracy. We were curious if the structure prediction method AlphaFold could predict the structure of SEWN0.1 and if the prediction depended on oligomeric state. When AlphaFold was used to predict the structure of monomeric SEWN0.1, it produced a model that resembles the Rosetta design model and is compatible with binding Gαq, but when used to predict the structure of a dimer, it predicted a conformation that closely resembles the SEWN0.1 crystal structure. AlphaFold’s ability to predict multiple conformations for a single protein sequence should be useful for engineering protein switches.

Description, A stabilized dimer of the surface protein from dengue virus has been engineered to elicit antibodies that neutralize the virus., Dengue virus (DENV) is a worldwide health burden, and a safe vaccine is needed. Neutralizing antibodies bind to quaternary epitopes on DENV envelope (E) protein homodimers. However, recombinantly expressed soluble E proteins are monomers under vaccination conditions and do not present these quaternary epitopes, partly explaining their limited success as vaccine antigens. Using molecular modeling, we found DENV2 E protein mutations that induce dimerization at low concentrations (

Protein engineering has contributed to successes in the field of T cell-based immunotherapy, including chimeric antigen receptor (CAR) T cell therapy. CAR T cell therapy has become a pillar of cancer immunotherapy, demonstrating clinical effectiveness against B cell malignancies by targeting the B cell antigen CD19. Current gene editing techniques have limited safety controls over CAR T cell activity, which presents a hurdle for control of CAR T cells in patients. Alternatively, CAR T cell activity can be controlled by engineering CARs to bind soluble adapter molecules that direct the interaction between the CAR T cell and target cell. The flexibility in this adapter-mediated approach overcomes the rigid specificity of traditional CAR T cells to allow targeting of multiple cell types. Here we describe adapter CAR T technologies and how these methods emphasize the growing role of protein engineering in the design of programmable tools for T cell therapies.

Each year vast international resources are wasted on irreproducible research. The scientific community has been slow to adopt standard software engineering practices, despite the increases in high-dimensional data, complexities of workflows, and computational environments. Here we show how scientific software applications can be created in a reproducible manner when simple design goals for reproducibility are met. We describe the implementation of a test server framework and 40 scientific benchmarks, covering numerous applications in Rosetta bio-macromolecular modeling. High performance computing cluster integration allows these benchmarks to run continuously and automatically. Detailed protocol captures are useful for developers and users of Rosetta and other macromolecular modeling tools. The framework and design concepts presented here are valuable for developers and users of any type of scientific software and for the scientific community to create reproducible methods. Specific examples highlight the utility of this framework and the comprehensive documentation illustrates the ease of adding new tests in a matter of hours.

During signal transduction, the G protein, Gαq, binds and activates phospholipase C-β isozymes. Several diseases have been shown to manifest upon constitutively activating mutation of Gαq, such as uveal melanoma. Therefore, methods are needed to directly inhibit Gαq. Previously, we demonstrated that a peptide derived from a helix-turn-helix (HTH) region of PLC-β3 (residues 852–878) binds Gαq with low micromolar affinity and inhibits Gαq by competing with full-length PLC-β isozymes for binding. Since the HTH peptide is unstructured in the absence of Gαq, we hypothesized that embedding the HTH in a folded protein might stabilize the binding-competent conformation and further improve the potency of inhibition. Using the molecular modeling software Rosetta, we searched the Protein Data Bank for proteins with similar HTH structures near their surface. The candidate proteins were computationally docked against Gαq, and their surfaces were redesigned to stabilize this interaction. We then used yeast surface display to affinity mature the designs. The most potent design bound Gαq/i with high affinity in vitro (KD = 18 nM) and inhibited activation of PLC-β isozymes in HEK293 cells. We anticipate that our genetically encoded inhibitor will help interrogate the role of Gαq in healthy and disease model systems. Our work demonstrates that grafting interaction motifs into folded proteins is a powerful approach for generating inhibitors of protein–protein interactions.

Dengue viruses (DENV serotypes 1-4) and Zika virus (ZIKV) are related flaviviruses that continue to be a public health concern, infecting hundreds of millions of people annually. The traditional live-attenuated virus vaccine approach has been challenging for the four DENV serotypes because of the need to achieve balanced replication of four independent vaccine components. Subunit vaccines represent an alternative approach that may circumvent problems inherent with live-attenuated DENV vaccines. In mature virus particles, the envelope (E) protein forms a homodimer that covers the surface of the virus and is the major target of neutralizing antibodies. Many neutralizing antibodies bind to quaternary epitopes that span across both E proteins in the homodimer. For soluble E (sE) protein to be a viable subunit vaccine, the antigens should be easy to produce and retain quaternary epitopes recognized by neutralizing antibodies. However, WT sE proteins are primarily monomeric at conditions relevant for vaccination and exhibit low expression yields. Previously, we identified amino acid mutations that stabilize the sE homodimer from DENV2 and dramatically raise expression yields. Here, we tested whether these same mutations raise the stability of sE from other DENV serotypes and ZIKV. We show that the mutations raise thermostability for sE from all the viruses, increase production yields from 4-fold to 250-fold, stabilize the homodimer, and promote binding to dimer-specific neutralizing antibodies. Our findings suggest that these sE variants could be valuable resources in the efforts to develop effective subunit vaccines for DENV serotypes 1 to 4 and ZIKV.

Engineered, light-sensitive protein switches are used to interrogate a broad variety of biological processes. These switches are typically constructed by genetically fusing naturally occurring light-responsive protein domains with functional domains from other proteins. Protein activity can be controlled using a variety of mechanisms including light-induced colocalization, caging, and allosteric regulation. Protein design efforts have focused on reducing background signaling, maximizing the change in activity upon light stimulation, and perturbing the kinetics of switching. It is common to combine structure-based modeling with experimental screening to identify ideal fusion points between domains and discover point mutations that optimize switching. Here, we introduce commonly used light-sensitive domains and summarize recent progress in using them to regulate protein activity.

Phosphatidylinositol-3-kinases (PI3Ks) are lipid kinases that phosphorylate phosphatidylinositol 4,5-bisphosphate to generate a key lipid second messenger, phosphatidylinositol 3,4,5-bisphosphate. PI3Kα and PI3Kγ require activation by RAS proteins to stimulate signaling pathways that control cellular growth, differentiation, motility and survival. Intriguingly, RAS binding to PI3K isoforms likely differ, as RAS mutations have been identified that discriminate between PI3Kα and PI3Kγ, consistent with low sequence homology (23%) between their RAS binding domains (RBDs). As disruption of the RAS/PI3Kα interaction reduces tumor growth in mice with RAS- and epidermal growth factor receptor driven skin and lung cancers, compounds that interfere with this key interaction may prove useful as anti-cancer agents. However, a structure of PI3Kα bound to RAS is lacking, limiting drug discovery efforts. Expression of full-length PI3K isoforms in insect cells has resulted in low yield and variable activity, limiting biophysical and structural studies of RAS/PI3K interactions. This led us to generate the first RBDs from PI3Kα and PI3Kγ that can be expressed at high yield in bacteria and bind to RAS with similar affinity to full-length PI3K. We also solved a 2.31 A X-ray crystal structure of the PI3Kα-RBD, which aligns well to full-length PI3Kα. Structural differences between the PI3Kα and PI3Kγ RBDs are consistent with differences in thermal stability and may underly differential RAS recognition and RAS-mediated PI3K activation. These high expression, functional PI3K RBDs will aid in interrogating RAS interactions and could aid in identifying inhibitors of this key interaction.

Dengue virus (DENV) is responsible for the most prevalent and significant arthropod-borne viral infection of humans. The leading DENV vaccines are based on tetravalent live-attenuated virus platforms. In practice, it has been challenging to induce balanced and effective responses to each of the four DENV serotypes because of differences in the replication efficiency and immunogenicity of individual vaccine components. Unlike live vaccines, tetravalent DENV envelope (E) protein subunit vaccines are likely to stimulate balanced immune responses, because immunogenicity is replication independent. However, E protein subunit vaccines have historically performed poorly, in part because the antigens utilized were mainly monomers that did not display quaternary-structure epitopes found on E dimers and higher-order structures that form the viral envelope. In this study, we compared the immunogenicity of DENV2 E homodimers and DENV2 E monomers. The stabilized DENV2 homodimers, but not monomers, were efficiently recognized by virus-specific and flavivirus cross-reactive potently neutralizing antibodies that have been mapped to quaternary-structure epitopes displayed on the viral surface. In mice, the dimers stimulated 3-fold-higher levels of virus-specific neutralizing IgG that recognized epitopes different from those recognized by lower-level neutralizing antibodies induced by monomers. The dimer induced a stronger E domain I (EDI)- and EDII-targeted response, while the monomer antigens stimulated an EDIII epitope response and induced fusion loop epitope antibodies that are known to facilitate antibody-dependent enhancement (ADE). This study shows that DENV E subunit antigens that have been designed to mimic the structural organization of the viral surface are better vaccine antigens than E protein monomers. IMPORTANCE Dengue virus vaccine development is particularly challenging because vaccines have to provide protection against four different dengue virus stereotypes. The leading dengue virus vaccine candidates in clinical testing are all based on live-virus vaccine platforms and struggle to induce balanced immunity. Envelope subunit antigens have the potential to overcome these limitations but have historically performed poorly as vaccine antigens, because the versions tested previously were presented as monomers and not in their natural dimer configuration. This study shows that the authentic presentation of DENV2 E-based subunits has a strong impact on antibody responses, underscoring the importance of mimicking the complex protein structures that are found on DENV particle surfaces when designing subunit vaccines.

The FastDesign protocol in the molecular modeling program Rosetta iterates between sequence optimization and structure refinement to stabilize de novo designed protein structures and complexes. FastDesign has been used previously to design novel protein folds and assemblies with important applications in research and medicine. To promote sampling of alternative conformations and sequences, FastDesign includes stages where the energy landscape is smoothened by reducing repulsive forces. Here, we discover that this process disfavors larger amino acids in the protein core because the protein compresses in the early stages of refinement. By testing alternative ramping strategies for the repulsive weight, we arrive at a scheme that produces lower energy designs with more native-like sequence composition in the protein core. We further validate the protocol by designing and experimentally characterizing over 4000 proteins and show that the new protocol produces higher stability proteins.

Many scientific disciplines rely on computational methods for data analysis, model generation, and prediction. Implementing these methods is often accomplished by researchers with domain expertise but without formal training in software engineering or computer science. This arrangement has led to underappreciation of sustainability and maintainability of scientific software tools developed in academic environments. Some software tools have avoided this fate, including the scientific library Rosetta. We use this software and its community as a case study to show how modern software development can be accomplished successfully, irrespective of subject area. Rosetta is one of the largest software suites for macromolecular modeling, with 3.1 million lines of code and many state-of-the-art applications. Since the mid 1990s, the software has been developed collaboratively by the RosettaCommons, a community of academics from over 60 institutions worldwide with diverse backgrounds including chemistry, biology, physiology, physics, engineering, mathematics, and computer science. Developing this software suite has provided us with more than two decades of experience in how to effectively develop advanced scientific software in a global community with hundreds of contributors. Here we illustrate the functioning of this development community by addressing technical aspects (like version control, testing, and maintenance), community-building strategies, diversity efforts, software dissemination, and user support. We demonstrate how modern computational research can thrive in a distributed collaborative community. The practices described here are independent of subject area and can be readily adopted by other software development communities.

Histone H3 lysine 36 methylation (H3K36me) is a conserved histone modification associated with transcription and DNA repair. Although the effects of H3K36 methylation have been studied, the genome-wide dynamics of H3K36me deposition and removal are not known. We established rapid and reversible optogenetic control for Set2, the sole H3K36 methyltransferase in yeast, by fusing the enzyme with the light-activated nuclear shuttle (LANS) domain. Light activation resulted in efficient Set2-LANS nuclear localization followed by H3K36me3 deposition in vivo, with total H3K36me3 levels correlating with RNA abundance. Although genes showed disparate levels of H3K36 methylation, relative rates of H3K36me3 accumulation were largely linear and consistent across genes, suggesting that H3K36me3 deposition occurs in a directed fashion on all transcribed genes regardless of their overall transcription frequency. Removal of H3K36me3 was highly dependent on the demethylase Rph1. However, the per-gene rate of H3K36me3 loss weakly correlated with RNA abundance and followed exponential decay, suggesting H3K36 demethylases act in a global, stochastic manner. Altogether, these data provide a detailed temporal view of H3K36 methylation and demethylation that suggests transcription-dependent and -independent mechanisms for H3K36me deposition and removal, respectively.

Background: Histone H3 lysine 36 methylation (H3K36me) is a conserved histone modification associated with transcription and DNA repair. Although the effects of H3K36 methylation have been studied, the genome-wide dynamics of H3K36me deposition and removal are not known. Results: We established rapid and reversible optogenetic control for Set2, the sole H3K36 methyltransferase in yeast, by fusing the enzyme with the light activated nuclear shuttle (LANS) domain. Early H3K36me3 dynamics identified rapid methylation in vivo, with total H3K36me3 levels correlating with RNA abundance. Although genes exhibited disparate levels of H3K36 methylation, relative rates of H3K36me3 accumulation were largely linear and consistent across genes, suggesting a rate-limiting mechanism for H3K36me3 deposition. Removal of H3K36me3 was also rapid and highly dependent on the demethylase Rph1. However, the per-gene rate of H3K36me3 loss weakly correlated with RNA abundance and followed exponential decay, suggesting H3K36 demethylases act in a global, stochastic manner. Conclusion: Altogether, these data provide a detailed temporal view of H3K36 methylation and demethylation that suggest transcription-dependent and independent mechanisms for H3K36me deposition and removal, respectively.

Optogenetic techniques use light-responsive proteins to study dynamic processes in living cells and organisms. These techniques typically rely on repurposed naturally occurring light-sensitive proteins to control sub-cellular localization and activity. We previously engineered two optogenetic systems, the Light Activated Nuclear Shuttle (LANS) and the Light-Inducible Nuclear eXporter (LINX), by embedding nuclear import or export sequence motifs into the C-terminal helix of the light-responsive LOV2 domain of Avena sativa phototropin 1, thus enabling light-dependent trafficking of a target protein into and out of the nucleus. While LANS and LINX are effective tools, we posited that mutations within the LOV2 hinge-loop, which connects the core PAS domain and the C-terminal helix, would further improve the functionality of these switches. Here, we identify hinge-loop mutations that favourably shift the dynamic range (the ratio of the on- to off-target subcellular accumulation) of the LANS and LINX photoswitches. We demonstrate the utility of these new optogenetic tools to control gene transcription and epigenetic modifications, thereby expanding the optogenetic ‘tool kit’ for the research community.

UHRF1 is a histone- and DNA-binding E3 ubiquitin ligase that functions with DNMT1 to maintain mammalian DNA methylation. UHRF1 facilitates DNMT1 recruitment to replicating chromatin through a coordinated mechanism involving histone and DNA recognition and histone ubiquitination. UHRF2 shares structural homology with UHRF1, but surprisingly lacks functional redundancy to facilitate DNA methylation maintenance. Molecular mechanisms uncoupling UHRF2 from DNA methylation maintenance are poorly defined. Through comprehensive and comparative biochemical analysis of recombinant human UHRF1 and UHRF2 reader and writer activities, we reveal conserved modes of histone PTM recognition but divergent DNA binding properties. While UHRF1 and UHRF2 diverge in their affinities toward hemi-methylated DNA, we surprisingly show that both hemi-methylated and hemi-hydroxymethylated DNA oligonucleotides stimulate UHRF2 ubiquitin ligase activity toward histone H3 peptide substrates. This is the first example of an E3 ligase allosterically regulated by DNA hydroxymethylation. However, UHRF2 is not a productive histone E3 ligase toward purified mononucleosomes, suggesting UHRF2 has an intra-domain architecture distinct from UHRF1 that is conformationally constrained when bound to chromatin. Collectively, our studies reveal that uncoupling of UHRF2 from the DNA methylation maintenance program is linked to differences in the molecular readout of chromatin signatures that connect UHRF1 to ubiquitination of histone H3.

During signal transduction, the G protein, Gαq, binds and activates phospholipase C-β isozymes. Several diseases have been shown to manifest upon constitutively activating mutation of Gαq, such as uveal melanoma. Therefore, methods are needed to directly inhibit Gαq. Previously, we demonstrated that a peptide derived from a helix-turn-helix (HTH) region of PLC-β3 (residues 852-878) binds Gαq with low micromolar affinity and inhibits Gαq by competing with full-length PLC-β isozymes for binding. Since the HTH peptide is unstructured in the absence of Gαq, we hypothesized that embedding the HTH in a folded protein might stabilize the binding-competent conformation and further improve the potency of inhibition. Using the molecular modeling software Rosetta, we searched the Protein Data Bank for proteins with similar HTH structures near their surface. The candidate proteins were computationally docked against Gαq and their surfaces were redesigned to stabilize this interaction. We then used yeast surface display to affinity mature the designs. The most potent design bound Gαq/i with high affinity in vitro (KD = 18 nM) and inhibited activation of PLC-β isozymes in HEK293 cells. We anticipate that our genetically encoded inhibitor will help interrogate the role of Gαq in healthy and disease model systems. Our work demonstrates that grafting interaction motifs into folded proteins is a powerful approach for generating inhibitors of protein-protein interactions.

Sactipeptides are ribosomally-synthesized peptides that contain a characteristic thioether bridge (sactionine bond) that is installed posttranslationally and is absolutely required for their antibiotic activity. Sactipeptide biosynthesis requires a unique family of radical SAM enzymes, which contain multiple [4Fe-4S] clusters, to form the requisite thioether bridge between a cysteine and the α-carbon of an opposing amino acid through radical-based chemistry. Here we present the structure of the sactionine bond-forming enzyme CteB, from Clostridium thermocellum ATCC 27405, with both SAM and an N-terminal fragment of its peptidyl-substrate at 2.04 Å resolution. CteB has the (β/α)(6)-TIM barrel fold that is characteristic of radical SAM enzymes, as well as a C-terminal SPASM domain that contains two auxiliary [4Fe-4S] clusters. Importantly, one [4Fe-4S] cluster in the SPASM domain exhibits an open coordination site in absence of peptide substrate, which is coordinated by a peptidyl-cysteine residue in the bound state. The crystal structure of CteB also reveals an accessory N-terminal domain that has high structural similarity to a recently discovered motif present in several enzymes that act on ribosomally-synthesized and post-translationally modified peptides (RiPPs), known as a RiPP precursor peptide recognition element (RRE). This crystal structure is the first of a sactionine bond forming enzyme and sheds light on structures and mechanisms of other members of this class such as AlbA or ThnB.

We used the molecular modeling program Rosetta to identify clusters of amino acid substitutions in antibody fragments (scFvs and scAbs) that improve global protein stability and resistance to thermal deactivation. Using this methodology, we increased the melting temperature (T(m)) and resistance to heat treatment of an antibody fragment that binds to the Clostridium botulinum hemagglutinin protein (anti-HA33). Two designed antibody fragment variants with two amino acid replacement clusters, designed to stabilize local regions, were shown to have both higher T(m) compared to the parental scFv and importantly, to retain full antigen binding activity after 2 hours of incubation at 70 °C. The crystal structure of one thermostabilized scFv variants was solved at 1.6 Å and shown to be in close agreement with the RosettaAntibody model prediction.

Proteins perform an amazingly diverse set of functions in all aspects of life. Critical to the function of many proteins are the highly specific three-dimensional structures they adopt. For this reason, there is strong interest in learning how to rationally design proteins that adopt user-defined structures. Over the last 25 years, there has been significant progress in the field of computational protein design as rotamer-based sequence optimization protocols have enabled accurate design of protein tertiary and quaternary structure. In this award article, I will summarize how the molecular modeling program Rosetta is used to design new protein structures and describe how we have taken advantage of this capability to create proteins that have important applications in research and medicine. I will highlight three protein design stories: the use of protein interface design to create therapeutic bispecific antibodies, the engineering of light-inducible proteins that can be used to recruit proteins to specific locations in the cell, and the de novo design of new protein structures from pieces of naturally occurring proteins.

The prediction of protein three-dimensional structure from amino acid sequence has been a grand challenge problem in computational biophysics for decades, owing to its intrinsic scientific interest and also to the many potential applications for robust protein structure prediction algorithms, from genome interpretation to protein function prediction. More recently, the inverse problem - designing an amino acid sequence that will fold into a specified three-dimensional structure - has attracted growing attention as a potential route to the rational engineering of proteins with functions useful in biotechnology and medicine. Methods for the prediction and design of protein structures have advanced dramatically in the past decade. Increases in computing power and the rapid growth in protein sequence and structure databases have fuelled the development of new data-intensive and computationally demanding approaches for structure prediction. New algorithms for designing protein folds and protein-protein interfaces have been used to engineer novel high-order assemblies and to design from scratch fluorescent proteins with novel or enhanced properties, as well as signalling proteins with therapeutic potential. In this Review, we describe current approaches for protein structure prediction and design and highlight a selection of the successful applications they have enabled.

The Rosetta software for macromolecular modeling, docking and design is extensively used in laboratories worldwide. During two decades of development by a community of laboratories at more than 60 institutions, Rosetta has been continuously refactored and extended. Its advantages are its performance and interoperability between broad modeling capabilities. Here we review tools developed in the last 5 years, including over 80 methods. We discuss improvements to the score function, user interfaces and usability. Rosetta is available at ., This Perspective reviews tools developed over the past five years in the macromolecular modeling, docking and design software Rosetta.

Cells have evolved a variety of mechanisms to regulate the enormous complexity of processes taking place inside them. One mechanism consists in tightly controlling the localization of macromolecules, keeping them away from their place of action until needed. Since a large fraction of the cellular response to external stimuli is mediated by gene expression, it is not surprising that transcriptional regulators are often subject to stimulus-induced nuclear import or export. Here we review recent methods in chemical biology and optogenetics for controlling the nuclear localization of proteins of interest inside living cells. These methods allow researchers to regulate protein activity with exquisite spatiotemporal control, and open up new possibilities for studying the roles of proteins in a broad array of cellular processes and biological functions.

Protein ubiquitination involves E1, E2, and E3 trienzyme cascades. E2 and RING E3 enzymes often collaborate to first prime a substrate with a single ubiquitin (UB) and then achieve different forms of polyubiquitination: multiubiquitination of several sites and elongation of linkage-specific UB chains. Here, cryo-EM and biochemistry show that the human E3 anaphase-promoting complex/cyclosome (APC/C) and its two partner E2s, UBE2C (aka UBCH10) and UBE2S, adopt specialized catalytic architectures for these two distinct forms of polyubiquitination. The APC/C RING constrains UBE2C proximal to a substrate and simultaneously binds a substrate-linked UB to drive processive multiubiquitination. Alternatively, during UB chain elongation, the RING does not bind UBE2S but rather lures an evolving substrate-linked UB to UBE2S positioned through a cullin interaction to generate a Lys11-linked chain. Our findings define mechanisms of APC/C regulation, and establish principles by which specialized E3-E2-substrate-UB architectures control different forms of polyubiquitination.

Building new proteins from the old Proteins are the workhorses of biology. Designing new, stable proteins with functions desirable in biotechnology or biomedicine remains challenging. Jacobs et al. developed a computational method called SEWING that designs proteins using pieces of existing structures (see the Perspective by Netzer and Fleishman). The new proteins can contain structural features such as pockets or grooves that are required for function. The solved structures of two designed proteins agreed well with the design models. The method allows rapid design of a diverse set of structures that will facilitate functional design. Science , this issue p. 687 ; see also p. 657

Protein binding specificities can be manipulated by redesigning contacts that already exist at an interface or by expanding the interface to allow interactions with residues adjacent to the original binding site. Previously, we developed a strategy, called AnchorDesign, for expanding interfaces around linear binding epitopes. The epitope is embedded in a loop of a scaffold protein, in our case a monobody, and then surrounding residues on the monobody are optimized for binding using directed evolution or computational design. Using this strategy, we have increased binding affinities by over 100-fold, but we have not tested whether it can be used to control protein binding specificities. Here, we test whether AnchorDesign can be used to engineer a monobody that binds specifically to the Mitogen-activated protein kinase (MAPK) p38α, but not to the related MAPKs ERK2 and JNK. To anchor the binding interaction, we used a small (D) docking motif from the Mitogen-activated protein kinase kinase (MAP2K) MKK6 that interacts with similar affinity to p38α and ERK2. Our hypothesis was that by embedding the motif in a larger protein that we could expand the interface and create contacts with residues that are not conserved between p38α and ERK2. Molecular modeling was used to inform insertion of the D motif into the monobody and a combination of phage and yeast display were used to optimize the interface. Binding experiments demonstrate that the engineered monobody binds to the target surface on p38α and does not exhibit detectable binding to ERK2 or JNK.

We have developed a set of protocols in the molecular modeling program Rosetta for performing requirement-driven protein design. First, the user specifies a set of structural features that need to be present in the designed protein. These requirements can be general (e.g., "create a protein with five helices"), or they can be very specific and require the correct placement of a set of amino acids to bind a ligand. Next, a large set of protein models are generated that satisfy the design requirements. The models are built using a method that we recently introduced into Rosetta, called SEWING, that rapidly assembles novel protein backbones by combining pieces of naturally occurring proteins. In the last step of the process, rotamer-based sequence optimization and backbone refinement are performed with Rosetta, and a variety of quality metrics are used to pick sequences for experimental characterization. Here we describe the input files and user options needed to run SEWING and perform requirement-driven design and provide detailed instructions for two specific applications of the process: the design of new structural elements at a protein-protein interface and the design of ligand binding sites.

Hydrogen bond networks play a critical role in determining the stability and specificity of biomolecular complexes, and the ability to design such networks is important for engineering novel structures, interactions, and enzymes. One key feature of hydrogen bond networks that makes them difficult to rationally engineer is that they are highly cooperative and are not energetically favorable until the hydrogen bonding potential has been satisfied for all buried polar groups in the network. Existing computational methods for protein design are ill-equipped for creating these highly cooperative networks because they rely on energy functions and sampling strategies that are focused on pairwise interactions. To enable the design of complex hydrogen bond networks, we have developed a new sampling protocol in the molecular modeling program Rosetta that explicitly searches for sets of amino acid mutations that can form self-contained hydrogen bond networks. For a given set of designable residues, the protocol often identifies many alternative sets of mutations/networks, and we show that it can readily be applied to large sets of residues at protein-protein interfaces or in the interior of proteins. The protocol builds on a recently developed method in Rosetta for designing hydrogen bond networks that has been experimentally validated for small symmetric systems but was not extensible to many larger protein structures and complexes. The sampling protocol we describe here not only recapitulates previously validated designs with performance improvements but also yields viable hydrogen bond networks for cases where the previous method fails, such as the design of large, asymmetric interfaces relevant to engineering protein-based therapeutics.

β‐sheets often have one face packed against the core of the protein and the other facing solvent. Mutational studies have indicated that the solvent‐facing residues can contribute significantly to protein stability, and that the preferred amino acid at each sequence position is dependent on the precise structure of the protein backbone and the identity of the neighboring amino acids. This suggests that the most advantageous methods for designing β‐sheet surfaces will be approaches that take into account the multiple energetic factors at play including side chain rotamer preferences, van der Waals forces, electrostatics, and desolvation effects. Here, we show that the protein design software Rosetta, which models these energetic factors, can be used to dramatically increase protein stability by optimizing interactions on the surfaces of small β‐sheet proteins. Two design variants of the β‐sandwich protein from tenascin were made with 7 and 14 mutations respectively on its β‐sheet surfaces. These changes raised the thermal midpoint for unfolding from 45°C to 64°C and 74°C. Additionally, we tested an empirical approach based on increasing the number of potential salt bridges on the surfaces of the β‐sheets. This was not a robust strategy for increasing stability, as three of the four variants tested were unfolded.

Light-inducible dimers are powerful tools for cellular optogenetics, as they can be used to control the localization and activity of proteins with high spatial and temporal resolution. Despite the generality of the approach, application of light-inducible dimers is not always straightforward, as it is frequently necessary to test alternative dimer systems and fusion strategies before the desired biological activity is achieved. This process is further hindered by an incomplete understanding of the biophysical/biochemical mechanisms by which available dimers behave and how this correlates to in vivo function. To better inform the engineering process, we examined the biophysical and biochemical properties of three blue-light-inducible dimer variants (cryptochrome2 (CRY2)/CIB1, iLID/SspB, and LOVpep/ePDZb) and correlated these characteristics to in vivo colocalization and functional assays. We find that the switches vary dramatically in their dark and lit state binding affinities and that these affinities correlate with activity changes in a variety of in vivo assays, including transcription control, intracellular localization studies, and control of GTPase signaling. Additionally, for CRY2, we observe that light-induced changes in homo-oligomerization can have significant effects on activity that are sensitive to alternative fusion strategies.

We engineered a photoactivatable system for rapidly and reversibly exporting proteins from the nucleus by embedding a nuclear export signal in the LOV2 domain from phototropin 1. Fusing the chromatin modifier Bre1 to the photoswitch, we achieved light-dependent control of histone H2B monoubiquitylation in yeast, revealing fast turnover of the ubiquitin mark. Moreover, this inducible system allowed us to dynamically monitor the status of epigenetic modifications dependent on H2B ubiquitylation.

Lipoprotein lipase (LPL) is a dimeric enzyme that is responsible for clearing triglyceride-rich lipoproteins from the blood. Although LPL plays a key role in cardiovascular health, an experimentally derived three-dimensional structure has not been determined. Such a structure would aid in understanding mutations in LPL that cause familial LPL deficiency in patients and help in the development of therapeutic strategies to target LPL. A major obstacle to structural studies of LPL is that LPL is an unstable protein that is difficult to produce in the quantities needed for nuclear magnetic resonance or crystallography. We present updated LPL structural models generated by combining disulfide mapping, computational modeling, and data derived from single-molecule Förster resonance energy transfer (smFRET). We pioneer the technique of smFRET for use with LPL by developing conditions for imaging active LPL and identifying positions in LPL for the attachment of fluorophores. Using this approach, we measure LPL-LPL intermolecular interactions to generate experimental constraints that inform new computational models of the LPL dimer structure. These models suggest that LPL may dimerize using an interface that is different from the dimerization interface suggested by crystal packing contacts seen in structures of pancreatic lipase.

Cellular signal transduction is often regulated at multiple steps in order to achieve more complex logic or precise control of a pathway. For instance, some signaling mechanisms couple allosteric activation with localization to achieve high signal to noise. Here, we create a system for light activated nuclear import that incorporates two levels of control. It consists of a nuclear import photoswitch, Light Activated Nuclear Shuttle (LANS), and a protein engineered to preferentially interact with LANS in the dark, Zdk2. First, Zdk2 is tethered to a location in the cytoplasm, which sequesters LANS in the dark. Second, LANS incorporates a nuclear localization signal (NLS) that is sterically blocked from binding to the nuclear import machinery in the dark. When activated with light, LANS both dissociates from its tethered location and exposes its NLS, which leads to nuclear accumulation. We demonstrate that this coupled system improves the dynamic range of LANS in mammalian cells, yeast, and C. elegans and provides tighter control of transcription factors that have been fused to LANS.