De Novo Human Angiotensin-Converting Enzyme 2 Decoy NL-CVX1 Protects Mice From Severe Disease After Severe Acute Respiratory Syndrome Coronavirus 2 Infection.

The emergence of novel variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) underscores the need to investigate alternative approaches to prevent infection and treat patients with coronavirus disease 2019. Here, we report the preclinical efficacy of NL-CVX1, a de novo decoy that blocks virus entry into cells by binding with nanomolar affinity and high specificity to the receptor-binding domain of the SARS-CoV-2 spike protein. Using a transgenic mouse model of SARS-CoV-2 infection, we showed that a single prophylactic intranasal dose of NL-CVX1 conferred complete protection from severe disease following SARS-CoV-2 infection. Multiple therapeutic administrations of NL-CVX1 also protected mice from succumbing to infection. Finally, we showed that infected mice treated with NL-CVX1 developed both anti-SARS-CoV-2 antibodies and memory T cells and were protected against reinfection a month after treatment. Overall, these observations suggest NL-CVX1 is a promising therapeutic candidate for preventing and treating severe SARS-CoV-2 infections.

Thermodynamic and kinetic analysis of the LAO binding protein and its isolated domains reveal non-additivity in stability, folding and function.

Substrate-binding proteins (SBPs) are used by organisms from the three domains of life for transport and signalling. SBPs are composed of two domains that collectively trap ligands with high affinity and selectivity. To explore the role of the domains and the integrity of the hinge region between them in the function and conformation of SBPs, here, we describe the ligand binding, conformational stability and folding kinetics of the Lysine Arginine Ornithine (LAO) binding protein from Salmonella thiphimurium and constructs corresponding to its two independent domains. LAO is a class II SBP formed by a continuous and a discontinuous domain. Contrary to the expected behaviour based on their connectivity, the discontinuous domain shows a stable native-like structure that binds l-arginine with moderate affinity, whereas the continuous domain is barely stable and shows no detectable ligand binding. Regarding folding kinetics, studies of the entire protein revealed the presence of at least two intermediates. While the unfolding and refolding of the continuous domain exhibited only a single intermediate and simpler and faster kinetics than LAO, the folding mechanism of the discontinuous domain was complex and involved multiple intermediates. These findings suggest that in the complete protein the continuous domain nucleates folding and that its presence funnels the folding of the discontinuous domain avoiding nonproductive interactions. The strong dependence of the function, stability and folding pathway of the lobes on their covalent association is most likely the result of the coevolution of both domains as a single unit.

Design of cell-type-specific hyperstable IL-4 mimetics via modular de novo scaffolds.

The interleukin-4 (IL-4) cytokine plays a critical role in modulating immune homeostasis. Although there is great interest in harnessing this cytokine as a therapeutic in natural or engineered formats, the clinical potential of native IL-4 is limited by its instability and pleiotropic actions. Here, we design IL-4 cytokine mimetics (denoted Neo-4) based on a de novo engineered IL-2 mimetic scaffold and demonstrate that these cytokines can recapitulate physiological functions of IL-4 in cellular and animal models. In contrast with natural IL-4, Neo-4 is hyperstable and signals exclusively through the type I IL-4 receptor complex, providing previously inaccessible insights into differential IL-4 signaling through type I versus type II receptors. Because of their hyperstability, our computationally designed mimetics can directly incorporate into sophisticated biomaterials that require heat processing, such as three-dimensional-printed scaffolds. Neo-4 should be broadly useful for interrogating IL-4 biology, and the design workflow will inform targeted cytokine therapeutic development.

De novo design of modular peptide-binding proteins by superhelical matching.

General approaches for designing sequence-specific peptide-binding proteins would have wide utility in proteomics and synthetic biology. However, designing peptide-binding proteins is challenging, as most peptides do not have defined structures in isolation, and hydrogen bonds must be made to the buried polar groups in the peptide backbone1-3. Here, inspired by natural and re-engineered protein-peptide systems4-11, we set out to design proteins made out of repeating units that bind peptides with repeating sequences, with a one-to-one correspondence between the repeat units of the protein and those of the peptide. We use geometric hashing to identify protein backbones and peptide-docking arrangements that are compatible with bidentate hydrogen bonds between the side chains of the protein and the peptide backbone12. The remainder of the protein sequence is then optimized for folding and peptide binding. We design repeat proteins to bind to six different tripeptide-repeat sequences in polyproline II conformations. The proteins are hyperstable and bind to four to six tandem repeats of their tripeptide targets with nanomolar to picomolar affinities in vitro and in living cells. Crystal structures reveal repeating interactions between protein and peptide interactions as designed, including ladders of hydrogen bonds from protein side chains to peptide backbones. By redesigning the binding interfaces of individual repeat units, specificity can be achieved for non-repeating peptide sequences and for disordered regions of native proteins.

A split, conditionally active mimetic of IL-2 reduces the toxicity of systemic cytokine therapy.

The therapeutic potential of recombinant cytokines has been limited by the severe side effects of systemic administration. We describe a strategy to reduce the dose-limiting toxicities of monomeric cytokines by designing two components that require colocalization for activity and that can be independently targeted to restrict activity to cells expressing two surface markers. We demonstrate the approach with a previously designed mimetic of cytokines interleukin-2 and interleukin-15-Neoleukin-2/15 (Neo-2/15)-both for trans-activating immune cells surrounding targeted tumor cells and for cis-activating directly targeted immune cells. In trans-activation mode, tumor antigen targeting of the two components enhanced antitumor activity and attenuated toxicity compared with systemic treatment in syngeneic mouse melanoma models. In cis-activation mode, immune cell targeting of the two components selectively expanded CD8+ T cells in a syngeneic mouse melanoma model and promoted chimeric antigen receptor T cell activation in a lymphoma xenograft model, enhancing antitumor efficacy in both cases.

An IL-2 Protein Therapeutic for Cancer that Gains Function on the Spot.

Recombinant human IL-2 (rhIL-2) is now rarely used to treat patients with cancer because it too often causes severe toxicities. In this issue, Nirschl and colleagues report the development and preclinical characterization of an engineered IL-2 prodrug called WTX-124 that activates in the tumor microenvironment and has minimal systemic toxicity. It will be intriguing to watch the translation of this approach to the clinic. See related article by Nirschl et al., p. 581 (5).

Super-enhancer-based identification of a BATF3/IL-2R-module reveals vulnerabilities in anaplastic large cell lymphoma.

Anaplastic large cell lymphoma (ALCL), an aggressive CD30-positive T-cell lymphoma, comprises systemic anaplastic lymphoma kinase (ALK)-positive, and ALK-negative, primary cutaneous and breast implant-associated ALCL. Prognosis of some ALCL subgroups is still unsatisfactory, and already in second line effective treatment options are lacking. To identify genes defining ALCL cell state and dependencies, we here characterize super-enhancer regions by genome-wide H3K27ac ChIP-seq. In addition to known ALCL key regulators, the AP-1-member BATF3 and IL-2 receptor (IL2R)-components are among the top hits. Specific and high-level IL2R expression in ALCL correlates with BATF3 expression. Confirming a regulatory link, IL-2R-expression decreases following BATF3 knockout, and BATF3 is recruited to IL2R regulatory regions. Functionally, IL-2, IL-15 and Neo-2/15, a hyper-stable IL-2/IL-15 mimic, accelerate ALCL growth and activate STAT1, STAT5 and ERK1/2. In line, strong IL-2Rα-expression in ALCL patients is linked to more aggressive clinical presentation. Finally, an IL-2Rα-targeting antibody-drug conjugate efficiently kills ALCL cells in vitro and in vivo. Our results highlight the importance of the BATF3/IL-2R-module for ALCL biology and identify IL-2Rα-targeting as a promising treatment strategy for ALCL.

De novo design of potent and resilient hACE2 decoys to neutralize SARS-CoV-2.

We developed a de novo protein design strategy to swiftly engineer decoys for neutralizing pathogens that exploit extracellular host proteins to infect the cell. Our pipeline allowed the design, validation, and optimization of de novo human angiotensin-converting enzyme 2 (hACE2) decoys to neutralize severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The best monovalent decoy, CTC-445.2, bound with low nanomolar affinity and high specificity to the receptor-binding domain (RBD) of the spike protein. Cryo-electron microscopy (cryo-EM) showed that the design is accurate and can simultaneously bind to all three RBDs of a single spike protein. Because the decoy replicates the spike protein target interface in hACE2, it is intrinsically resilient to viral mutational escape. A bivalent decoy, CTC-445.2d, showed ~10-fold improvement in binding. CTC-445.2d potently neutralized SARS-CoV-2 infection of cells in vitro, and a single intranasal prophylactic dose of decoy protected Syrian hamsters from a subsequent lethal SARS-CoV-2 challenge.

De novo design of ACE2 protein decoys to neutralize SARS-CoV-2.

There is an urgent need for the ability to rapidly develop effective countermeasures for emerging biological threats, such as the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes the ongoing coronavirus disease 2019 (COVID-19) pandemic. We have developed a generalized computational design strategy to rapidly engineer de novo proteins that precisely recapitulate the protein surface targeted by biological agents, like viruses, to gain entry into cells. The designed proteins act as decoys that block cellular entry and aim to be resilient to viral mutational escape. Using our novel platform, in less than ten weeks, we engineered, validated, and optimized de novo protein decoys of human angiotensin-converting enzyme 2 (hACE2), the membrane-associated protein that SARS-CoV-2 exploits to infect cells. Our optimized designs are hyperstable de novo proteins (∼18-37 kDa), have high affinity for the SARS-CoV-2 receptor binding domain (RBD) and can potently inhibit the virus infection and replication in vitro. Future refinements to our strategy can enable the rapid development of other therapeutic de novo protein decoys, not limited to neutralizing viruses, but to combat any agent that explicitly interacts with cell surface proteins to cause disease.

The advent of de novo proteins for cancer immunotherapy.

Engineered proteins are revolutionizing immunotherapy, but advances are still needed to harness their full potential. Traditional protein engineering methods use naturally existing proteins as a starting point, and therefore, are intrinsically limited to small alterations of a protein's natural structure and function. Conversely, computational de novo protein design is free of such limitation, and can produce a virtually infinite number of novel protein sequences, folds, and functions. Recently, we used de novo protein engineering to create Neoleukin-2/15 (Neo-2/15), a protein mimetic of the function of both interleukin-2 (IL-2) and interleukin-15 (IL-15). To our knowledge, Neo-2/15 is the first de novo protein with immunotherapeutic activity, and in murine cancer models, it has demonstrated enhanced therapeutic potency and reduced toxicity compared to IL-2. De novo protein design is already showcasing its tremendous potential for driving the next wave of protein-based therapeutics that are explicitly engineered to treat disease.

De novo protein design by citizen scientists.

Online citizen science projects such as GalaxyZoo1, Eyewire2 and Phylo3 have proven very successful for data collection, annotation and processing, but for the most part have harnessed human pattern-recognition skills rather than human creativity. An exception is the game EteRNA4, in which game players learn to build new RNA structures by exploring the discrete two-dimensional space of Watson-Crick base pairing possibilities. Building new proteins, however, is a more challenging task to present in a game, as both the representation and evaluation of a protein structure are intrinsically three-dimensional. We posed the challenge of de novo protein design in the online protein-folding game Foldit5. Players were presented with a fully extended peptide chain and challenged to craft a folded protein structure and an amino acid sequence encoding that structure. After many iterations of player design, analysis of the top-scoring solutions and subsequent game improvement, Foldit players can now-starting from an extended polypeptide chain-generate a diversity of protein structures and sequences that encode them in silico. One hundred forty-six Foldit player designs with sequences unrelated to naturally occurring proteins were encoded in synthetic genes; 56 were found to be expressed and soluble in Escherichia coli, and to adopt stable monomeric folded structures in solution. The diversity of these structures is unprecedented in de novo protein design, representing 20 different folds-including a new fold not observed in natural proteins. High-resolution structures were determined for four of the designs, and are nearly identical to the player models. This work makes explicit the considerable implicit knowledge that contributes to success in de novo protein design, and shows that citizen scientists can discover creative new solutions to outstanding scientific challenges such as the protein design problem.

De novo design of potent and selective mimics of IL-2 and IL-15.

We describe a de novo computational approach for designing proteins that recapitulate the binding sites of natural cytokines, but are otherwise unrelated in topology or amino acid sequence. We use this strategy to design mimics of the central immune cytokine interleukin-2 (IL-2) that bind to the IL-2 receptor ßγc heterodimer (IL-2Rßγc) but have no binding site for IL-2Rα (also called CD25) or IL-15Rα (also known as CD215). The designs are hyper-stable, bind human and mouse IL-2Rßγc with higher affinity than the natural cytokines, and elicit downstream cell signalling independently of IL-2Rα and IL-15Rα. Crystal structures of the optimized design neoleukin-2/15 (Neo-2/15), both alone and in complex with IL-2Rßγc, are very similar to the designed model. Neo-2/15 has superior therapeutic activity to IL-2 in mouse models of melanoma and colon cancer, with reduced toxicity and undetectable immunogenicity. Our strategy for building hyper-stable de novo mimetics could be applied generally to signalling proteins, enabling the creation of superior therapeutic candidates.

Structures and disulfide cross-linking of de novo designed therapeutic mini-proteins.

Recent advances in computational protein design now enable the massively parallel de novo design and experimental characterization of small hyperstable binding proteins with potential therapeutic activity. By providing experimental feedback on tens of thousands of designed proteins, the design-build-test-learn pipeline provides a unique opportunity to systematically improve our understanding of protein folding and binding. Here, we review the structures of mini-protein binders in complex with Influenza hemagglutinin and Bot toxin, and illustrate in the case of disulfide bond placement how analysis of the large datasets of computational models and experimental data can be used to identify determinants of folding and binding.

Comprehensive computational design of ordered peptide macrocycles.

Mixed-chirality peptide macrocycles such as cyclosporine are among the most potent therapeutics identified to date, but there is currently no way to systematically search the structural space spanned by such compounds. Natural proteins do not provide a useful guide: Peptide macrocycles lack regular secondary structures and hydrophobic cores, and can contain local structures not accessible with l-amino acids. Here, we enumerate the stable structures that can be adopted by macrocyclic peptides composed of l- and d-amino acids by near-exhaustive backbone sampling followed by sequence design and energy landscape calculations. We identify more than 200 designs predicted to fold into single stable structures, many times more than the number of currently available unbound peptide macrocycle structures. Nuclear magnetic resonance structures of 9 of 12 designed 7- to 10-residue macrocycles, and three 11- to 14-residue bicyclic designs, are close to the computational models. Our results provide a nearly complete coverage of the rich space of structures possible for short peptide macrocycles and vastly increase the available starting scaffolds for both rational drug design and library selection methods.

Medical Professionalism: the Effects of Sociodemographic Diversity and Curricular Organization on the Attitudinal Performance of Medical Students / Profissionalismo Médico: Efeito da Diversidade Sociodemográfica e da Organização Curricular no Desempenho Atitudinal dos Estudantes de Medicina

ABSTRACT Introduction: Socioeconomic and demographic diversity in the educational environment and the development of professional attitudes enhance the quality of health care delivery. Despite the importance of diversity for equity and accessibility to health care, its repercussions for students' attitudinal learning have not been adequately evaluated. Purpose: Evaluate the influence of academic sociodemographic diversity and curricular organization in the development of professional attitudes in different phases of the undergraduate medical curriculum. Method: In 2012, the attitudinal performance of 310 socioeconomically diverse medical students was evaluated by the administration of a five-point professional attitudes scale. The participants were at different points in their education at a Brazilian public school of medicine in Brasília, Federal District. The scale comprised 6 factors: communication, ethics, professional excellence, self-assessment, beliefs, social determinants; and a general factor called medical professionalism and was validated for the purpose of this research. The reliability coefficients (aCronbach) ranged from 0.65 to 0.87, according to different scale dimensions. Student diversity was analyzed according to differences in gender, age, religious affiliation, system of student selection and socioeconomic background. Results: The authors observed a decline in the mean attitude scores during the clinical phase compared to the preclinical phase of the curriculum. Female students displayed more positive attitudes than male students, and the students who declared a religious affiliation recorded higher attitude scores compared to those who declared themselves atheist, agnostic or non-religious. There was no correlation between family income or the system of student selection and the students' attitude scores. The students who had attended public schools expressed a greater interest in working in the public health system compared to the other students. Age and marital status had no relevant effect on attitude scores. Conclusions: The attitude scores of medical students declined as the curriculum progressed. Female students had more positive attitudes than male students. Religious affiliation appeared to positively influence the observed attitude scores.

RESUMO Introdução: A diversidade socioeconômica e demográfica no ambiente educacional e o desenvolvimento de attitudes profissionais estão associados ao aumento na qualidade da assistência em saúde. Apesar da importância dessa diversidade para a equidade e acessibilidade ao sistema de saúde, sua repercussão no aprendizado atitudinal dos estudantes em nosso meio ainda é muito pouco estudada e avaliada. Objetivo: Avaliar a influência das diferenças demográficas, sociais e económicas e da organização curricular no desempenho atitudinal de estudantes de graduação em Medicina em diferentes fases do curso. Método: Em 2012, o desempenho atitudinal de 310 estudantes de Medicina foi avaliado mediante a aplicação de uma escala de atitudes profissionais de cinco pontos. Os participantes eram de diferentes séries do curso de graduação em Medicina de uma escola pública de Medicina de Brasília (DF). A escala de atitudes utilizada era composta por seis fatores — Comunicação; Ética; Excelência Profissional; Autoavaliação; Crenças; Determinantes Sociais; e um fator geral chamado Profissionalismo Médico — e foi validada para as finalidades desta pesquisa. O coeficiente de fidedignidade (a de Cronbach) para as diferentes dimensões da escala variou de 0,65 a 0,87. A diversidade dos estudantes foi avaliada de acordo com gênero, idade, religião, sistema de ingresso no curso (cotistas sociais/não cotistas) e condições socioeconómicas. Resultados: Os autores observaram um declínio nos escores médios de atitude em várias dimensões da escala durante a fase clínica, comparada à fase pré-clínica do currículo. Estudantes do gênero feminino obtiveram escores de atitudes mais positivos do que os do gênero masculino. Estudantes que declararam ter uma religião tiveram melhores escores do que os que se declararam ateus, agnósticos ou sem religião. Não houve correlação entre idade, estado civil e renda familiar e o desempenho atitudinal medido pela escala. Estudantes que ingressaram no curso pelo sistema de cotas expressaram maior interesse em trabalhar no sistema público de saúde. Conclusões: Houve um declínio do escore de atitude dos estudantes de Medicina com a progressão do curso. Estudantes do gênero feminino apresentaram escores de atitudes mais positivos que os do gênero masculino. Filiação religiosa parece influenciar positivamente o desempenho atitudinal dos estudantes.

De novo design of covalently constrained mesosize protein scaffolds with unique tertiary structures.

The folding of natural proteins typically relies on hydrophobic packing, metal binding, or disulfide bond formation in the protein core. Alternatively, a 3D structure can be defined by incorporating a multivalent cross-linking agent, and this approach has been successfully developed for the selection of bicyclic peptides from large random-sequence libraries. By contrast, there is no general method for the de novo computational design of multicross-linked proteins with predictable and well-defined folds, including ones not found in nature. Here we use Rosetta and Tertiary Motifs (TERMs) to design small proteins that fold around multivalent cross-linkers. The hydrophobic cross-linkers stabilize the fold by macrocyclic restraints, and they also form an integral part of a small apolar core. The designed CovCore proteins were prepared by chemical synthesis, and their structures were determined by solution NMR or X-ray crystallography. These mesosized proteins, lying between conventional proteins and small peptides, are easily accessible either through biosynthetic precursors or chemical synthesis. The unique tertiary structures and ease of synthesis of CovCore proteins indicate that they should provide versatile templates for developing inhibitors of protein-protein interactions.

Massively parallel de novo protein design for targeted therapeutics.

De novo protein design holds promise for creating small stable proteins with shapes customized to bind therapeutic targets. We describe a massively parallel approach for designing, manufacturing and screening mini-protein binders, integrating large-scale computational design, oligonucleotide synthesis, yeast display screening and next-generation sequencing. We designed and tested 22,660 mini-proteins of 37-43 residues that target influenza haemagglutinin and botulinum neurotoxin B, along with 6,286 control sequences to probe contributions to folding and binding, and identified 2,618 high-affinity binders. Comparison of the binding and non-binding design sets, which are two orders of magnitude larger than any previously investigated, enabled the evaluation and improvement of the computational model. Biophysical characterization of a subset of the binder designs showed that they are extremely stable and, unlike antibodies, do not lose activity after exposure to high temperatures. The designs elicit little or no immune response and provide potent prophylactic and therapeutic protection against influenza, even after extensive repeated dosing.

Principles for designing proteins with cavities formed by curved ß sheets.

Active sites and ligand-binding cavities in native proteins are often formed by curved ß sheets, and the ability to control ß-sheet curvature would allow design of binding proteins with cavities customized to specific ligands. Toward this end, we investigated the mechanisms controlling ß-sheet curvature by studying the geometry of ß sheets in naturally occurring protein structures and folding simulations. The principles emerging from this analysis were used to design, de novo, a series of proteins with curved ß sheets topped with α helices. Nuclear magnetic resonance and crystal structures of the designs closely match the computational models, showing that ß-sheet curvature can be controlled with atomic-level accuracy. Our approach enables the design of proteins with cavities and provides a route to custom design ligand-binding and catalytic sites.

Computationally designed high specificity inhibitors delineate the roles of BCL2 family proteins in cancer.

Many cancers overexpress one or more of the six human pro-survival BCL2 family proteins to evade apoptosis. To determine which BCL2 protein or proteins block apoptosis in different cancers, we computationally designed three-helix bundle protein inhibitors specific for each BCL2 pro-survival protein. Following in vitro optimization, each inhibitor binds its target with high picomolar to low nanomolar affinity and at least 300-fold specificity. Expression of the designed inhibitors in human cancer cell lines revealed unique dependencies on BCL2 proteins for survival which could not be inferred from other BCL2 profiling methods. Our results show that designed inhibitors can be generated for each member of a closely-knit protein family to probe the importance of specific protein-protein interactions in complex biological processes.

Motif-Driven Design of Protein-Protein Interfaces.

Protein-protein interfaces regulate many critical processes for cellular function. The ability to accurately control and regulate these molecular interactions is of major interest for biomedical and synthetic biology applications, as well as to address fundamental biological questions. In recent years, computational protein design has emerged as a tool for designing novel protein-protein interactions with functional relevance. Although attractive, these computational tools carry a steep learning curve. In order to make some of these methods more accessible, we present detailed descriptions and examples of ROSETTA computational protocols for the design of functional protein binders using seeded protein interface design. In these protocols, a motif of known structure that interacts with the target site is grafted into a scaffold protein, followed by design of the surrounding interaction surface.