Prioritisation of Compounds for 3CLpro Inhibitor Development on SARS-CoV-2 Variants

Computational Analysis of S1PR1 SNPs Reveals Drug Binding Modes Relevant to Multiple Sclerosis Treatment

Background/Objectives: Multiple sclerosis (MS) is an autoimmune disorder of the central nervous system (CNS) characterized by myelin and axonal damage with a globally rising incidence. While there is no known cure for MS, various disease-modifying treatments (DMTs) exist, including those targeting Sphingosine-1-Phosphate Receptors (S1PRs), which play important roles in immune response, CNS function, and cardiovascular regulation. This study focuses on understanding how nonsynonymous single nucleotide polymorphisms (rs1299231517, rs1323297044, rs1223284736, rs1202284551, rs1209378712, rs201200746, and rs1461490142) in the S1PR1's active site affect the binding of endogenous ligands, as well as different drugs used in MS management. Methods: Extensive molecular dynamics simulations and linear interaction energy (LIE) calculations were employed to predict binding affinities and potentially guide future personalized medicinal therapies. The empirical parameters of the LIE method were optimized using the binding free energies calculated from experimentally determined IC50 values. These optimized parameters were then applied to calculate the binding free energies of S1P to mutated S1PR1, which correlated well with experimental values, confirming their validity for assessing the impact of SNPs on S1PR1 binding affinities. Results: The binding free energies varied from the least favorable -8.2 kcal/mol for the wild type with ozanimod to the most favorable -16.7 kcal/mol for the combination of siponimod with the receptor carrying the F2055.42L mutation. Conclusions: We successfully demonstrated the differences in the binding modes, interactions, and affinities of investigated MS drugs in connection with SNPs in the S1PR1 binding site, resulting in several viable options for personalized therapies depending on the present mutations.

Identification of SARS-CoV-2 Main Protease Inhibitors Using Chemical Similarity Analysis Combined with Machine Learning

SARS-CoV-2 Main Protease (Mpro) is an enzyme that cleaves viral polyproteins translated from the viral genome, which is critical for viral replication. Mpro is a target for anti-SARS-CoV-2 drug development. Herein, we performed a large-scale virtual screening by comparing multiple structural descriptors of reference molecules with reported anti-coronavirus activity against a library with >17 million compounds. Further filtering, performed by applying two machine learning algorithms, identified eighteen computational hits as anti-SARS-CoV-2 compounds with high structural diversity and drug-like properties. The activities of twelve compounds on Mpro's enzymatic activity were evaluated by fluorescence resonance energy transfer (FRET) assays. Compound 13 (ZINC13878776) significantly inhibited SARS-CoV-2 Mpro activity and was employed as a reference for an experimentally hit expansion. The structural analogues 13a (ZINC4248385), 13b (ZNC13523222), and 13c (ZINC4248365) were tested as Mpro inhibitors, reducing the enzymatic activity of recombinant Mpro with potency as follows: 13c > 13 > 13b > 13a. Then, their anti-SARS-CoV-2 activities were evaluated in plaque reduction assays using Vero CCL81 cells. Subtoxic concentrations of compounds 13a, 13c, and 13b displayed in vitro antiviral activity with IC50 in the mid micromolar range. Compounds 13a-c could become lead compounds for the development of new Mpro inhibitors with improved activity against anti-SARS-CoV-2.

Design of Tetra-Peptide Ligands of Antibody Fc Regions Using In Silico Combinatorial Library Screening

Peptides, or short chains of amino-acid residues, are becoming increasingly important as active ingredients of drugs and as crucial probes and/or tools in medical, biotechnological, and pharmaceutical research. Situated at the interface between small molecules and larger macromolecular systems, they pose a difficult challenge for computational methods. We report an in silico peptide library generation and prioritization workflow using CmDock for identifying tetrapeptide ligands that bind to Fc regions of antibodies that is analogous to known in vitro recombinant peptide libraries' display and expression systems. The results of our in silico study are in accordance with existing scientific literature on in vitro peptides that bind to antibody Fc regions. In addition, we postulate an evolving in silico library design workflow that will help circumvent the combinatorial problem of in vitro comprehensive peptide libraries by focusing on peptide subunits that exhibit favorable interaction profiles in initial in silico peptide generation and testing.

Preventative and therapeutic potential of animal milk components against COVID-19: A comprehensive review

The global pandemic of COVID-19 is considered one of the most catastrophic events on earth. During the pandemic, food ingredients may play crucial roles in preventing infectious diseases and sustaining people's general health and well-being. Animal milk acts as a super food since it has the capacity to minimize the occurrence of viral infections due to inherent antiviral properties of its ingredients. SARS-CoV-2 virus infection can be prevented by immune-enhancing and antiviral properties of caseins, α-lactalbumin, β-lactoglobulin, mucin, lactoferrin, lysozyme, lactoperoxidase, oligosaccharides, glycosaminoglycans, and glycerol monolaurate. Some of the milk proteins (i.e., lactoferrin) may work synergistically with antiviral medications (e.g., remdesivir), and enhance the effectiveness of treatment in this disease. Cytokine storm during COVID-19 can be managed by casein hydrolyzates, lactoferrin, lysozyme, and lactoperoxidase. Thrombus formation can be prevented by casoplatelins as these can inhibit human platelet aggregation. Milk vitamins (i.e., A, D, E, and B complexes) and minerals (i.e., Ca, P, Mg, Zn, and Se) can have significantly positive effects on boosting the immunity and health status of individuals. In addition, certain vitamins and minerals can also act as antioxidants, anti-inflammatory, and antivirals. Thus, the overall effect of milk might be a result of synergistic antiviral effects and host immunomodulator activities from multiple components. Due to multiple overlapping functions of milk ingredients, they can play vital and synergistic roles in prevention as well as supportive agents during principle therapy of COVID-19.

Mechanistic Insights of Polyphenolic Compounds from Rosemary Bound to Their Protein Targets Obtained by Molecular Dynamics Simulations and Free-Energy Calculations

Rosemary represents an important medicinal plant that has been attributed with various health-promoting properties, especially antioxidative, anti-inflammatory, and anticarcinogenic activities. Carnosic acid, carnosol, and rosmanol, as well as the phenolic acid ester rosmarinic acid, are the main compounds responsible for these actions. In our earlier research, we carried out an inverse molecular docking at the proteome scale to determine possible protein targets of the mentioned compounds. Here, we subjected the previously identified ligand-protein complexes with HIV-1 protease, K-RAS, and factor X to molecular dynamics simulations coupled with free-energy calculations. We observed that carnosic acid and rosmanol act as viable binders of the HIV-1 protease. In addition, carnosol represents a potential binder of the oncogene protein K-RAS. On the other hand, rosmarinic acid was characterized as a weak binder of factor X. We also emphasized the importance of water-mediated hydrogen-bond networks in stabilizing the binding conformation of the studied polyphenols, as well as in mechanistically explaining their promiscuous nature.

Functional dynamics of SARS-CoV-2 3C-like protease as a member of clan PA

SARS-CoV-2 3C-like protease (3CL^pro), a potential therapeutic target for COVID-19, consists of a chymotrypsin fold and a C-terminal α-helical domain (domain III), the latter of which mediates dimerization required for catalytic activation. To gain further understanding of the functional dynamics of SARS-CoV-2 3CL^pro, this review extends the scope to the comparative study of many crystal structures of proteases having the chymotrypsin fold (clan PA of the MEROPS database). First, the close correspondence between the zymogen-enzyme transformation in chymotrypsin and the allosteric dimerization activation in SARS-CoV-2 3CL^pro is illustrated. Then, it is shown that the 3C-like proteases of family Coronaviridae (the protease family C30), which are closely related to SARS-CoV-2 3CL^pro, have the same homodimeric structure and common activation mechanism via domain III mediated dimerization. The survey extended to order Nidovirales reveals that all 3C-like proteases belonging to Nidovirales have domain III, but with various chain lengths, and 3CL^pro of family Mesoniviridae (family C107) has the same homodimeric structure as that of C30, even though they have no sequence similarity. As a reference, monomeric 3C proteases belonging to the more distant family Picornaviridae (family C3) lacking domain III are compared with C30, and it is shown that the 3C proteases are rigid enough to maintain their structures in the active state.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12551-022-01020-x.

Ginkgo biloba in the management of the COVID-19 severity

The severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection is linked with inflammatory disorders and the development of oxidative stress in extreme cases. Therefore, anti-inflammatory and antioxidant drugs may alleviate these complications. Ginkgo biloba L. folium extract (EGb) is a herbal medicine containing various active constituents. This review aims to provide a critical discussion on the potential role of EGb in the management of coronavirus disease 2019 (COVID-19). The antiviral effect of EGb is mediated by different mechanisms, including blocking SARS-CoV-2 3-chymotrypsin-like protease that provides trans-variant effectiveness. Moreover, EGb impedes the development of pulmonary inflammatory disorders through the diminution of neutrophil elastase activity, the release of proinflammatory cytokines, platelet aggregation, and thrombosis. Thus, EGb can attenuate the acute lung injury and acute respiratory distress syndrome in COVID-19. In conclusion, EGb offers the potential of being used as adjuvant antiviral and symptomatic therapy. Nanosystems enabling targeted delivery, personalization, and booster of effects provide the opportunity for the use of EGb in modern phytotherapy.

Production of a functionally active recombinant SARS-CoV-2 (COVID-19) 3C-Like protease and a soluble inactive 3C-like protease-RBD chimeric in a prokaryotic expression system

During the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) intracellular life-cycle, two large polyproteins, pp1a and pp1ab, are produced. Processing of these by viral cysteine proteases, the papain-like protease (PLpro) and the chymotrypsin-like 3C-like protease (3CL-pro) release non-structural proteins necessary for the establishment of the viral replication and transcription complex (RTC), crucial for viral replication. Hence, these proteases are considered prime targets against which anti-coronavirus disease 2019 (COVID-19) drugs could be developed. Here, we describe the expression of a highly soluble and functionally active recombinant 3CL-pro using Escherichia coli BL21 cells. We show that the enzyme functions in a dimeric form and exhibits an unexpected inhibitory profile because its activity is potently blocked by serine rather than cysteine protease inhibitors. In addition, we assessed the ability of our 3CL-pro to function as a carrier for the receptor binding domain (RBD) of the Spike protein. The co-expressed chimeric protein, 3CLpro-RBD, did not exhibit 3CL-pro activity, but its enhanced solubility made purification easier and improved RBD antigenicity when tested against serum from vaccinated individuals in ELISAs. Chimeric proteins containing the 3CL-pro could represent an innovative approach to developing new COVID-19 vaccines.

Rational Discovery of Antiviral Whey Protein-Derived Small Peptides Targeting the SARS-CoV-2 Main Protease

In the present work, and for the first time, three whey protein-derived peptides (IAEK, IPAVF, MHI), endowed with ACE inhibitory activity, were examined for their antiviral activity against the SARS-CoV-2 3C-like protease (3CL^pro) and Human Rhinovirus 3C protease (3C^pro) by employing molecular docking. Computational studies showed reliable binding poses within 3CL^pro for the three investigated small peptides, considering docking scores as well as the binding free energy values. Validation by in vitro experiments confirmed these results. In particular, IPAVF exhibited the highest inhibitory activity by returning an IC₅₀ equal to 1.21 μM; it was followed by IAEK, which registered an IC₅₀ of 154.40 μM, whereas MHI was less active with an IC₅₀ equal to 2700.62 μM. On the other hand, none of the assayed peptides registered inhibitory activity against 3C^pro. Based on these results, the herein presented small peptides are introduced as promising molecules to be exploited in the development of “target-specific antiviral” agents against SARS-CoV-2.

Development of a colorimetric assay for the detection of SARS-CoV-2 3CLpro activity

Diagnostic testing continues to be an integral component of the strategy to contain the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) global pandemic, the causative agent of Coronavirus Disease 2019 (COVID-19). The SARS-CoV-2 genome encodes the 3C-like protease (3CLpro) which is essential for coronavirus replication. This study adapts an in vitro colorimetric gold nanoparticle (AuNP) based protease assay to specifically detect the activity of SARS-CoV-2 3CLpro as a purified recombinant protein and as a cellular protein exogenously expressed in HEK293T human cells. We also demonstrate that the specific sensitivity of the assay for SARS-CoV-2 3CLpro can be improved by use of an optimised peptide substrate and through hybrid dimerisation with inactive 3CLpro mutant monomers. These findings highlight the potential for further development of the AuNP protease assay to detect SARS-CoV-2 3CLpro activity as a novel, accessible and cost-effective diagnostic test for SARS-CoV-2 infection at the point-of-care. Importantly, this versatile assay could also be easily adapted to detect specific protease activity associated with other viruses or diseases conditions.

Investigating novel thiazolyl-indazole derivatives as scaffolds for SARS-CoV-2 MPro inhibitors

COVID-19 is a global pandemic caused by infection with the SARS-CoV-2 virus. Remdesivir, a SARS-CoV-2 RNA polymerase inhibitor, is the only drug to have received widespread approval for treatment of COVID-19. The SARS-CoV-2 main protease enzyme (MPro), essential for viral replication and transcription, remains an active target in the search for new treatments. In this study, the ability of novel thiazolyl-indazole derivatives to inhibit MPro is evaluated. These compounds were synthesized via the heterocyclization of phenacyl bromide with (R)-carvone, (R)-pulegone and (R)-menthone thiosemicarbazones. The binding affinity and binding interactions of each compound were evaluated through Schrödinger Glide docking, AMBER molecular dynamics simulations, and MM-GBSA free energy estimation, and these results were compared with similar calculations of MPro binding various 5-mer substrates (VKLQA, VKLQS, VKLQG) and a previously identified MPro tight-binder X77. From these simulations, we can see that binding is driven by residue specific interactions such as π-stacking with His41, and S/π interactions with Met49 and Met165. The compounds were also experimentally evaluated in a MPro biochemical assay and the most potent compound containing a phenylthiazole moiety inhibited protease activity with an IC50 of 92.9 ​μM. This suggests that the phenylthiazole scaffold is a promising candidate for the development of future MPro inhibitors.

Artificial Intelligence Technologies for COVID-19 De Novo Drug Design

The recent covid crisis has provided important lessons for academia and industry regarding digital reorganization. Among the fascinating lessons from these times is the huge potential of data analytics and artificial intelligence. The crisis exponentially accelerated the adoption of analytics and artificial intelligence, and this momentum is predicted to continue into the 2020s and beyond. Drug development is a costly and time-consuming business, and only a minority of approved drugs generate returns exceeding the research and development costs. As a result, there is a huge drive to make drug discovery cheaper and faster. With modern algorithms and hardware, it is not too surprising that the new technologies of artificial intelligence and other computational simulation tools can help drug developers. In only two years of covid research, many novel molecules have been designed/identified using artificial intelligence methods with astonishing results in terms of time and effectiveness. This paper reviews the most significant research on artificial intelligence in de novo drug design for COVID-19 pharmaceutical research.

In silico discovery of novel inhibitors from Northern African natural products database against main protease (Mpro) of SARS-CoV-2

The recent outbreak of COVID-19 (Coronavirus Disease 2019), caused by a novel SARS-CoV-2 virus, has led to public health emergencies worldwide where time is as important as equipment to save lives. Antimalarial drugs such as hydroxychloroquine and chloroquine derivatives are used in emergencies but they are not suitable for patients with high blood pressure, diabetes and heart problems. Since there are no approved drugs for this disease, science is challenged to find vaccines and new drugs. Therefore, as part of our Silico drug design strategy, we identified drug-like compounds that inhibit replication of the main protease (Mpro) of SARS-CoV-2 based on receptor-based virtual database screening, molecular docking, molecular dynamics, and drug-similarity profiling from the NANPDB natural products database available at North African. The two resulting hit compounds named 5- Chloro-Omega-hydroxy-1-O-methylemodin and cystodion E showed the highest binding energy with Mpro of SARS-CoV-2 and strong inhibitory activity compared with the previously published N3 inhibitor. The complexes of these two compounds were validated by molecular dynamics analysis (RMSD, RMSF, Rg, total number of hydrogen bonds and secondary structure fractions of the protein in the complex) as the best method to evaluate the biological stability of the system. Therefore, these molecules deserve more attention in drug development compared to COVID-19. HighlightsA large database of natural compounds was screened against nCoV-2's Mpro.Molecular docking and Molecular dynamics were used as powerful methods.Two compounds were found are very attractive to inhibit Mpro of nCoV-2.ADME-Tox profiling is evaluated the active compounds are not cancerogenic.Communicated by Ramaswamy H. Sarma.

Casiopeinas® as SARS-CoV-2 main protease (Mpro) inhibitors: a combined DFT, molecular docking and ONIOM approach

Computational combined protocols suggest that Casiopeinas can block the active site of Mpro SARS-CoV-2 by binding to its main amino acids.

Commercial SARS-CoV-2 Targeted, Protease Inhibitor Focused and Protein-Protein Interaction Inhibitor Focused Molecular Libraries for Virtual Screening and Drug Design

Since December 2019, the new SARS-CoV-2-related COVID-19 disease has caused a global pandemic and shut down the public life worldwide. Several proteins have emerged as potential therapeutic targets for drug development, and we sought out to review the commercially available and marketed SARS-CoV-2-targeted libraries ready for high-throughput virtual screening (HTVS). We evaluated the SARS-CoV-2-targeted, protease-inhibitor-focused and protein-protein-interaction-inhibitor-focused libraries to gain a better understanding of how these libraries were designed. The most common were ligand- and structure-based approaches, along with various filtering steps, using molecular descriptors. Often, these methods were combined to obtain the final library. We recognized the abundance of targeted libraries offered and complimented by the inclusion of analytical data; however, serious concerns had to be raised. Namely, vendors lack the information on the library design and the references to the primary literature. Few references to active compounds were also provided when using the ligand-based design and usually only protein classes or a general panel of targets were listed, along with a general reference to the methods, such as molecular docking for the structure-based design. No receptor data, docking protocols or even references to the applied molecular docking software (or other HTVS software), and no pharmacophore or filter design details were given. No detailed functional group or chemical space analyses were reported, and no specific orientation of the libraries toward the design of covalent or noncovalent inhibitors could be observed. All libraries contained pan-assay interference compounds (PAINS), rapid elimination of swill compounds (REOS) and aggregators, as well as focused on the drug-like model, with the majority of compounds possessing their molecular mass around 500 g/mol. These facts do not bode well for the use of the reviewed libraries in drug design and lend themselves to commercial drug companies to focus on and improve.

Repurposing of Drugs for SARS-CoV-2 Using Inverse Docking Fingerprints

Severe acute respiratory syndrome coronavirus 2 or SARS-CoV-2 is a virus that belongs to the Coronaviridae family. This group of viruses commonly causes colds but possesses a tremendous pathogenic potential. In humans, an outbreak of SARS caused by the SARS-CoV virus was first reported in 2003, followed by 2012 when the Middle East respiratory syndrome coronavirus (MERS-CoV) led to an outbreak of Middle East respiratory syndrome (MERS). Moreover, COVID-19 represents a serious socioeconomic and global health problem that has already claimed more than four million lives. To date, there are only a handful of therapeutic options to combat this disease, and only a single direct-acting antiviral, the conditionally approved remdesivir. Since there is an urgent need for active drugs against SARS-CoV-2, the strategy of drug repurposing represents one of the fastest ways to achieve this goal. An in silico drug repurposing study using two methods was conducted. A structure-based virtual screening of the FDA-approved drug database on SARS-CoV-2 main protease was performed, and the 11 highest-scoring compounds with known 3CLpro activity were identified while the methodology was used to report further 11 potential and completely novel 3CLpro inhibitors. Then, inverse molecular docking was performed on the entire viral protein database as well as on the Coronaviridae family protein subset to examine the hit compounds in detail. Instead of target fishing, inverse docking fingerprints were generated for each hit compound as well as for the five most frequently reported and direct-acting repurposed drugs that served as controls. In this way, the target-hitting space was examined and compared and we can support the further biological evaluation of all 11 newly reported hits on SARS-CoV-2 3CLpro as well as recommend further in-depth studies on antihelminthic class member compounds. The authors acknowledge the general usefulness of this approach for a full-fledged inverse docking fingerprint screening in the future.

Molecular docking identification for the efficacy of natural limonoids against COVID-19 virus main protease

COVID-19 pandemic is the biggest public health problem of the century so far.The main protease (Mpro) is one of the main enzymes studied as a pharmacological target. In this context, the present work aimed to perform a virtual screening of possible inhibitors against the enzyme Mpro, having limonoids as the main object of research as supposed inhibitors. Molecular docking simulations indicated that limonoids have an affinity to complex with M-pro.However, Limonine and Nimoliciol showed nonspecific and low affinity interactions. In conclusion, Limonoids are substances of natural origin that can be used in the study of new pharmacological tools designed to combat and understand COVID-19.

Viral 3CLpro as a Target for Antiviral Intervention Using Milk-Derived Bioactive Peptides

Viruses of the picornavirus-like supercluster mainly achieve cleavage of polyproteins into mature proteins through viral 3-chymotrypsin proteases (3C^pro) or 3-chymotrypsin-like proteases (3CL^pro). Due to the essential role in processing viral polyproteins, 3C^pro/3CL^pro is a drug target for treating viral infections. The 3CL^pro is considered the main protease (M^pro) of coronaviruses. In the current study, the SARS-CoV-2 M^pro inhibitory activity of di- and tri-peptides (DTPs) resulted from the proteolysis of bovine milk proteins was evaluated. A set of 326 DTPs were obtained from virtual digestion of bovine milk major proteins. The resulted DTPs were screened using molecular docking. Twenty peptides (P1–P20) showed the best binding energies (ΔG_b <  − 7.0 kcal/mol). Among these 20 peptides, the top five ligands, namely P1 (RVY), P3 (QSW), P17 (DAY), P18 (QSA), and P20 (RNA), based on the highest binding affinity and the highest number of interactions with residues in the active site of M^pro were selected for further characterization by ADME/Tox analyses. For further validation of our results, molecular dynamics simulation was carried out for P3 as one of the most favorable candidates for up to 100 ns. In comparison to N3, a peptidomimetic control inhibitor, high stability was observed as supported by the calculated binding energy of the M^pro-P3 complex (− 59.48 ± 4.87 kcal/mol). Strong interactions between P3 and the M^pro active site, including four major hydrogen bonds to HIS41, ASN142, GLU166, GLN189 residues, and many hydrophobic interactions from which the interaction with CYS145 as a catalytic residue is worth mentioning. Conclusively, milk-derived bioactive peptides, especially the top five selected peptides P1, P3, P17, P18, and P20, show promise as an antiviral lead compound.

Exploring the Binding Mechanism of PF-07321332 SARS-CoV-2 Protease Inhibitor through Molecular Dynamics and Binding Free Energy Simulations

The novel coronavirus disease, caused by severe acute respiratory coronavirus 2 (SARS-CoV-2), rapidly spreading around the world, poses a major threat to the global public health. Herein, we demonstrated the binding mechanism of PF-07321332, α-ketoamide, lopinavir, and ritonavir to the coronavirus 3-chymotrypsin-like-protease (3CLpro) by means of docking and molecular dynamic (MD) simulations. The analysis of MD trajectories of 3CLpro with PF-07321332, α-ketoamide, lopinavir, and ritonavir revealed that 3CLpro-PF-07321332 and 3CLpro-α-ketoamide complexes remained stable compared with 3CLpro-ritonavir and 3CLpro-lopinavir. Investigating the dynamic behavior of ligand-protein interaction, ligands PF-07321332 and α-ketoamide showed stronger bonding via making interactions with catalytic dyad residues His41-Cys145 of 3CLpro. Lopinavir and ritonavir were unable to disrupt the catalytic dyad, as illustrated by increased bond length during the MD simulation. To decipher the ligand binding mode and affinity, ligand interactions with SARS-CoV-2 proteases and binding energy were calculated. The binding energy of the bespoke antiviral PF-07321332 clinical candidate was two times higher than that of α-ketoamide and three times than that of lopinavir and ritonavir. Our study elucidated in detail the binding mechanism of the potent PF-07321332 to 3CLpro along with the low potency of lopinavir and ritonavir due to weak binding affinity demonstrated by the binding energy data. This study will be helpful for the development and optimization of more specific compounds to combat coronavirus disease.