A genetically encoded BRET-based SARS-CoV-2 Mpro protease activity sensor

BRET-based biosensors for SARS-CoV-2 oligonucleotide detection

The need for the early detection of emerging pathogenic viruses and their newer variants has driven the urgent demand for developing point-of-care diagnostic tools. Although nucleic acid-based methods such as reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and loop-mediated isothermal amplification (LAMP) have been developed, a more facile and robust platform is still required. To address this need, as a proof-of-principle study, we engineered a prototype-the versatile, sensitive, rapid, and cost-effective bioluminescence resonance energy transfer (BRET)-based biosensor for oligonucleotide detection (BioOD). Specifically, we designed BioODs against the SARS-CoV-2 parental (Wuhan strain) and B.1.617.2 Delta variant through the conjugation of specific, fluorescently modified molecular beacons (sensor module) through a complementary oligonucleotide handle DNA functionalized with the NanoLuc (NLuc) luciferase protein such that the dissolution of the molecular beacon loop upon the binding of the viral oligonucleotide will result in a decrease in BRET efficiency and, thus, a change in the bioluminescence spectra. Following the assembly of the BioODs, we determined their kinetics response, affinity for variant-specific oligonucleotides, and specificity, and found them to be rapid and highly specific. Furthermore, the decrease in BRET efficiency of the BioODs in the presence of viral oligonucleotides can be detected as a change in color in cell phone camera images. We envisage that the BioODs developed here will find application in detecting viral infections with variant specificity in a point-of-care-testing format, thus aiding in large-scale viral infection surveillance.

A slow but steady nanoLuc: R162A mutation results in a decreased, but stable, nanoLuc activity

NanoLuc (NLuc) luciferase has found extensive application in designing a range of biological assays, including gene expression analysis, protein-protein interaction, and protein conformational changes due to its enhanced brightness and small size. However, questions related to its mechanism of interaction with the substrate, furimazine, as well as bioluminescence activity remain elusive. Here, we combined molecular dynamics (MD) simulation and mutational analysis to show that the R162A mutation results in a decreased but stable bioluminescence activity of NLuc in living cells and in vitro. Specifically, we performed multiple, all-atom, explicit solvent MD simulations of the apo and furimazine-docked (holo) NLuc structures revealing differential dynamics of the protein in the absence and presence of the ligand. Further, analysis of trajectories for hydrogen bonds (H-bonds) formed between NLuc and furimazine revealed substantial H-bond interaction between R162 and Q32 residues. Mutation of the two residues in NLuc revealed a decreased but stable activity of the R162A, but not Q32A, mutant NLuc in live cell and in vitro assays performed using lysates prepared from cells expressing the proteins and with the furimazine substrate. In addition to highlighting the role of the R162 residue in NLuc activity, we believe that the mutant NLuc will find wide application in designing in vitro assays requiring extended monitoring of NLuc bioluminescence activity. SIGNIFICANCE: Bioluminescence has been extensively utilized in developing a variety of biological and biomedical assays. In this regard, engineering of brighter bioluminescent proteins, i.e. luciferases, has played a significant role. This is acutely exemplified by the engineering of the NLuc luciferase, which is small in size and displays much enhanced bioluminescence and thermal stability compared to previously available luciferases. While enhanced bioluminescent activity is desirable in a multitude of biological and biomedical assays, it would also be useful to develop variants of the protein that display a prolonged bioluminescence activity. This is specifically relevant in designing assays that require bioluminescence for extended periods, such as in the case of biosensors designed for monitoring slow enzymatic or cellular signaling reactions, without necessitating multiple rounds of luciferase substrate addition or any specialized reagents that result in increased assay costs. In the current manuscript, we report a mutant NLuc that possesses a stable and prolonged bioluminescence activity, albeit lower than the wild-type NLuc, and envisage a wider application of the mutant NLuc in designing biosensors for monitoring slower biological and biomedical events.

Identification of a potential DNA methyltransferase (DNMT) inhibitor

DNA methyltransferases (DNMTs) play an important role in the epigenetic regulation of gene expression through the methylation of DNA. Since hypermethylation and consequent suppression of tumor suppressor genes are associated with cancer development and progression, DNA hypomethylating agents (HMAs) such as DNMT inhibitors have been proposed for cancer therapy. Two nucleoside analogues approved for the treatment of hematological cancers, decitabine and azacytidine, have poor pharmacokinetic properties, and hence there is a critical need for identifying novel HMAs. Virtual screening of a library of ∼40,000 compounds from the ZINC database, followed by molecular docking of 4,000 compounds having potential druggable properties with DNMT1, DNMT3A and DNMT3B were performed. One unique inhibitor (ZINC167686681) was identified that successfully passed through the Lipinski Rule of 5, geometry constraints as well as ADME/Tox filters and having strong binding energy for DNMTs. Further, molecular dynamics simulations of the docked complexes showed detailed structural features critical for its binding with the DNMTs and the stability of their interaction. Our study identified a compound with potential druggable properties and predicted to bind and inhibit DNMTs. Further investigations involving cellular and animal models of ZINC167686681 will help in potentially taking it into clinical trials for the treatment of cancers.Communicated by Ramaswamy H. Sarma.

Development of a bioluminescence resonance energy transfer Quenchbody sensor for the detection of organophosphorus pesticides in water bodies

Rapid and precise quantification of organophosphorus pesticides (OPPs) in environmental water bodies is crucial for evaluating ecological risks and safeguarding human health. Traditional instrumental methods are complex, time-consuming, and expensive, while enzyme-based biosensors suffer from instability and require a constant supply of substrates. Hence, there is an urgent need for a fast, simple, and sensitive biosensor for OPPs. In this study, we developed a novel non-enzymatic biosensor for the detection of methyl parathion (MP) by employing the bioluminescence resonance energy transfer (BRET) Q-body strategy. Optimizing the spacer arm and screening fluorescent dyes identified the R6G BRET MP Q-body sensor with the best performance. Key parameters affecting the sensor's detection performance were optimized by using single-factor experiments. Under optimal conditions, the detection exhibited a detection limit of 5.09 ng·mL-1 and a linear range of 16.21-848.81 ng·mL-1. The sensor's accuracy was validated using standard recovery experiments, yielding a recovery rate of 84.47 %-102.08 % with a standard deviation of 1.93 %-9.25 %. The detection results of actual water samples demonstrate that this fast, simple, and highly sensitive BRET Q-body sensor holds great promise for practical water quality monitoring.

Functional Characterization of Novel MC4R Variants Identified in Two Unrelated Patients with Morbid Obesity in Qatar

The leptin-melanocortin pathway is pivotal in appetite and energy homeostasis. Pathogenic variants in genes involved in this pathway lead to severe early-onset monogenic obesity (MO). The MC4R gene plays a central role in leptin-melanocortin signaling, and heterozygous variants in this gene are the most common cause of MO. A targeted gene panel consisting of 52 obesity-related genes was used to screen for variants associated with obesity. Variants were analyzed and filtered to identify potential disease-causing activity and validated using Sanger sequencing. We identified two novel heterozygous variants, c.253A>G p.Ser85Gly and c.802T>C p.Tyr268His, in the MC4R gene in two unrelated patients with morbid obesity and evaluated the functional impact of these variants. The impact of the variants on the MC4R gene was assessed using in silico prediction tools and molecular dynamics simulation. To further study the pathogenicity of the identified variants, GT1-7 cells were transfected with plasmid DNA encoding either wild-type or mutant MC4R variants. The effects of allelic variations in the MC4R gene on cAMP synthesis, MC4R protein level, and activation of PKA, ERB, and CREB signaling pathways in both stimulated and unstimulated ɑ-MSH paradigms were determined for their functional implications. In silico analysis suggested that the variants destabilized the MC4R structure and affected the overall dynamics of the MC4R protein, possibly leading to intracellular receptor retention. In vitro analysis of the functional impact of these variants showed a significant reduction in cell surface receptor expression and impaired extracellular ligand binding activity, leading to reduced cAMP production. Our analysis shows that the variants do not affect total protein expression; however, they are predicted to affect the post-translational localization of the MC4R protein to the cell surface and impair downstream signaling cascades such as PKA, ERK, and CREB signaling pathways. This finding might help our patients to benefit from the novel therapeutic advances for monogenic forms of obesity.

Protegrin-2, a potential inhibitor for targeting SARS-CoV-2 main protease Mpro

Background

SARS-CoV-2 variants continue to spread throughout the world and cause waves of COVID-19 infections. It is important to find effective antiviral drugs to combat SARS-CoV-2 and its variants. The main protease (Mpro) of SARS-CoV-2 is a promising therapeutic target due to its crucial role in viral replication and its conservation in all the variants. Therefore, the aim of this work was to identify an effective inhibitor of Mpro.

Methods

We studied around 200 antimicrobial peptides using in silico methods including molecular docking and allergenicity and toxicity prediction. One selected antiviral peptide was studied experimentally using a Bioluminescence Resonance Energy Transfer (BRET)-based Mpro biosensor, which reports Mpro activity through a decrease in energy transfer.

Results

Molecular docking identified one natural antimicrobial peptide, Protegrin-2, with high binding affinity and stable interactions with Mpro allosteric residues. Furthermore, free energy calculations and molecular dynamics simulation illustrated a high affinity interaction between the two. We also determined the impact of the binding of Protegrin-2 to Mpro using a BRET-based assay, showing that it inhibits the proteolytic cleavage activity of Mpro.

Conclusions

Our in silico and experimental studies identified Protegrin-2 as a potent inhibitor of Mpro that could be pursued further towards drug development against COVID-19 infection.

COVID-19Base v3: Update of the knowledgebase for drugs and biomedical entities linked to COVID-19

COVID-19 has taken a huge toll on our lives over the last 3 years. Global initiatives put forward by all stakeholders are still in place to combat this pandemic and help us learn lessons for future ones. While the vaccine rollout was not able to curb the spread of the disease for all strains, the research community is still trying to develop effective therapeutics for COVID-19. Although Paxlovid and remdesivir have been approved by the FDA against COVID-19, they are not free of side effects. Therefore, the search for a therapeutic solution with high efficacy continues in the research community. To support this effort, in this latest version (v3) of COVID-19Base, we have summarized the biomedical entities linked to COVID-19 that have been highlighted in the scientific literature after the vaccine rollout. Eight different topic-specific dictionaries, i.e., gene, miRNA, lncRNA, PDB entries, disease, alternative medicines registered under clinical trials, drugs, and the side effects of drugs, were used to build this knowledgebase. We have introduced a BLSTM-based deep-learning model to predict the drug-disease associations that outperforms the existing model for the same purpose proposed in the earlier version of COVID-19Base. For the very first time, we have incorporated disease-gene, disease-miRNA, disease-lncRNA, and drug-PDB associations covering the largest number of biomedical entities related to COVID-19. We have provided examples of and insights into different biomedical entities covered in COVID-19Base to support the research community by incorporating all of these entities under a single platform to provide evidence-based support from the literature. COVID-19Base v3 can be accessed from: https://covidbase-v3.vercel.app/. The GitHub repository for the source code and data dictionaries is available to the community from: https://github.com/91Abdullah/covidbasev3.0.

SARS-CoV-2 accessory proteins ORF7a and ORF3a use distinct mechanisms to down-regulate MHC-I surface expression

Major histocompatibility complex class I (MHC-I) molecules, which are dimers of a glycosylated polymorphic transmembrane heavy chain and the small-protein β₂-microglobulin (β₂m), bind peptides in the endoplasmic reticulum that are generated by the cytosolic turnover of cellular proteins. In virus-infected cells, these peptides may include those derived from viral proteins. Peptide-MHC-I complexes then traffic through the secretory pathway and are displayed at the cell surface where those containing viral peptides can be detected by CD8⁺ T lymphocytes that kill infected cells. Many viruses enhance their in vivo survival by encoding genes that down-regulate MHC-I expression to avoid CD8⁺ T cell recognition. Here, we report that two accessory proteins encoded by SARS-CoV-2, the causative agent of the ongoing COVID-19 pandemic, down-regulate MHC-I expression using distinct mechanisms. First, ORF3a, a viroporin, reduces the global trafficking of proteins, including MHC-I, through the secretory pathway. The second, ORF7a, interacts specifically with the MHC-I heavy chain, acting as a molecular mimic of β₂m to inhibit its association. This slows the exit of properly assembled MHC-I molecules from the endoplasmic reticulum. We demonstrate that ORF7a reduces antigen presentation by the human MHC-I allele HLA-A*02:01. Thus, both ORF3a and ORF7a act post-translationally in the secretory pathway to lower surface MHC-I expression, with ORF7a exhibiting a specific mechanism that allows immune evasion by SARS-CoV-2.

Structure-Based Virtual Screening and Functional Validation of Potential Hit Molecules Targeting the SARS-CoV-2 Main Protease

The recent global health emergency caused by the coronavirus disease 2019 (COVID-19) pandemic has taken a heavy toll, both in terms of lives and economies. Vaccines against the disease have been developed, but the efficiency of vaccination campaigns worldwide has been variable due to challenges regarding production, logistics, distribution and vaccine hesitancy. Furthermore, vaccines are less effective against new variants of the SARS-CoV-2 virus and vaccination-induced immunity fades over time. These challenges and the vaccines' ineffectiveness for the infected population necessitate improved treatment options, including the inhibition of the SARS-CoV-2 main protease (M^pro). Drug repurposing to achieve inhibition could provide an immediate solution for disease management. Here, we used structure-based virtual screening (SBVS) to identify natural products (from NP-lib) and FDA-approved drugs (from e-Drug3D-lib and Drugs-lib) which bind to the M^pro active site with high-affinity and therefore could be designated as potential inhibitors. We prioritized nine candidate inhibitors (e-Drug3D-lib: Ciclesonide, Losartan and Telmisartan; Drugs-lib: Flezelastine, Hesperidin and Niceverine; NP-lib: three natural products) and predicted their half maximum inhibitory concentration using DeepPurpose, a deep learning tool for drug-target interactions. Finally, we experimentally validated Losartan and two of the natural products as in vitro M^pro inhibitors, using a bioluminescence resonance energy transfer (BRET)-based M^pro sensor. Our study suggests that existing drugs and natural products could be explored for the treatment of COVID-19.