Adaptive Evolution of Peptide Inhibitors for Mutating SARS-CoV-2.

The SARS-CoV-2 virus is currently causing a worldwide pandemic with dramatic societal consequences for the humankind. In the past decades, disease outbreaks due to such zoonotic pathogens have appeared with an accelerated rate, which calls for an urgent development of adaptive (smart) therapeutics. Here, a computational strategy is developed to adaptively evolve peptides that could selectively inhibit mutating S protein receptor binding domains (RBDs) of different SARS-CoV-2 viral strains from binding to their human host receptor, angiotensin-converting enzyme 2 (ACE2). Starting from suitable peptide templates, based on selected ACE2 segments (natural RBD binder), the templates are gradually modified by random mutations, while retaining those mutations that maximize their RBD-binding free energies. In this adaptive evolution, atomistic molecular dynamics simulations of the template-RBD complexes are iteratively perturbed by the peptide mutations, which are retained under favorable Monte Carlo decisions. The computational search will provide libraries of optimized therapeutics capable of reducing the SARS-CoV-2 infection on a global scale.

Scalable Inhibitors of the Nsp3–Nsp4 Coupling in SARS-CoV-2

The human Betacoronavirus SARS-CoV-2 is a novel pathogen claiming millions of lives and causing a global pandemic that has disrupted international healthcare systems, economies, and communities. The virus is fast mutating and presenting more infectious but less lethal versions. Currently, some small-molecule therapeutics have received FDA emergency use authorization for the treatment of COVID-19, including Lagevrio (molnupiravir) and Paxlovid (nirmaltrevir/ritonavir), which target the RNA-dependent RNA polymerase and the 3CLpro main protease, respectively. Proteins downstream in the viral replication process, specifically the nonstructural proteins (Nsps1–16), are potential drug targets due to their crucial functions. Of these Nsps, Nsp4 is a particularly promising drug target due to its involvement in the SARS-CoV viral replication and double-membrane vesicle formation (mediated via interaction with Nsp3). Given the degree of sequence conservation of these two Nsps across the Betacoronavirus clade, their protein–protein interactions and functions are likely to be conserved as well in SARS-CoV-2. Through AlphaFold2 and its recent advancements, protein structures were generated of Nsp3 and 4 lumenal loops of interest. Then, using a combination of molecular docking suites and an existing library of lead-like compounds, we virtually screened 7 million ligands to identify five putative ligand inhibitors of Nsp4, which could present an alternative pharmaceutical approach against SARS-CoV-2. These ligands exhibit promising lead-like properties (ideal molecular weight and log P profiles), maintain fixed-Nsp4-ligand complexes in molecular dynamics (MD) simulations, and tightly associate with Nsp4 via hydrophobic interactions. Additionally, alternative peptide inhibitors based on Nsp3 were designed and shown in MD simulations to provide a highly stable binding to the Nsp4 protein. Finally, these therapeutics were attached to dendrimer structures to promote their multivalent binding with Nsp4, especially its large flexible luminal loop (Nsp4LLL). The therapeutics tested in this study represent many different approaches for targeting large flexible protein structures, especially those localized to the ER. This study is the first work targeting the membrane rearrangement system of viruses and will serve as a potential avenue for treating viruses with similar replicative function.

Dendrimer-Peptide Conjugates for Effective Blockade of the Interactions between SARS-CoV-2 Spike Protein and Human ACE2 Receptor.

The coronavirus disease 2019 (COVID-19) pandemic has threatened the stability of global healthcare, which is becoming an endemic issue. Despite the development of various treatment strategies to fight COVID-19, the currently available treatment options have shown varied efficacy. Herein, we have developed an avidity-based SARS-CoV-2 antagonist using dendrimer-peptide conjugates (DPCs) for effective COVID-19 treatment. Two different peptide fragments obtained from angiotensin-converting enzyme 2 (ACE2) were integrated into a single sequence, followed by the conjugation to poly(amidoamine) (PAMAM) dendrimers. We hypothesized that the strong multivalent binding avidity endowed by dendrimers would help peptides effectively block the interaction between SARS-CoV-2 and ACE2, and this antagonist effect would be dependent upon the generation (size) of the dendrimers. To assess this, binding kinetics of the DPCs prepared from generation 4 (G4) and G7 PAMAM dendrimers to spike protein of SARS-CoV-2 were quantitatively measured using surface plasmon resonance. The larger dendrimer-based DPCs exhibited significantly enhanced binding strength by 3 orders of magnitude compared to the free peptides, whereas the smaller one showed a 12.8-fold increase only. An in vitro assay using SARS-CoV-2-mimicking microbeads also showed the improved SARS-CoV-2 blockade efficiency of the G7-peptide conjugates compared to G4. In addition, the interaction between the DPCs and SARS-CoV-2 was analyzed using molecular dynamics (MD) simulation, providing an insight into how the dendrimer-mediated multivalent binding effect can enhance the SARS-CoV-2 blockade. Our findings demonstrate that the DPCs having strong binding to SARS-CoV-2 effectively block the interaction between ACE2 and SARS-CoV-2, providing a potential as a high-affinity drug delivery system to direct anti-COVID payloads to the virus.

Broad-Spectrum Extracellular Antiviral Properties of Cucurbit[n]urils.

Viruses are microscopic pathogens capable of causing disease and are responsible for a range of human mortalities and morbidities worldwide. They can be rendered harmless or destroyed with a range of antiviral chemical compounds. Cucurbit[n]urils (CB[n]s) are a family of macrocycle chemical compounds existing as a range of homologues; due to their structure, they can bind to biological materials, acting as supramolecular "hosts" to "guests", such as amino acids. Due to the increasing need for a nontoxic antiviral compound, we investigated whether cucurbit[n]urils could act in an antiviral manner. We have found that certain cucurbit[n]uril homologues do indeed have an antiviral effect against a range of viruses, including herpes simplex virus 2 (HSV-2), respiratory syncytial virus (RSV) and SARS-CoV-2. In particular, we demonstrate that CB[7] is the active homologue of CB[n], having an antiviral effect against enveloped and nonenveloped species. High levels of efficacy were observed with 5 min contact times across different viruses. We also demonstrate that CB[7] acts with an extracellular virucidal mode of action via host-guest supramolecular interactions between viral surface proteins and the CB[n] cavity, rather than via cell internalization or a virustatic mechanism. This finding demonstrates that CB[7] acts as a supramolecular virucidal antiviral (a mechanism distinct from other current extracellular antivirals), demonstrating the potential of supramolecular interactions for future antiviral disinfectants.

Retrained Generic Antibodies Can Recognize SARS-CoV-2.

The dramatic impact novel viruses can have on humans could be more quickly mitigated if generic antibodies already present in one's system are temporarily retrained to recognize these viruses. This type of intervention can be administered during the early stages of infection, while a specific immune response is being developed. With this idea in mind, double-faced peptide-based boosters were computationally designed to allow recognition of SARS-CoV-2 by Hepatitis B antibodies. One booster face is made of ACE2-mimic peptides that can bind to the receptor binding domain (RBD) of SARS-CoV-2. The other booster face is composed of a Hepatitis B core-antigen, targeting the Hepatitis B antibody fragment. Molecular dynamics simulations revealed that the designed boosters have a highly specific and stable binding to both the RBD and the antibody fragment (AF). This approach can provide a cheap and efficient neutralization of emerging pathogens.

Sulfoglycodendrimer Therapeutics for HIV-1 and SARS-CoV-2.

Hexavalent sulfoglycodendrimers (SGDs) are synthesized as mimics of host cell heparan sulfate proteoglycans (HSPGs) to inhibit the early stages in viral binding/entry of HIV-1 and SARS-CoV-2. Using an HIV neutralization assay, the most promising of the seven candidates are found to have sub-micromolar anti-HIV activities. Molecular dynamics simulations are separately implemented to investigate how/where the SGDs interacted with both pathogens. The simulations revealed that the SGDs: 1) develop multivalent binding with polybasic regions within and outside of the V3 loop on glycoprotein 120 (gp120) for HIV-1, and consecutively bind with multiple gp120 subunits, and 2) interact with basic amino acids in both the angiotensin-converting enzyme 2 (ACE2) and HSPG binding regions of the Receptor Binding Domain (RBD) from SARS-CoV-2. These results illustrate the considerable potential of SGDs as inhibitors in viral binding/entry of both HIV-1 and SARS-CoV-2 pathogens, leading the way for further development of this class of molecules as broad-spectrum antiviral agents.

Adaptive Evolution of Peptide Inhibitors for Mutating SARS-CoV-2.

The SARS-CoV-2 virus is currently causing a worldwide pandemic with dramatic societal consequences for the humankind. In the last decades, disease outbreaks due to such zoonotic pathogens have appeared with an accelerated rate, which calls for an urgent development of
adaptive (smart) therapeutics. Here, we develop a computational strategy to adaptively evolve peptides that could selectively inhibit mutating S protein receptor binding domains (RBDs) of different SARS-CoV-2 viral strains from binding to their human host receptor, angiotensin-converting enzyme 2 (ACE2). Starting from suitable peptide templates, based on selected ACE2 segments (natural RBD binder), we gradually modify the templates by random mutations, while retaining those mutations that maximize their RBD-binding free energies. In this adaptive evolution, atomistic molecular dynamics simulations of the template-RBD complexes are iteratively perturbed by the peptide mutations, which are retained under favorable Monte Carlo decisions. The computational search will provide libraries
of optimized therapeutics capable of reducing the SARS-CoV-2 infection on a global scale.
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Oscillatory Dynamics in Infectivity and Death Rates of COVID-19.

The analysis of systematically collected data for coronavirus disease 2019 (COVID-19) infectivity and death rates has revealed, in many countries around the world, a typical oscillatory pattern with a 7-day (circaseptan) period. Additionally, in some countries, 3.5-day (hemicircaseptan) and 14-day periodicities have also been observed. Interestingly, the 7-day infectivity and death rate oscillations are almost in phase, showing local maxima on Thursdays/Fridays and local minima on Sundays/Mondays. These observations are in stark contrast to a known pattern correlating the death rate with the reduced medical staff in hospitals on the weekends. While we cannot exclude the possibility that a significant portion of the observed oscillations is associated with the reporting of the individual cases, other reasons might contribute at least partly to these data. One possible hypothesis addressing these observations is that they reflect gradually increasing stress with the progressing week, which can trigger the higher death rates on Thursdays/Fridays. Moreover, assuming the weekends provide the likely time for new infections, the maximum number of new cases might fall, again, on Thursdays/Fridays. These observations deserve further study to provide a better understanding of COVID-19 dynamics.IMPORTANCE The infectivity and death rates for COVID-19 have been observed in many countries around the world as well as in the collective data of the whole world. These oscillations show distinct circaseptan periodicity, which could be associated with numerous biological reasons as well as with improper reporting of the data collected. Since very different results are observed in different countries and even continents, such as Sweden (very significant oscillations) or India (almost no oscillations), these data provide a very important message about different conditions under which the disease is spread or is reported, which, in turn, could serve as guidance tools in future epidemics. It is necessary that follow-up studies track the observed differences and fully reliably address their origins.

Computational Design of ACE2-Based Peptide Inhibitors of SARS-CoV-2.

Peptide inhibitors against the SARS-CoV-2 coronavirus, currently causing a worldwide pandemic, are designed and simulated. The inhibitors are mostly formed by two sequential self-supporting α-helices (bundle) extracted from the protease domain (PD) of angiotensin-converting enzyme 2 (ACE2), which bind to the SARS-CoV-2 receptor binding domains. Molecular dynamics simulations revealed that the α-helical peptides maintain their secondary structure and provide a highly specific and stable binding (blocking) to SARS-CoV-2. To provide a multivalent binding to the SARS-CoV-2 receptors, many such peptides could be attached to the surfaces of nanoparticle carriers. The proposed peptide inhibitors could provide simple and efficient therapeutics against the COVID-19 disease.