A Computationally Designed Hemagglutinin Stem-Binding Protein Provides In Vivo Protection from Influenza Independent of a Host Immune Response

PB-GPT: An innovative GPT-based model for protein backbone generation

With advanced computational methods, it is now feasible to modify or design proteins for specific functions, a process with significant implications for disease treatment and other medical applications. Protein structures and functions are intrinsically linked to their backbones, making the design of these backbones a pivotal aspect of protein engineering. In this study, we focus on the task of unconditionally generating protein backbones. By means of codebook quantization and compression dictionaries, we convert protein backbone structures into a distinctive coded language and propose a GPT-based protein backbone generation model, PB-GPT. To validate the generalization performance of the model, we trained and evaluated the model on both public datasets and small protein datasets. The results demonstrate that our model has the capability to unconditionally generate elaborate, highly realistic protein backbones with structural patterns resembling those of natural proteins, thus showcasing the significant potential of large language models in protein structure design.

COVID-19 cooling: Nanostrategies targeting cytokine storm for controlling severe and critical symptoms

As severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants continue to wreak havoc worldwide, the "Cytokine Storm" (CS, also known as the inflammatory storm) or Cytokine Release Syndrome has reemerged in the public consciousness. CS is a significant contributor to the deterioration of infected individuals. Therefore, CS control is of great significance for the treatment of critically ill patients and the reduction of mortality rates. With the occurrence of variants, concerns regarding the efficacy of vaccines and antiviral drugs with a broad spectrum have grown. We should make an effort to modernize treatment strategies to address the challenges posed by mutations. Thus, in addition to the requirement for additional clinical data to monitor the long-term effects of vaccines and broad-spectrum antiviral drugs, we can use CS as an entry point and therapeutic target to alleviate the severity of the disease in patients. To effectively combat the mutation, new technologies for neutralizing or controlling CS must be developed. In recent years, nanotechnology has been widely applied in the biomedical field, opening up a plethora of opportunities for CS. Here, we put forward the view of cytokine storm as a therapeutic target can be used to treat critically ill patients by expounding the relationship between coronavirus disease 2019 (COVID-19) and CS and the mechanisms associated with CS. We pay special attention to the representative strategies of nanomaterials in current neutral and CS research, as well as their potential chemical design and principles. We hope that the nanostrategies described in this review provide attractive treatment options for severe and critical COVID-19 caused by CS.

From De Novo Design to Redesign: Harnessing Computational Protein Design for Understanding SARS-CoV-2 Molecular Mechanisms and Developing Therapeutics

The continuous emergence of novel SARS-CoV-2 variants and subvariants serves as compelling evidence that COVID-19 is an ongoing concern. The swift, well-coordinated response to the pandemic highlights how technological advancements can accelerate the detection, monitoring, and treatment of the disease. Robust surveillance systems have been established to understand the clinical characteristics of new variants, although the unpredictable nature of these variants presents significant challenges. Some variants have shown resistance to current treatments, but innovative technologies like computational protein design (CPD) offer promising solutions and versatile therapeutics against SARS-CoV-2. Advances in computing power, coupled with open-source platforms like AlphaFold and RFdiffusion (employing deep neural network and diffusion generative models), among many others, have accelerated the design of protein therapeutics with precise structures and intended functions. CPD has played a pivotal role in developing peptide inhibitors, mini proteins, protein mimics, decoy receptors, nanobodies, monoclonal antibodies, identifying drug-resistance mutations, and even redesigning native SARS-CoV-2 proteins. Pending regulatory approval, these designed therapies hold the potential for a lasting impact on human health and sustainability. As SARS-CoV-2 continues to evolve, use of such technologies enables the ongoing development of alternative strategies, thus equipping us for the "New Normal".

Computational Protein Design for COVID-19 Research and Emerging Therapeutics

As the world struggles with the ongoing COVID-19 pandemic, unprecedented obstacles have continuously been traversed as new SARS-CoV-2 variants continually emerge. Infectious disease outbreaks are unavoidable, but the knowledge gained from the successes and failures will help create a robust health management system to deal with such pandemics. Previously, scientists required years to develop diagnostics, therapeutics, or vaccines; however, we have seen that, with the rapid deployment of high-throughput technologies and unprecedented scientific collaboration worldwide, breakthrough discoveries can be accelerated and insights broadened. Computational protein design (CPD) is a game-changing new technology that has provided alternative therapeutic strategies for pandemic management. In addition to the development of peptide-based inhibitors, miniprotein binders, decoys, biosensors, nanobodies, and monoclonal antibodies, CPD has also been used to redesign native SARS-CoV-2 proteins and human ACE2 receptors. We discuss how novel CPD strategies have been exploited to develop rationally designed and robust COVID-19 treatment strategies.

Analysis of the conserved protective epitopes of hemagglutinin on influenza A viruses

The conserved protective epitopes of hemagglutinin (HA) are essential to the design of a universal influenza vaccine and new targeted therapeutic agents. Over the last 15 years, numerous broadly neutralizing antibodies (bnAbs) targeting the HA of influenza A viruses have been isolated from B lymphocytes of human donors and mouse models, and their binding epitopes identified. This work has brought new perspectives for identifying conserved protective epitopes of HA. In this review, we succinctly analyzed and summarized the antigenic epitopes and functions of more than 70 kinds of bnAb. The highly conserved protective epitopes are concentrated on five regions of HA: the hydrophobic groove, the receptor-binding site, the occluded epitope region of the HA monomers interface, the fusion peptide region, and the vestigial esterase subdomain. Our analysis clarifies the distribution of the conserved protective epitope regions on HA and provides distinct targets for the design of novel vaccines and therapeutics to combat influenza A virus infection.

Structural basis for a human broadly neutralizing influenza A hemagglutinin stem-specific antibody including H17/18 subtypes

Influenza infection continues are a persistent threat to public health. The identification and characterization of human broadly neutralizing antibodies can facilitate the development of antibody drugs and the design of universal influenza vaccines. Here, we present structural information for the human antibody PN-SIA28's heterosubtypic binding of hemagglutinin (HA) from circulating and emerging potential influenza A viruses (IAVs). Aside from group 1 and 2 conventional IAV HAs, PN-SIA28 also inhibits membrane fusion mediated by bat-origin H17 and H18 HAs. Crystallographic analyses of Fab alone or in complex with H1, H14, and H18 HA proteins reveal that PN-SIA28 binds to a highly conserved epitope in the fusion domain of different HAs, with the same CDRHs but different CDRLs for different HAs tested, distinguishing it from other structurally characterized anti-stem antibodies. The binding characteristics of PN-SIA28 provides information to support the design of increasingly potent engineered antibodies, antiviral drugs, and/or universal influenza vaccines.

Antiviral Peptides as Anti-Influenza Agents

Influenza viruses represent a leading cause of high morbidity and mortality worldwide. Approaches for fighting flu are seasonal vaccines and some antiviral drugs. The development of the seasonal flu vaccine requires a great deal of effort, as careful studies are needed to select the strains to be included in each year's vaccine. Antiviral drugs available against Influenza virus infections have certain limitations due to the increased resistance rate and negative side effects. The highly mutative nature of these viruses leads to the emergence of new antigenic variants, against which the urgent development of new approaches for antiviral therapy is needed. Among these approaches, one of the emerging new fields of "peptide-based therapies" against Influenza viruses is being explored and looks promising. This review describes the recent findings on the antiviral activity, mechanism of action and therapeutic capability of antiviral peptides that bind HA, NA, PB1, and M2 as a means of countering Influenza virus infection.

Inhibition of H1 and H5 Influenza A Virus Entry by Diverse Macrocyclic Peptides Targeting the Hemagglutinin Stem Region

Influenza A viruses pose a serious pandemic risk, while generation of efficient vaccines against seasonal variants remains challenging. There is thus a pressing need for new treatment options. We report here a set of macrocyclic peptides that inhibit influenza A virus infection at low nanomolar concentrations by binding to hemagglutinin, selected using ultrahigh-throughput screening of a diverse peptide library. The peptides are active against both H1 and H5 variants, with no detectable cytotoxicity. Despite the high sequence diversity across hits, all tested peptides were found to bind to the same region in the hemagglutinin stem by HDX-MS epitope mapping. A mutation in this region identified in an escape variant confirmed the binding site. This stands in contrast to the immunodominance of the head region for antibody binding and suggests that macrocyclic peptides from in vitro display may be well suited for finding new druggable sites not revealed by antibodies. Functional analysis indicates that these peptides stabilize the prefusion conformation of the protein and thereby prevent virus-cell fusion. High-throughput screening of macrocyclic peptides is thus shown here to be a powerful method for the discovery of novel broadly acting viral fusion inhibitors with therapeutic potential.

Protein design via deep learning

Proteins with desired functions and properties are important in fields like nanotechnology and biomedicine. De novo protein design enables the production of previously unseen proteins from the ground up and is believed as a key point for handling real social challenges. Recent introduction of deep learning into design methods exhibits a transformative influence and is expected to represent a promising and exciting future direction. In this review, we retrospect the major aspects of current advances in deep-learning-based design procedures and illustrate their novelty in comparison with conventional knowledge-based approaches through noticeable cases. We not only describe deep learning developments in structure-based protein design and direct sequence design, but also highlight recent applications of deep reinforcement learning in protein design. The future perspectives on design goals, challenges and opportunities are also comprehensively discussed.

Computationally Designed ACE2 Decoy Receptor Binds SARS-CoV-2 Spike (S) Protein with Tight Nanomolar Affinity

Even with the availability of vaccines, therapeutic options for COVID-19 still remain highly desirable, especially in hospitalized patients with moderate or severe disease. Soluble ACE2 (sACE2) is a promising therapeutic candidate that neutralizes SARS CoV-2 infection by acting as a decoy. Using computational mutagenesis, we designed a number of sACE2 derivatives carrying three to four mutations. The top-predicted sACE2 decoy based on the in silico mutagenesis scan was subjected to molecular dynamics and free-energy calculations for further validation. After illuminating the mechanism of increased binding for our designed sACE2 derivative, the design was verified experimentally by flow cytometry and BLI-binding experiments. The computationally designed sACE2 decoy (ACE2-FFWF) bound the receptor-binding domain of SARS-CoV-2 tightly with low nanomolar affinity and ninefold affinity enhancement over the wild type. Furthermore, cell surface expression was slightly greater than wild-type ACE2, suggesting that the design is well-folded and stable. Having an arsenal of high-affinity sACE2 derivatives will help to buffer against the emergence of SARS CoV-2 variants. Here, we show that computational methods have become sufficiently accurate for the design of therapeutics for current and future viral pandemics.

Small Molecule Inhibitors of Influenza Virus Entry

Hemagglutinin (HA) plays a critical role during influenza virus receptor binding and subsequent membrane fusion process, thus HA has become a promising drug target. For the past several decades, we and other researchers have discovered a series of HA inhibitors mainly targeting its fusion machinery. In this review, we summarize the advances in HA-targeted development of small molecule inhibitors. Moreover, we discuss the structural basis and mode of action of these inhibitors, and speculate upon future directions toward more potent inhibitors of membrane fusion and potential anti-influenza drugs.

Nanoscale pathogens treated with nanomaterial-like peptides: a platform technology appropriate for future pandemics

Viral infections are historically very difficult to treat. Although imperfect and time-consuming to develop, we do have some conventional vaccine and therapeutic approaches to stop viral spreading. Most importantly, all of this takes significant time while viruses continue to wreak havoc on our healthcare system. Furthermore, viral infections are accompanied by a weakened immune system which is often overlooked in antiviral drug strategies and requires additional drug development. In this review, for the first time, we touch on some promising alternative approaches to treat viral infections, specifically those focused on the use of platform nanomaterials with antiviral peptides. In doing so, this review presents a timely discussion of how we need to change our old way of treating viruses into one that can quickly meet the demands of COVID-19, as well as future pandemic-causing viruses, which will come.

Non-Toxic Virucidal Macromolecules Show High Efficacy Against Influenza Virus Ex Vivo and In Vivo

Influenza is one of the most widespread viral infections worldwide and represents a major public health problem. The risk that one of the next pandemics is caused by an influenza strain is high. It is important to develop broad-spectrum influenza antivirals to be ready for any possible vaccine shortcomings. Anti-influenza drugs are available but they are far from ideal. Arguably, an ideal antiviral should target conserved viral domains and be virucidal, that is, irreversibly inhibit viral infectivity. Here, a new class of broad-spectrum anti-influenza macromolecules is described that meets these criteria and display exceedingly low toxicity. These compounds are based on a cyclodextrin core modified on its primary face with long hydrophobic linkers terminated either in 6'sialyl-N-acetyllactosamine (6'SLN) or in 3'SLN. SLN enables nanomolar inhibition of the viruses while the hydrophobic linkers confer irreversibility to the inhibition. The combination of these two properties allows for efficacy in vitro against several human or avian influenza strains, as well as against a 2009 pandemic influenza strain ex vivo. Importantly, it is shown that, in mice, one of the compounds provides therapeutic efficacy when administered 24 h post-infection allowing 90% survival as opposed to no survival for the placebo and oseltamivir.

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.

Neutralizing Antibodies Targeting the Conserved Stem Region of Influenza Hemagglutinin

Influenza continues to be a public health threat despite the availability of annual vaccines. While vaccines are generally effective at inducing strain-specific immunity, they are sub-optimal or ineffective when drifted or novel pandemic strains arise due to sequence changes in the major surface glycoprotein hemagglutinin (HA). The discovery of a large number of antibodies targeting the highly conserved stem region of HAs that are capable of potently neutralizing a broad range of virus strains and subtypes suggests new ways to protect against influenza. The structural characterization of HA stem epitopes and broadly neutralizing antibody paratopes has enabled the design of novel proteins, mini-proteins, and peptides targeting the HA stem, thus providing a foundation for the design of new vaccines. In this narrative, we comprehensively review the current knowledge about stem-directed broadly neutralizing antibodies and the structural features contributing to virus neutralization.

Mammalian Surface Display Screening of Diverse Cystine-Dense Peptide Libraries for Difficult-to-Drug Targets

Many diseases are mediated by targets that are not amenable to conventional small-molecule drug approaches. While antibody-based drugs have undeniable utility, peptides of the 1-9 kDa size range (10-80 amino acids) have drawn interest as alternate drug scaffolds This is born of a desire to identify compounds with the advantages of antibody-based therapeutics (affinity, potency, specificity, and ability to disrupt protein:protein interactions) without all of their liabilities (large size, expensive manufacturing, and necessity of humanization). Of these alternate scaffolds, cystine-dense peptides (CDPs) have several specific benefits. Due to their stable intra-chain disulfide bridges, CDPs often demonstrate resistance to heat and proteolysis, along with low immunogenicity. These properties do not require chemical modifications, permitting CDP screening by conventional genetic means. The cystine topology of a typical CDP requires an oxidative environment, and we have found that the mammalian secretory pathway is most effective at allowing diverse CDPs to achieve a stable fold. As such, high-diversity screens to identify CDPs that interact with targets of interest can be efficiently conducted using mammalian surface display. In this protocol, we present the theory and tools to conduct a mammalian surface display screen for CDPs that bind with targets of interest, including the steps to validate binding and mature the affinity of preliminary candidates. With these methods, CDPs of all kinds can be brought to bear against targets that would benefit from a peptide-based intervention.

Improving the Efficiency of Ligand-Binding Protein Design with Molecular Dynamics Simulations

Custom-designed ligand-binding proteins represent a promising class of macromolecules with exciting applications toward the design of new enzymes or the engineering of antibodies and small-molecule recruited proteins for therapeutic interventions. However, several challenges remain in designing a protein sequence such that the binding site organization results in high affinity interaction with a bound ligand. Here, we study the dynamics of explicitly solvated designed proteins through all-atom molecular dynamics (MD) simulations to gain insight into the causes that lead to the low affinity or instability of most of these designs, despite the prediction of their success by the computational design methodology. Simulations ranging from 500 to 1000 ns per replicate were conducted on 37 designed protein variants encompassing two distinct folds and a range of ligand affinities, resulting in more than 180 μs of combined sampling. The simulations provide retrospective insights into the properties affecting ligand affinity that can prove useful in guiding further steps of design optimization. Features indicate that entropic components are particularly important for affinity, which are not easily incorporated in the empirical models often used in design protocols. Additionally, we demonstrate that the application of machine learning approaches built upon the output from the simulations can help discriminate between successful and failed binders, such that MD could act as a screening step in protein design, resulting in a more efficient process.

Antiviral peptides as promising therapeutic drugs

While scientific advances have led to large-scale production and widespread distribution of vaccines and antiviral drugs, viruses still remain a major cause of human diseases today. The ever-increasing reports of viral resistance and the emergence and re-emergence of viral epidemics pressure the health and scientific community to constantly find novel molecules with antiviral potential. This search involves numerous different approaches, and the use of antimicrobial peptides has presented itself as an interesting alternative. Even though the number of antimicrobial peptides with antiviral activity is still low, they already show immense potential to become pharmaceutically available antiviral drugs. Such peptides can originate from natural sources, such as those isolated from mammals and from animal venoms, or from artificial sources, when bioinformatics tools are used. This review aims to shed some light on antimicrobial peptides with antiviral activities against human viruses and update the data about the already well-known peptides that are still undergoing studies, emphasizing the most promising ones that may become medicines for clinical use.

A small-molecule fusion inhibitor of influenza virus is orally active in mice

Recent characterization of broadly neutralizing antibodies (bnAbs) against influenza virus identified the conserved hemagglutinin (HA) stem as a target for development of universal vaccines and therapeutics. Although several stem bnAbs are being evaluated in clinical trials, antibodies are generally unsuited for oral delivery. Guided by structural knowledge of the interactions and mechanism of anti-stem bnAb CR6261, we selected and optimized small molecules that mimic the bnAb functionality. Our lead compound neutralizes influenza A group 1 viruses by inhibiting HA-mediated fusion in vitro, protects mice against lethal and sublethal influenza challenge after oral administration, and effectively neutralizes virus infection in reconstituted three-dimensional cell culture of fully differentiated human bronchial epithelial cells. Cocrystal structures with H1 and H5 HAs reveal that the lead compound recapitulates the bnAb hotspot interactions.

Influenza Virus with Increased pH of Hemagglutinin Activation Has Improved Replication in Cell Culture but at the Cost of Infectivity in Human Airway Epithelium

The pH stability of the hemagglutinin surface protein varies between different influenza strains and subtypes and can affect the virus’ ability to replicate and transmit. Here, we demonstrate a delicate balance that the virus strikes within and without the target cell. We show that a pH-stable hemagglutinin enables a human influenza virus to replicate more effectively in human airway cells and mouse lungs by facilitating virus survival in the extracellular environment of the upper respiratory tract. Conversely, after entering target cells, being more pH stable confers a relative disadvantage, resulting in less efficient delivery of the viral genome to the host cell nucleus. Since the balance we describe will be affected differently in different host environments, it may restrict a virus’ ability to cross species. In addition, our findings imply that different influenza viruses may show variation in how well they are controlled by antiviral strategies targeting pH-dependent steps in the virus replication cycle.

Pandemic H1N1 (pH1N1) influenza virus emerged from swine in 2009 with an adequate capability to infect and transmit between people. In subsequent years, it has circulated as a seasonal virus and evolved further human-adapting mutations. Mutations in the hemagglutinin (HA) stalk that increase pH stability have been associated with human adaptation and airborne transmission of pH1N1 virus. Yet, our understanding of how pH stability impacts virus-host interactions is incomplete. Here, using recombinant viruses with point mutations that alter the pH stability of pH1N1 HA, we found distinct effects on virus phenotypes in different experimental models. Increased pH sensitivity enabled viruses to uncoat in endosomes more efficiently, manifesting as increased replication rate in typical continuous cell cultures under single-cycle conditions. A more acid-labile HA also conferred a small reduction in sensitivity to antiviral therapeutics that act at the pH-sensitive HA fusion step. Conversely, in primary human airway epithelium cultured at the air-liquid interface, increased pH sensitivity attenuated multicycle viral replication by compromising virus survival in the extracellular microenvironment. In a mouse model of influenza pathogenicity, there was an optimum HA activation pH, and viruses with either more- or less-pH-stable HA were less virulent. Opposing pressures inside and outside the host cell that determine pH stability may influence zoonotic potential. The distinct effects that changes in pH stability exert on viral phenotypes underscore the importance of using the most appropriate systems for assessing virus titer and fitness, which has implications for vaccine manufacture, antiviral drug development, and pandemic risk assessment.

IMPORTANCE The pH stability of the hemagglutinin surface protein varies between different influenza strains and subtypes and can affect the virus’ ability to replicate and transmit. Here, we demonstrate a delicate balance that the virus strikes within and without the target cell. We show that a pH-stable hemagglutinin enables a human influenza virus to replicate more effectively in human airway cells and mouse lungs by facilitating virus survival in the extracellular environment of the upper respiratory tract. Conversely, after entering target cells, being more pH stable confers a relative disadvantage, resulting in less efficient delivery of the viral genome to the host cell nucleus. Since the balance we describe will be affected differently in different host environments, it may restrict a virus’ ability to cross species. In addition, our findings imply that different influenza viruses may show variation in how well they are controlled by antiviral strategies targeting pH-dependent steps in the virus replication cycle.

Structural Insights for Anti-Influenza Vaccine Design

Influenza A virus are a persistent and significant threat to human health, and current vaccines do not provide sufficient protection due to antigenic drift, which allows influenza viruses to easily escape immune surveillance and antiviral drug activity. Influenza hemagglutinin (HA) is a glycoprotein needed for the entry of enveloped influenza viruses into host cells and is a potential target for anti-influenza humoral immune responses. In recent years, a number of broadly neutralizing antibodies (bnAbs) have been isolated, and their relative structural information obtained from the crystallization of influenza antigens in complex with bnAbs has provided some new insights into future influenza vaccine research. Here, we review the current knowledge of the HA-targeted bnAbs and the structure-based mechanisms contributing to neutralization. We also discuss the potential for this structure-based approach to overcome the challenge of obtaining a highly desired "universal" influenza vaccine, especially on small proteins and peptides.

Epitope mapping of diverse influenza Hemagglutinin drug candidates using HDX-MS

Epitope characterization is critical for elucidating the mechanism of action of drug candidates. However, traditional high-resolution epitope mapping techniques are not well suited for screening numerous drug candidates recognizing a similar target. Here, we use Hydrogen-Deuterium Exchange Mass Spectrometry (HDX-MS) to explore the conformational impact of diverse drug molecules binding on Hemagglutinin (HA), the major surface antigen of influenza viruses. We optimized a semi-automated HDX-MS workflow to systematically probe distantly related HA subtypes in complex with 4 different drug candidates, ranging from a monoclonal antibody to a small synthetic peptide. This fast, cost-effective HDX-MS epitope mapping approach accurately determined the main antigenic site in all cases. Moreover, our studies reveal distinct changes in the local conformational dynamics of HA associated to the molecular mechanism of neutralization, establishing a marker for broad anti-HA activity. Taken together, these findings highlight the potential for HDX-MS epitope mapping-based screening to identify promising candidates against HA at early stages of drug discovery.

Data-driven engineering of protein therapeutics

Protein therapeutics requires a series of properties beyond biochemical activity, including serum stability, low immunogenicity, and manufacturability. Mutations that improve one property often decrease one or more of the other essential requirements for therapeutic efficacy, making the protein engineering challenge difficult. The past decade has seen an explosion of new techniques centered around cheaply reading and writing DNA. This review highlights the recent use of such high throughput technologies for engineering protein therapeutics. Examples include the use of human antibody repertoire sequence data to pair antibody heavy and light chains, comprehensive mutational analysis for engineering antibody specificity, and the use of ancestral and inter-species sequence data to engineer simultaneous improvements in enzyme catalytic efficiency and stability. We conclude with a perspective on further ways to integrate mature protein engineering pipelines with the exponential increases in the volume of sequencing data expected in the forthcoming decade.

Accurate Calculation of Free Energy Changes upon Amino Acid Mutation

Molecular dynamics based free energy calculations allow for a robust and accurate evaluation of free energy changes upon amino acid mutation in proteins. In this chapter we cover the basic theoretical concepts important for the use of calculations utilizing the non-equilibrium alchemical switching methodology. We further provide a detailed step-by-step protocol for estimating the effect of a single amino acid mutation on protein thermostability. In addition, the potential caveats and solutions to some frequently encountered issues concerning the non-equilibrium alchemical free energy calculations are discussed. The protocol comprises details for the hybrid structure/topology generation required for alchemical transitions, equilibrium simulation setup, and description of the fast non-equilibrium switching. Subsequently, the analysis of the obtained results is described. The steps in the protocol are complemented with an illustrative practical application: a destabilizing mutation in the Trp cage mini protein. The concepts that are described are generally applicable. The shown example makes use of the pmx software package for the free energy calculations using Gromacs as a molecular dynamics engine. Finally, we discuss how the current protocol can readily be adapted to carry out charge-changing or multiple mutations at once, as well as large-scale mutational scans.

Advances in distributed computing with modern drug discovery

INTRODUCTION

Computational chemistry dramatically accelerates the drug discovery process and high-performance computing (HPC) can be used to speed up the most expensive calculations. Supporting a local HPC infrastructure is both costly and time-consuming, and, therefore, many research groups are moving from in-house solutions to remote-distributed computing platforms. Areas covered: The authors focus on the use of distributed technologies, solutions, and infrastructures to gain access to HPC capabilities, software tools, and datasets to run the complex simulations required in computational drug discovery (CDD). Expert opinion: The use of computational tools can decrease the time to market of new drugs. HPC has a crucial role in handling the complex algorithms and large volumes of data required to achieve specificity and avoid undesirable side-effects. Distributed computing environments have clear advantages over in-house solutions in terms of cost and sustainability. The use of infrastructures relying on virtualization reduces set-up costs. Distributed computing resources can be difficult to access, although web-based solutions are becoming increasingly available. There is a trade-off between cost-effectiveness and accessibility in using on-demand computing resources rather than free/academic resources. Graphics processing unit computing, with its outstanding parallel computing power, is becoming increasingly important.

Passive immunization with influenza haemagglutinin specific monoclonal antibodies

The isolation of broadly neutralising antibodies against the influenza haemagglutinin has spurred investigation into their clinical potential, and has led to advances in influenza virus biology and universal influenza vaccine development. Studies in animal models have been invaluable for demonstrating the prophylactic and therapeutic efficacy of broadly neutralising antibodies, for comparisons with antiviral drugs used as the standard of care, and for defining their mechanism of action and potential role in providing protection from airborne infection.

Computational analysis of the receptor binding specificity of novel influenza A/H7N9 viruses

BACKGROUND

Influenza viruses are undergoing continuous and rapid evolution. The fatal influenza A/H7N9 has drawn attention since the first wave of infections in March 2013, and raised more grave concerns with its increased potential to spread among humans. Experimental studies have revealed several host and virulence markers, indicating differential host binding preferences which can help estimate the potential of causing a pandemic. Here we systematically investigate the sequence pattern and structural characteristics of novel influenza A/H7N9 using computational approaches.

RESULTS

The sequence analysis highlighted mutations in protein functional domains of influenza viruses. Molecular docking and molecular dynamics simulation revealed that the hemagglutinin (HA) of A/Taiwan/1/2017(H7N9) strain enhanced the binding with both avian and human receptor analogs, compared with the previous A/Shanghai/02/2013(H7N9) strain. The Molecular Mechanics - Poisson Boltzmann Surface Area (MM-PBSA) calculation revealed the change of residue-ligand interaction energy and detected the residues with conspicuous binding preference.

CONCLUSION

The results are novel and specific to the emerging influenza A/Taiwan/1/2017(H7N9) strain compared with A/Shanghai/02/2013(H7N9). Its enhanced ability to bind human receptor analogs, which are abundant in the human upper respiratory tract, may be responsible for the recent outbreak. Residues showing binding preference were detected, which could facilitate monitoring the circulating influenza viruses.

Principles of Broad and Potent Antiviral Human Antibodies: Insights for Vaccine Design

Antibodies are the principal immune effectors that mediate protection against reinfection following viral infection or vaccination. Robust techniques for human mAb isolation have been developed in the last decade. The study of human mAbs isolated from subjects with prior immunity has become a mainstay for rational structure-based, next-generation vaccine development. The plethora of detailed molecular and genetic studies coupling the structure of antigen-antibody complexes with their antiviral function has begun to reveal common principles of critical interactions on which we can build better vaccines and therapeutic antibodies. This review outlines the approaches to isolating and studying human antiviral mAbs and discusses the common principles underlying the basis for their activity. This review also examines progress toward the goal of achieving a comprehensive understanding of the chemical and physical basis for molecular recognition of viral surface proteins in order to build predictive molecular models that can be used for vaccine design.

Tuning of in vivo cognate B-T cell interactions by Intersectin 2 is required for effective anti-viral B cell immunity

Wiskott-Aldrich syndrome (WAS) is an immune pathology associated with mutations in WAS protein (WASp) or in WASp interacting protein (WIP). Together with the small GTPase Cdc42 and other effectors, these proteins participate in the remodelling of the actin network downstream of BCR engagement. Here we show that mice lacking the adaptor protein ITSN2, a G-nucleotide exchange factor (GEF) for Cdc42 that also interacts with WASp and WIP, exhibited increased mortality during primary infection, incomplete protection after Flu vaccination, reduced germinal centre formation and impaired antibody responses to vaccination. These defects were found, at least in part, to be intrinsic to the B cell compartment. In vivo, ITSN2 deficient B cells show a reduction in the expression of SLAM, CD84 or ICOSL that correlates with a diminished ability to form long term conjugates with T cells, to proliferate in vivo, and to differentiate into germinal centre cells. In conclusion, our study not only revealed a key role for ITSN2 as an important regulator of adaptive immune-response during vaccination and viral infection but it is also likely to contribute to a better understanding of human immune pathologies.

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.

Potent peptidic fusion inhibitors of influenza virus

Influenza therapeutics with new targets and mechanisms of action are urgently needed to combat potential pandemics, emerging viruses, and constantly mutating strains in circulation. We report here on the design and structural characterization of potent peptidic inhibitors of influenza hemagglutinin. The peptide design was based on complementarity-determining region loops of human broadly neutralizing antibodies against the hemagglutinin (FI6v3 and CR9114). The optimized peptides exhibit nanomolar affinity and neutralization against influenza A group 1 viruses, including the 2009 H1N1 pandemic and avian H5N1 strains. The peptide inhibitors bind to the highly conserved stem epitope and block the low pH-induced conformational rearrangements associated with membrane fusion. These peptidic compounds and their advantageous biological properties should accelerate the development of new small molecule- and peptide-based therapeutics against influenza virus.

Deep sequencing methods for protein engineering and design

The advent of next-generation sequencing (NGS) has revolutionized protein science, and the development of complementary methods enabling NGS-driven protein engineering have followed. In general, these experiments address the functional consequences of thousands of protein variants in a massively parallel manner using genotype-phenotype linked high-throughput functional screens followed by DNA counting via deep sequencing. We highlight the use of information rich datasets to engineer protein molecular recognition. Examples include the creation of multiple dual-affinity Fabs targeting structurally dissimilar epitopes and engineering of a broad germline-targeted anti-HIV-1 immunogen. Additionally, we highlight the generation of enzyme fitness landscapes for conducting fundamental studies of protein behavior and evolution. We conclude with discussion of technological advances.

In vitro evolution of an influenza broadly neutralizing antibody is modulated by hemagglutinin receptor specificity

The relatively recent discovery and characterization of human broadly neutralizing antibodies (bnAbs) against influenza virus provide valuable insights into antiviral and vaccine development. However, the factors that influence the evolution of high-affinity bnAbs remain elusive. We therefore explore the functional sequence space of bnAb C05, which targets the receptor-binding site (RBS) of influenza haemagglutinin (HA) via a long CDR H3. We combine saturation mutagenesis with yeast display to enrich for C05 variants of CDR H3 that bind to H1 and H3 HAs. The C05 variants evolve up to 20-fold higher affinity but increase specificity to each HA subtype used in the selection. Structural analysis reveals that the fine specificity is strongly influenced by a highly conserved substitution that regulates receptor binding in different subtypes. Overall, this study suggests that subtle natural variations in the HA RBS between subtypes and species may differentially influence the evolution of high-affinity bnAbs.

Broadly neutralizing antibodies (bnAbs) against influenza hemagglutinin (HA) have yielded insights for antiviral development. Here, the authors employ saturated mutagenesis of the paratope region of a bnAb combined with yeast display screening using H1 and H3 HAs, and find that a tradeoff exists between Ab affinity and breadth that influenced by disparate modes of receptor binding.

Anti-Influenza Treatment: Drugs Currently Used and Under Development

La gripe es una enfermedad contagiosa altamente prevalente y con significativa morbimortalidad. El tratamiento disponible con fármacos antivirales, de ser administrado de forma precoz, puede reducir el riesgo de complicaciones severas; sin embargo, muchos tipos de virus desarrollan resistencia a estos fármacos, reduciendo notablemente su efectividad. Ha habido un gran interés en el desarrollo de nuevas opciones terapéuticas para combatir la enfermedad. Una gran variedad de fármacos han demostrado tener actividad antiinfluenza, pero aún no están disponibles para su uso en la clínica. Muchos de ellos tienen como objetivo componentes del virus, mientras que otros son dirigidos a elementos de la célula huésped que participan en el ciclo viral. Modular los componentes del huésped es una estrategia que minimiza el desarrollo de cepas resistentes, dado que estos no están sujetos a la variabilidad genética que tiene el virus. Por otro lado, la principal desventaja es que existe un mayor riesgo de efectos secundarios asociados al tratamiento. El objetivo de la presente revisión es describir los principales agentes farmacológicos disponibles en la actualidad, así como los nuevos fármacos en estudio con potencial beneficio en el tratamiento de la gripe.

Structure and Function Analysis of an Antibody Recognizing All Influenza A Subtypes

Influenza virus remains a threat because of its ability to evade vaccine-induced immune responses due to antigenic drift. Here, we describe the isolation, evolution, and structure of a broad-spectrum human monoclonal antibody (mAb), MEDI8852, effectively reacting with all influenza A hemagglutinin (HA) subtypes. MEDI8852 uses the heavy-chain VH6-1 gene and has higher potency and breadth when compared to other anti-stem antibodies. MEDI8852 is effective in mice and ferrets with a therapeutic window superior to that of oseltamivir. Crystallographic analysis of Fab alone or in complex with H5 or H7 HA proteins reveals that MEDI8852 binds through a coordinated movement of CDRs to a highly conserved epitope encompassing a hydrophobic groove in the fusion domain and a large portion of the fusion peptide, distinguishing it from other structurally characterized cross-reactive antibodies. The unprecedented breadth and potency of neutralization by MEDI8852 support its development as immunotherapy for influenza virus-infected humans.