Orally administered bismuth drug together with N-acetyl cysteine as a broad-spectrum anti-coronavirus cocktail therapy

The emergence of SARS-CoV-2 variants of concern compromises vaccine efficacy and emphasizes the need for further development of anti-SARS-CoV-2 therapeutics, in particular orally administered take-home therapies. Cocktail therapy has shown great promise in the treatment of viral infection. Herein, we reported the potent preclinical anti-SARS-CoV-2 efficacy of a cocktail therapy consisting of clinically used drugs, e.g. colloidal bismuth subcitrate (CBS) or bismuth subsalicylate (BSS), and N-acetyl-l-cysteine (NAC). Oral administration of the cocktail reduced viral loads in the lung and ameliorated virus-induced pneumonia in a hamster infection model. The mechanistic studies showed that NAC prevented the hydrolysis of bismuth drugs at gastric pH via the formation of the stable component [Bi(NAC)₃], and optimized the pharmacokinetics profile of CBS in vivo. Combination of bismuth drugs with NAC suppressed the replication of a panel of medically important coronaviruses including Middle East respiratory syndrome-related coronavirus (MERS-CoV), Human coronavirus 229E (HCoV-229E) and SARS-CoV-2 Alpha variant (B.1.1.7) with broad-spectrum inhibitory activities towards key viral cysteine enzymes/proteases including papain-like protease (PL^pro), main protease (M^pro), helicase (Hel) and angiotensin-converting enzyme 2 (ACE2). Importantly, our study offered a potential at-home treatment for combating SARS-CoV-2 and future coronavirus infections.

A cocktail therapy comprising bismuth drugs and N-acetyl-l-cysteine is reported to suppress the replication of SARS-CoV-2 via the oral route. The broad-spectrum inhibitory activities of the combination upon key viral cysteine enzymes are verified.     

Selective covalent targeting of SARS-CoV-2 main protease by enantiopure chlorofluoroacetamide

The coronavirus disease 2019 (COVID-19) pandemic has necessitated the development of antiviral agents against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The main protease (M^pro) is a promising target for COVID-19 treatment. Here, we report an irreversible SARS-CoV-2 M^pro inhibitor possessing chlorofluoroacetamide (CFA) as a warhead for the covalent modification of M^pro. Ugi multicomponent reaction using chlorofluoroacetic acid enabled the rapid synthesis of dipeptidic CFA derivatives that identified 18 as a potent inhibitor of SARS-CoV-2 M^pro. Among the four stereoisomers, (R,R)-18 exhibited a markedly higher inhibitory activity against M^pro than the other isomers. Reaction kinetics and computational docking studies suggest that the R configuration of the CFA warhead is crucial for the rapid covalent inhibition of M^pro. Our findings highlight the prominent influence of the CFA chirality on the covalent modification of proteinous cysteines and provide the basis for improving the potency and selectivity of CFA-based covalent inhibitors.

Chlorofluoroacetamide (CFA) was used as the warhead for covalent targeting of SARS-CoV-2 M^pro. The chirality at CFA showed marked influence on inhibitory activity, suggesting stereospecific activation of CFA for cysteine modification in the protein.     

Synergistic inhibition of SARS-CoV-2 cell entry by otamixaban and covalent protease inhibitors: pre-clinical assessment of pharmacological and molecular properties

SARS-CoV-2, the cause of the COVID-19 pandemic, exploits host cell proteins for viral entry into human lung cells. One of them, the protease TMPRSS2, is required to activate the viral spike protein (S). Even though two inhibitors, camostat and nafamostat, are known to inhibit TMPRSS2 and block cell entry of SARS-CoV-2, finding further potent therapeutic options is still an important task. In this study, we report that a late-stage drug candidate, otamixaban, inhibits SARS-CoV-2 cell entry. We show that otamixaban suppresses TMPRSS2 activity and SARS-CoV-2 infection of a human lung cell line, although with lower potency than camostat or nafamostat. In contrast, otamixaban inhibits SARS-CoV-2 infection of precision cut lung slices with the same potency as camostat. Furthermore, we report that otamixaban''s potency can be significantly enhanced by (sub-) nanomolar nafamostat or camostat supplementation. Dominant molecular TMPRSS2-otamixaban interactions are assessed by extensive 109 μs of atomistic molecular dynamics simulations. Our findings suggest that combinations of otamixaban with supplemental camostat or nafamostat are a promising option for the treatment of COVID-19.

SARS-CoV-2, the cause of the COVID-19 pandemic, exploits host proteins for viral entry into human lung cells and is blocked by otamixaban in combination with a covalent protease inhibitor.     

Rational design of thioamide peptides as selective inhibitors of cysteine protease cathepsin L

Aberrant levels of cathepsin L (Cts L), a ubiquitously expressed endosomal cysteine protease, have been implicated in many diseases such as cancer and diabetes. Significantly, Cts L has been identified as a potential target for the treatment of COVID-19 due to its recently unveiled critical role in SARS-CoV-2 entry into the host cells. However, there are currently no clinically approved specific inhibitors of Cts L, as it is often challenging to obtain specificity against the many highly homologous cathepsin family cysteine proteases. Peptide-based agents are often promising protease inhibitors as they offer high selectivity and potency, but unfortunately are subject to degradation in vivo. Thioamide substitution, a single-atom O-to-S modification in the peptide backbone, has been shown to improve the proteolytic stability of peptides addressing this issue. Utilizing this approach, we demonstrate herein that good peptidyl substrates can be converted into sub-micromolar inhibitors of Cts L by a single thioamide substitution in the peptide backbone. We have designed and scanned several thioamide stabilized peptide scaffolds, in which one peptide, R^S_1A, was stabilized against proteolysis by all five cathepsins (Cts L, Cts V, Cts K, Cts S, and Cts B) while inhibiting Cts L with >25-fold specificity against the other cathepsins. We further showed that this stabilized R^S_1A peptide could inhibit Cts L in human liver carcinoma lysates (IC₅₀ = 19 μM). Our study demonstrates that one can rationally design a stabilized, specific peptidyl protease inhibitor by strategic placement of a thioamide and reaffirms the place of this single-atom modification in the toolbox of peptide-based rational drug design.

Information on the effects of sidechain and backbone modification on the activity of cathepsin (Cts) L, V, K, S, and B was used to design a thioamide peptide that is inert to all Cts and selectively inhibits Cts L.     

Inhibitor binding influences the protonation states of histidines in SARS-CoV-2 main protease

The main protease (M^pro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an attractive target for antiviral therapeutics. Recently, many high-resolution apo and inhibitor-bound structures of M^pro, a cysteine protease, have been determined, facilitating structure-based drug design. M^pro plays a central role in the viral life cycle by catalyzing the cleavage of SARS-CoV-2 polyproteins. In addition to the catalytic dyad His41–Cys145, M^pro contains multiple histidines including His163, His164, and His172. The protonation states of these histidines and the catalytic nucleophile Cys145 have been debated in previous studies of SARS-CoV M^pro, but have yet to be investigated for SARS-CoV-2. In this work we have used molecular dynamics simulations to determine the structural stability of SARS-CoV-2 M^pro as a function of the protonation assignments for these residues. We simulated both the apo and inhibitor-bound enzyme and found that the conformational stability of the binding site, bound inhibitors, and the hydrogen bond networks of M^pro are highly sensitive to these assignments. Additionally, the two inhibitors studied, the peptidomimetic N3 and an α-ketoamide, display distinct His41/His164 protonation-state-dependent stabilities. While the apo and the N3-bound systems favored N_δ (HD) and N_ϵ (HE) protonation of His41 and His164, respectively, the α-ketoamide was not stably bound in this state. Our results illustrate the importance of using appropriate histidine protonation states to accurately model the structure and dynamics of SARS-CoV-2 M^pro in both the apo and inhibitor-bound states, a necessary prerequisite for drug-design efforts.

The main protease (M^pro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an attractive target for antiviral therapeutics.     

Peptide epitope-imprinted polymer microarrays for selective protein recognition. Application for SARS-CoV-2 RBD protein

We introduce a practically generic approach for the generation of epitope-imprinted polymer-based microarrays for protein recognition on surface plasmon resonance imaging (SPRi) chips. The SPRi platform allows the subsequent rapid screening of target binding kinetics in a multiplexed and label-free manner. The versatility of such microarrays, both as synthetic and screening platform, is demonstrated through developing highly affine molecularly imprinted polymers (MIPs) for the recognition of the receptor binding domain (RBD) of SARS-CoV-2 spike protein. A characteristic nonapeptide GFNCYFPLQ from the RBD and other control peptides were microspotted onto gold SPRi chips followed by the electrosynthesis of a polyscopoletin nanofilm to generate in one step MIP arrays. A single chip screening of essential synthesis parameters, including the surface density of the template peptide and its sequence led to MIPs with dissociation constants (K_D) in the lower nanomolar range for RBD, which exceeds the affinity of RBD for its natural target, angiotensin-convertase 2 enzyme. Remarkably, the same MIPs bound SARS-CoV-2 virus like particles with even higher affinity along with excellent discrimination of influenza A (H3N2) virus. While MIPs prepared with a truncated heptapeptide template GFNCYFP showed only a slightly decreased affinity for RBD, a single mismatch in the amino acid sequence of the template, i.e. the substitution of the central cysteine with a serine, fully suppressed the RBD binding.

We introduce highly affine epitope-imprinted polymer-based microarrays for selective protein detection by surface plasmon resonance imaging as shown through the selective recognition of the receptor binding domain of SARS-CoV-2 spike protein.     

Mechanism of inhibition of SARS-CoV-2 Mpro by N3 peptidyl Michael acceptor explained by QM/MM simulations and design of new derivatives with tunable chemical reactivity

The SARS-CoV-2 main protease (M^pro) is essential for replication of the virus responsible for the COVID-19 pandemic, and one of the main targets for drug design. Here, we simulate the inhibition process of SARS-CoV-2 M^pro with a known Michael acceptor (peptidyl) inhibitor, N3. The free energy landscape for the mechanism of the formation of the covalent enzyme-inhibitor product is computed with QM/MM molecular dynamics methods. The simulations show a two-step mechanism, and give structures and calculated barriers in good agreement with experiment. Using these results and information from our previous investigation on the proteolysis reaction of SARS-CoV-2 M^pro, we design two new, synthetically accessible N3-analogues as potential inhibitors, in which the recognition and warhead motifs are modified. QM/MM modelling of the mechanism of inhibition of M^pro by these novel compounds indicates that both may be promising candidates as drug leads against COVID-19, one as an irreversible inhibitor and one as a potential reversible inhibitor.

QM/MM simulations identify the mechanism of reaction of N3, a covalent peptidyl inhibitor of SARS-CoV-2 main protease. Modelling of two novel proposed compounds, B1 and B2, suggests that reversibility of covalent inhibition could be tailored.     

Automated discovery of noncovalent inhibitors of SARS-CoV-2 main protease by consensus Deep Docking of 40 billion small molecules

Recent explosive growth of ‘make-on-demand’ chemical libraries brought unprecedented opportunities but also significant challenges to the field of computer-aided drug discovery. To address this expansion of the accessible chemical universe, molecular docking needs to accurately rank billions of chemical structures, calling for the development of automated hit-selecting protocols to minimize human intervention and error. Herein, we report the development of an artificial intelligence-driven virtual screening pipeline that utilizes Deep Docking with Autodock GPU, Glide SP, FRED, ICM and QuickVina2 programs to screen 40 billion molecules against SARS-CoV-2 main protease (Mpro). This campaign returned a significant number of experimentally confirmed inhibitors of Mpro enzyme, and also enabled to benchmark the performance of twenty-eight hit-selecting strategies of various degrees of stringency and automation. These findings provide new starting scaffolds for hit-to-lead optimization campaigns against Mpro and encourage the development of fully automated end-to-end drug discovery protocols integrating machine learning and human expertise.

Deep learning-accelerated docking coupled with computational hit selection strategies enable the identification of inhibitors for the SARS-CoV-2 main protease from a chemical library of 40 billion small molecules.     

Structure-based de novo drug design using 3D deep generative models

Deep generative models are attracting much attention in the field of de novo molecule design. Compared to traditional methods, deep generative models can be trained in a fully data-driven way with little requirement for expert knowledge. Although many models have been developed to generate 1D and 2D molecular structures, 3D molecule generation is less explored, and the direct design of drug-like molecules inside target binding sites remains challenging. In this work, we introduce DeepLigBuilder, a novel deep learning-based method for de novo drug design that generates 3D molecular structures in the binding sites of target proteins. We first developed Ligand Neural Network (L-Net), a novel graph generative model for the end-to-end design of chemically and conformationally valid 3D molecules with high drug-likeness. Then, we combined L-Net with Monte Carlo tree search to perform structure-based de novo drug design tasks. In the case study of inhibitor design for the main protease of SARS-CoV-2, DeepLigBuilder suggested a list of drug-like compounds with novel chemical structures, high predicted affinity, and similar binding features to those of known inhibitors. The current version of L-Net was trained on drug-like compounds from ChEMBL, which could be easily extended to other molecular datasets with desired properties based on users'' demands and applied in functional molecule generation. Merging deep generative models with atomic-level interaction evaluation, DeepLigBuilder provides a state-of-the-art model for structure-based de novo drug design and lead optimization.

DeepLigBuilder, a novel deep generative model for structure-based de novo drug design, directly generates 3D structures of drug-like compounds in the target binding site.     

Fine-tuning the spike: role of the nature and topology of the glycan shield in the structure and dynamics of the SARS-CoV-2 S

The dense glycan shield is an essential feature of the SARS-CoV-2 spike (S) architecture, key to immune evasion and to the activation of the prefusion conformation. Recent studies indicate that the occupancy and structures of the SARS-CoV-2 S glycans depend not only on the nature of the host cell, but also on the structural stability of the trimer; a point that raises important questions about the relative competence of different glycoforms. Moreover, the functional role of the glycan shield in the SARS-CoV-2 pathogenesis suggests that the evolution of the sites of glycosylation is potentially intertwined with the evolution of the protein sequence to affect optimal activity. Our results from multi-microsecond molecular dynamics simulations indicate that the type of glycosylation at N234, N165 and N343 greatly affects the stability of the receptor binding domain (RBD) open conformation, and thus its exposure and accessibility. Furthermore, our results suggest that the loss of glycosylation at N370, a newly acquired modification in the SARS-CoV-2 S glycan shield''s topology, may have contributed to increase the SARS-CoV-2 infectivity as we find that N-glycosylation at N370 stabilizes the closed RBD conformation by binding a specific cleft on the RBD surface. We discuss how the absence of the N370 glycan in the SARS-CoV-2 S frees the RBD glycan binding cleft, which becomes available to bind cell-surface glycans, and potentially increases host cell surface localization.

The N-glycans structures affect the mechanistic properties of the SARS-CoV-2 S, fine-tuning the glycoprotein. The evolution of the glycan shield led to the loss of N370 glycosylation in SARS-CoV-2 S, where the RBD cleft can bind host-cell glycans.     

Discovery of SARS-CoV-2 Mpro peptide inhibitors from modelling substrate and ligand binding

The main protease (M^pro) of SARS-CoV-2 is central to viral maturation and is a promising drug target, but little is known about structural aspects of how it binds to its 11 natural cleavage sites. We used biophysical and crystallographic data and an array of biomolecular simulation techniques, including automated docking, molecular dynamics (MD) and interactive MD in virtual reality, QM/MM, and linear-scaling DFT, to investigate the molecular features underlying recognition of the natural M^pro substrates. We extensively analysed the subsite interactions of modelled 11-residue cleavage site peptides, crystallographic ligands, and docked COVID Moonshot-designed covalent inhibitors. Our modelling studies reveal remarkable consistency in the hydrogen bonding patterns of the natural M^pro substrates, particularly on the N-terminal side of the scissile bond. They highlight the critical role of interactions beyond the immediate active site in recognition and catalysis, in particular plasticity at the S2 site. Building on our initial M^pro-substrate models, we used predictive saturation variation scanning (PreSaVS) to design peptides with improved affinity. Non-denaturing mass spectrometry and other biophysical analyses confirm these new and effective ‘peptibitors’ inhibit M^pro competitively. Our combined results provide new insights and highlight opportunities for the development of M^pro inhibitors as anti-COVID-19 drugs.

The main protease (M^pro) of SARS-CoV-2 is central to viral maturation and is a promising drug target. In silico methods reveal structural aspects of how it binds to its 11 natural cleavage sites, the design of novel peptide inhibitors, and insights into drug design.     

Revealing the molecular mechanisms of proteolysis of SARS-CoV-2 Mpro by QM/MM computational methods

SARS-CoV-2 M^pro is one of the enzymes essential for the replication process of the virus responsible for the COVID-19 pandemic. This work is focused on exploring its proteolysis reaction by means of QM/MM methods. The resulting free energy landscape of the process provides valuable information on the species appearing along the reaction path and suggests that the mechanism of action of this enzyme, taking place in four steps, slightly differs from that of other cysteine proteases. Our predictions, which are in agreement with some recently published experimental data, can be used to guide the design of COVID-19 antiviral compounds with clinical potential.

The molecular mechanism of the proteolysis reaction catalyzed by SARS-CoV-2 M^pro, one of the enzymes essential for the replication process of the virus responsible for the COVID-19 pandemic, is described using computational QM/MM methods.     

Point mutations in SARS-CoV-2 variants induce long-range dynamical perturbations in neutralizing antibodies

Monoclonal antibodies are emerging as a viable treatment for the coronavirus disease 19 (COVID-19). However, newly evolved variants of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can reduce the efficacy of currently available antibodies and can diminish vaccine-induced immunity. Here, we demonstrate that the microscopic dynamics of neutralizing monoclonal antibodies can be profoundly modified by the mutations present in the spike proteins of the SARS-COV-2 variants currently circulating in the world population. The dynamical perturbations within the antibody structure, which alter the thermodynamics of antigen recognition, are diverse and can depend both on the nature of the antibody and on the spatial location of the spike mutation. The correlation between the motion of the antibody and that of the spike receptor binding domain (RBD) can also be changed, modulating binding affinity. Using protein-graph-connectivity networks, we delineated the mutant-induced modifications in the information-flow along allosteric pathway throughout the antibody. Changes in the collective dynamics were spatially distributed both locally and across long-range distances within the antibody. On the receptor side, we identified an anchor-like structural element that prevents the detachment of the antibodies; individual mutations there can significantly affect the antibody binding propensity. Our study provides insight into how virus neutralization by monoclonal antibodies can be impacted by local mutations in the epitope via a change in dynamics. This realization adds a new layer of sophistication to the efforts for rational design of monoclonal antibodies against new variants of SARS-CoV2, taking the allostery in the antibody into consideration.

Mutations in the new variants of SARS-CoV-2 spike protein modulates the dynamics of the neutralizing antibodies. Capturing such modulations from MD simulations and graph network model identifies the role of mutations in facilitating immune evasion.     

Translating daily COVID-19 screening into a simple glucose test: a proof of concept study

Home testing is an attractive emerging strategy to combat the COVID-19 pandemic and prevent overloading of healthcare resources through at-home isolation, screening and monitoring of symptoms. However, current diagnostic technologies of SARS-CoV-2 still suffer from some drawbacks because of the tradeoffs between sensitivity, usability and costs, making the test unaffordable to most users at home. To address these limitations, taking advantage of clustered regularly interspaced short palindromic repeats (CRISPRs) and a portable glucose meter (PGM), we present a proof-of-concept demonstration of a target-responsive CRISPR-PGM system for translating SARS-CoV-2 detection into a glucose test. Using this system, a specific N gene, N protein, and pseudo-viruses of SARS-CoV-2 have been detected quantitatively with a PGM. Given the facile integration of various bioreceptors into the CRISPR-PGM system, the proposed method provides a starting point to provide patients with a single-device solution that can quantitatively monitor multiple COVID-19 biomarkers at home.

COVID-19 glucose test: translating SARS-CoV-2 detection into a glucose test is achieved by incorporating target-responsive rolling circle amplification and a CRISPR-based collateral cleavage module with a portable glucose meter.     

Structure-mechanics statistical learning uncovers mechanical relay in proteins

A protein''s adaptive response to its substrates is one of the key questions driving molecular physics and physical chemistry. This work employs the recently developed structure-mechanics statistical learning method to establish a mechanical perspective. Specifically, by mapping all-atom molecular dynamics simulations onto the spring parameters of a backbone-side-chain elastic network model, the chemical moiety specific force constants (or mechanical rigidity) are used to assemble the rigidity graph, which is the matrix of inter-residue coupling strength. Using the S1A protease and the PDZ3 signaling domain as examples, chains of spatially contiguous residues are found to exhibit prominent changes in their mechanical rigidity upon substrate binding or dissociation. Such a mechanical-relay picture thus provides a mechanistic underpinning for conformational changes, long-range communication, and inter-domain allostery in both proteins, where the responsive mechanical hotspots are mostly residues having important biological functions or significant mutation sensitivity.

Protein residues exhibit specific routes of mechanical relay as the adaptive responses to substrate binding or dissociation. On such physically contiguous connections, residues experience prominent changes in their coupling strengths.     

OvoAMtht from Methyloversatilis thermotolerans ovothiol biosynthesis is a bifunction enzyme: thiol oxygenase and sulfoxide synthase activities

Mononuclear non-heme iron enzymes are a large class of enzymes catalyzing a wide-range of reactions. In this work, we report that a non-heme iron enzyme in Methyloversatilis thermotolerans, OvoA_Mtht, has two different activities, as a thiol oxygenase and a sulfoxide synthase. When cysteine is presented as the only substrate, OvoA_Mtht is a thiol oxygenase. In the presence of both histidine and cysteine as substrates, OvoA_Mtht catalyzes the oxidative coupling between histidine and cysteine (a sulfoxide synthase). Additionally, we demonstrate that both substrates and the active site iron''s secondary coordination shell residues exert exquisite control over the dual activities of OvoA_Mtht (sulfoxide synthase vs. thiol oxygenase activities). OvoA_Mtht is an excellent system for future detailed mechanistic investigation on how metal ligands and secondary coordination shell residues fine-tune the iron-center electronic properties to achieve different reactivities.

Modulation of OvoA_Mtht''s dual activities: sulfoxide synthase and thiol oxygenase.     

Conformational interplay in hybrid peptide–helical aromatic foldamer macrocycles

Macrocyclic peptides are an important class of bioactive substances. When inserting an aromatic foldamer segment in a macrocyclic peptide, the strong folding propensity of the former may influence the conformation and alter the properties of the latter. Such an insertion is relevant because some foldamer–peptide hybrids have recently been shown to be tolerated by the ribosome, prior to forming macrocycles, and can thus be produced using an in vitro translation system. We have investigated the interplay of peptide and foldamer conformations in such hybrid macrocycles. We show that foldamer helical folding always prevails and stands as a viable means to stretch, i.e. unfold, peptides in a solvent dependent manner. Conversely, the peptide systematically has a reciprocal influence and gives rise to strong foldamer helix handedness bias as well as foldamer helix stabilisation. The hybrid macrocycles also show resistance towards proteolytic degradation.

When peptides and helical aromatic foldamers are combined in a macrocycle, an interplay of their properties is observed, including helix handedness bias, helix stabilisation, peptide stretching and peptide resistance to proteolytic degradation.     

Late-stage modification of peptides and proteins at cysteine with diaryliodonium salts

The modification of peptides and proteins has emerged as a powerful means to efficiently prepare high value bioconjugates for a range of applications in chemical biology and for the development of next-generation therapeutics. Herein, we report a novel method for the chemoselective late-stage modification of peptides and proteins at cysteine in aqueous buffer with suitably functionalised diaryliodonium salts, furnishing stable thioether-linked synthetic conjugates. The power of this new platform is showcased through the late-stage modification of the affibody zEGFR and the histone protein H2A.

New operationally simple platform for the chemoselective arylation of cysteine in peptides and proteins to access a variety of high value bioconjugates.