Novel Small-Molecule Inhibitors of the SARS-CoV-2 Spike Protein Binding to Neuropilin 1

Comprehensive analysis and immunohistochemistry localization of NRP1 expression in pancancer and normal individual tissues in relation to SARS‑CoV‑2 susceptibility

Neuropilin 1 (NRP1/CD304) is a typical membrane-bound co-receptor for vascular endothelial growth factor, semaphorin family members and viral severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, NRP1 expression levels across cancer types and the potential role of SARS-CoV-2 infection in patients with cancer are not clear. Online databases, such as The Cancer Genome Atlas database of Human Protein Atlas, Gene Expression Profiling Interactive Analysis and cBioPortal were used for the expression analysis in this study. Immunohistochemical (IHC) staining for NRP1 was performed in the tissues of patients with non-small cell carcinoma. As a result, it was found that NRP1 mRNA and protein expression levels were highest in the female reproductive tissues and the respiratory system, specifically in the nasopharynx, bronchus and fallopian tube, as well as in adipocytes, hepatic stellate cells, Sertoli cells, endothelial cells and dendritic cells. IHC showed that the NRP1 protein was mainly localized to the cytoplasm and membrane in the tissues of patients with non-small cell carcinoma, demonstrating its role in lung infection by SARS-CoV-2, due to invasion of cell membranes by the virus. Levels of NRP1 mRNA were significantly increased in lymphoid neoplasm diffuse large B-cell lymphoma, esophageal carcinoma, glioblastoma multiforme, head and neck squamous cell carcinoma, kidney renal clear cell carcinoma (KIRC), pancreatic adenocarcinoma, stomach adenocarcinoma and thymoma, and significantly decreased in cervical squamous cell carcinoma and endocervical adenocarcinoma, kidney chromophobe, lung squamous cell carcinoma, ovarian serous cystadenocarcinoma, uterine corpus endometrial carcinoma and uterine carcinosarcoma, compared with corresponding healthy tissues in pancancer, indicating roles for viral invasion in most cancer types. Moreover, low NRP1 expression was significantly associated with long overall survival (OS) time in adrenocortical carcinoma, brain lower grade glioma, stomach adenocarcinoma and uveal melanoma, but with short OS time in KIRC only. The ENST00000374867.6 (NRP1-202) isoform is most highly expressed in most cancer types and thus could be involved in tumorigenesis and SARS-CoV-2 invasion in cancer patients. NRP1 may be involved in SARS-CoV-2 invasion in patients with cancer, including those with lung cancer.

Natural Product Cordycepin (CD) Inhibition for NRP1/CD304 Expression and Possibly SARS-CoV-2 Susceptibility Prevention on Cancers

NRP1/CD304 is a typical membrane-bound co-receptor for the vascular endothelial cell growth factor (VEGF), semaphorin family members, and viral SARS-CoV-2. Cordycepin (CD) is a natural product or active gradient from traditional Chinese medicine (TCM) from Cordyceps militaris Link and Ophiocordyceps sinensis (Berk.). However, NRP1 expression regulation via CD in cancers and the potential roles and mechanisms of SARS-CoV-2 infection are not clear. In this study, online databases were analyzed, Western blotting and quantitative RT-PCR were used for NRP1 expression change via CD, molecular docking was used for NRP/CD interaction, and a syncytial formation assay was used for CD inhibition using a pseudovirus SARS-CoV-2 entry. As a result, we revealed that CD inhibits NRP1 expressed in cancer cells and prevents viral syncytial formation in 293T-hACE2 cells, implying the therapeutic potential for both anti-cancer and anti-viruses, including anti-SARS-CoV-2. We further found significant associations between NRP1 expressions and the tumor-immune response in immune lymphocytes, chemokines, receptors, immunostimulators, immune inhibitors, and major histocompatibility complexes in most cancer types, implying NRP1's roles in both anti-cancer and anti-SARS-CoV-2 entry likely via immunotherapy. Importantly, CD also downregulated the expression of NRP1 from lymphocytes in mice and downregulated the expression of A2AR from the lung cancer cell line H1975 when treated with CD, implying the NRP1 mechanism probably through immuno-response pathways. Thus, CD may be a therapeutic component for anti-cancer and anti-viral diseases, including COVID-19, by targeting NRP1 at least.

Computational Screening of Neuropilin-1 Unveils Novel Potential Anti-SARS-CoV-2 Therapeutics

Neuropilin 1 (NRP-1) inhibition has shown promise in reducing the infectivity of severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) and preventing the virus entry into nerve tissues, thereby mitigating neurological symptoms in COVID-19 patients. In this study, we employed virtual screening, including molecular docking, Molecular Dynamics (MD) simulation, and Molecular Mechanics-Poisson Boltzmann Surface Area (MM-PBSA) calculations, to identify potential NRP-1 inhibitors. From a compendium of 1930 drug-like natural compounds, we identified five potential leads: CNP0435132, CNP0435311, CNP0424372, CNP0429647, and CNP0427474, displaying robust binding energies of -8.2, -8.1, -10.7, -8.2, and -8.2 kcal/mol, respectively. These compounds demonstrated interactions with critical residues Tyr297, Trp301, Thr316, Asp320, Ser346, Thr349, and Tyr353 located within the b1 subdomain of NRP-1. Furthermore, MD simulations and MM-PBSA calculations affirmed the stability of the complexes formed, with average root mean square deviation, radius of gyration, and solvent accessible surface area values of 0.118 nm, 1.516 nm, and 88.667 nm2 , respectively. Notably, these lead compounds were estimated to penetrate the blood-brain barrier and displayed antiviral properties, with Pa values ranging from 0.414 to 0.779. The antagonistic effects of these lead compounds merit further investigation, as they hold the potential to serve as foundational scaffolds for the development of innovative therapeutics aimed at reducing the neuroinfectivity of SARS-CoV-2.

Effectiveness, Tolerability and Prescribing Choice of Antiviral Molecules Molnupiravir, Remdesivir and Nirmatrelvir/r: A Real-World Comparison in the First Ten Months of Use

In 2022, three antiviral drugs-molnupiravir, remdesivir and nirmatrelvir/ritonavir-were introduced for treatment of mild-to-moderate COVID-19 in high-risk patients. The aim of this study is the evaluation of their effectiveness and tolerability in a real-life setting. A single-center observational study was set up, with the involvement of 1118 patients, with complete follow-up data, treated between the 5th of January and the 3rd of October 2022 at Santa Maria Goretti's hospital in Latina, Central Italy. A univariable and a multivariable analysis were performed on clinical and demographic data and composite outcome, the persistence of symptoms at 30 days and time to negativization, respectively. The three antivirals showed a similar effectiveness in containing the progression of the infection to severe COVID-19 and a good tolerability in the absence of serious adverse effects. Persistence of symptoms after 30 days was more common in females than males and less common in patients treated with molnupiravir and nirmatrelvir/r. The availability of different antiviral molecules is a strong tool and, if correctly prescribed, they can have a significant role in changing the natural history of infection for frail persons, in which vaccination could be not sufficient for the prevention of severe COVID-19.

The Envelope (E) Protein of SARS-CoV-2 as a Pharmacological Target

The COVID-19 pandemic caused by the SARS-CoV-2 virus is still a global health concern. Several spike (S) protein-based vaccines have been developed that efficiently protect the human population against severe forms of COVID-19. However, some SARS-CoV-2 variants of concern (VOCs) have emerged that evade the protective effect of vaccine-induced antibodies. Therefore, efficient and specific antiviral treatments to control COVID-19 are indispensable. To date, two drugs have been approved for mild COVID-19 treatment; nevertheless, more drugs, preferably broad-spectrum and ready-to-use therapeutic agents for new pandemics, are needed. Here, I discuss the PDZ-dependent protein-protein interactions of the viral E protein with host proteins as attractive alternatives for the development of antivirals against coronavirus.

Autochthonous Peruvian Natural Plants as Potential SARS-CoV-2 Mpro Main Protease Inhibitors

Over 750 million cases of COVID-19, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), have been reported since the onset of the global outbreak. The need for effective treatments has spurred intensive research for therapeutic agents based on pharmaceutical repositioning or natural products. In light of prior studies asserting the bioactivity of natural compounds of the autochthonous Peruvian flora, the present study focuses on the identification SARS-CoV-2 M^pro main protease dimer inhibitors. To this end, a target-based virtual screening was performed over a representative set of Peruvian flora-derived natural compounds. The best poses obtained from the ensemble molecular docking process were selected. These structures were subjected to extensive molecular dynamics steps for the computation of binding free energies along the trajectory and evaluation of the stability of the complexes. The compounds exhibiting the best free energy behaviors were selected for in vitro testing, confirming the inhibitory activity of Hyperoside against M^pro, with a K_i value lower than 20 µM, presumably through allosteric modulation.

SARS-CoV-2 Receptors and Their Involvement in Cell Infection

The new coronavirus infection (COVID-19) pandemic caused by SARS-CoV-2 has many times surpassed the epidemics caused by SARS-CoV and MERS-CoV. The reason for this was the presence of sites in the protein sequence of SARS-CoV-2 that provide interaction with a broader range of receptor proteins on the host cell surface. In this review, we consider both already known receptors common to SARS-CoV and SARS-CoV-2 and new receptors specific to SARS-CoV-2.

Folic Acid and Leucovorin Have Potential to Prevent SARS-CoV-2-Virus Internalization by Interacting with S-Glycoprotein/Neuropilin-1 Receptor Complex

The interaction of the SARS-CoV-2 spike (S) glycoprotein receptor-binding domain with the host-cell ACE2 receptor is a well-known step in virus infection. Neuropilin-1 (NRP-1) is another host factor involved in virus internalization. The interaction between S-glycoprotein and NRP-1 has been identified as a potential COVID-19 treatment target. Herein, the effectiveness of folic acid and leucovorin in preventing contact between S-glycoprotein and NRP-1 receptors was investigated using in silico studies and then confirmed in vitro. The results of a molecular docking study showed that leucovorin and folic acid had lower binding energies than EG01377, a well-known NRP-1 inhibitor, and lopinavir. Two hydrogen bonds with Asp 320 and Asn 300 residues stabilized the leucovorin, while interactions with Gly 318, Thr 349, and Tyr 353 residues stabilized the folic acid. The molecular dynamic simulation revealed that the folic acid and leucovorin created very stable complexes with the NRP-1. The in vitro studies showed that the leucovorin was the most active inhibitor of the S1-glycoprotein/NRP-1 complex formation, with an IC₇₅ value of 185.95 µg/mL. The results of this study suggest that folic acid and leucovorin could be considered as potential inhibitors of the S-glycoprotein/NRP-1 complex and, thus, could prevent the SARS-CoV-2 virus' entry into host cells.

Lessons Learnt from COVID-19: Computational Strategies for Facing Present and Future Pandemics

Since its outbreak in December 2019, the COVID-19 pandemic has caused the death of more than 6.5 million people around the world. The high transmissibility of its causative agent, the SARS-CoV-2 virus, coupled with its potentially lethal outcome, provoked a profound global economic and social crisis. The urgency of finding suitable pharmacological tools to tame the pandemic shed light on the ever-increasing importance of computer simulations in rationalizing and speeding up the design of new drugs, further stressing the need for developing quick and reliable methods to identify novel active molecules and characterize their mechanism of action. In the present work, we aim at providing the reader with a general overview of the COVID-19 pandemic, discussing the hallmarks in its management, from the initial attempts at drug repurposing to the commercialization of Paxlovid, the first orally available COVID-19 drug. Furthermore, we analyze and discuss the role of computer-aided drug discovery (CADD) techniques, especially those that fall in the structure-based drug design (SBDD) category, in facing present and future pandemics, by showcasing several successful examples of drug discovery campaigns where commonly used methods such as docking and molecular dynamics have been employed in the rational design of effective therapeutic entities against COVID-19.

Towards a transactional medicine approach to combating global emerging pathogens: the case of COVID-19

When the COVID-19 pandemic struck and China reported the first case to the World Health Organization in December 2019, there was no evidence-based treatment to combat it. With the catastrophic situation that followed, materialised by a considerable number of deaths, researchers, doctors, traditional healers, and governments of all nations committed themselves to find therapeutic solutions, including preventive and curative. There are effective treatments offered both by modern medicine and traditional medicine for COVID-19 today. However, other therapeutic proposals have not been approved due to the lack of effectiveness and scientific rigour during their development process. Proponents of modern medicine prefer biomedical therapies while in some countries, traditional treatments are used regularly because of their availability, affordability and satisfaction they bring to the population. In this paper, we propose a transactional medicine approach where the interaction between traditional and modern medicine produces a change. With this approach, the promoters of traditional medicine and those of modern medicine will be able to acquire knowledge through the experience produced by their encounters. Transactional medicine aims to be a model for decolonising medicine and recognising the value of both traditional and modern medicine in the fight against COVID-19 and other global emerging pathogens.

Ganoderma lucidum polysaccharides ameliorate lipopolysaccharide-induced acute pneumonia via inhibiting NRP1-mediated inflammation

CONTEXT

Ganoderma lucidum polysaccharides (GLP), from Ganoderma lucidum (Leyss. ex Fr.) Karst. (Ganodermataceae), are reported to have anti-inflammatory effects, including anti-neuroinflammation and anti-colitis. Nevertheless, the role of GLP in acute pneumonia is unknown.

OBJECTIVE

To explore the protective role of GLP against LPS-induced acute pneumonia and investigate possible mechanisms.

MATERIALS AND METHODS

GLP were extracted and used for high-performance liquid chromatography (HPLC) analysis after acid hydrolysis and PMP derivatization. Sixty C57BL/6N male mice were randomly divided into six groups: Sham, Model, LPS + GLP (25, 50 and 100 mg/kg/d administered intragastrically for two weeks) and LPS + dexamethasone (6 mg/kg/d injected intraperitoneally for one week). Acute pneumonia mouse models were established by intratracheal injection of LPS. Haematoxylin and eosin (H&E) staining was examined to evaluate lung lesions. ELISA and quantitative real-time PCR were employed to assess inflammatory factors expression. Western blots were carried out to measure Neuropilin-1 expression and proteins related to apoptosis and autophagy.

RESULTS

GLP suppressed inflammatory cell infiltration. In BALF, cell counts were 1.1 × 10⁶ (model) and 7.1 × 10⁵ (100 mg/kg). Release of GM-CSF and IL-6 was reduced with GLP (25, 50 and 100 mg/kg) treatment. The expression of genes IL-1β, IL-6, TNF-α and Saa3 was reduced. GLP treatment also suppressed the activation of Neuropilin-1 (NRP1), upregulated the levels of Bcl2/Bax and LC3 and led to downregulation of the ratio C-Caspase 3/Caspase 3 and P62 expression.

DISCUSSION AND CONCLUSIONS

GLP could protect against LPS-induced acute pneumonia through multiple mechanisms: blocking the infiltration of inflammatory cells, inhibiting cytokine secretion, suppressing NRP1 activation and regulating pneumonocyte apoptosis and autophagy.

Non-covalent cyclic peptides simultaneously targeting Mpro and NRP1 are highly effective against Omicron BA.2.75

Available vaccine-based immunity may at high risk of being evaded due to substantial mutations in the variant Omicron. The main protease (Mpro) of SARS-CoV-2 and human neuropilin-1 (NRP1), two less mutable proteins, have been reported to be crucial for SARS-CoV-2 replication and entry into host cells, respectively. Their dual blockade may avoid vaccine failure caused by continuous mutations of the SARS-CoV-2 genome and exert synergistic antiviral efficacy. Herein, four cyclic peptides non-covalently targeting both Mpro and NRP1 were identified using virtual screening. Among them, MN-2 showed highly potent affinity to Mpro (K_d = 18.2 ± 1.9 nM) and NRP1 (K_d = 12.3 ± 1.2 nM), which was about 3,478-fold and 74-fold stronger than that of the positive inhibitors Peptide-21 and EG3287. Furthermore, MN-2 exhibited significant inhibitory activity against Mpro and remarkable anti-infective activity against the pseudotyped variant Omicron BA.2.75 without obvious cytotoxicity. These data demonstrated that MN-2, a novel non-covalent cyclic peptide, is a promising agent against Omicron BA.2.75.

Characterization of the SARS-CoV-2 co-receptor NRP1 expression profiles in healthy people and cancer patients: Implication for susceptibility to COVID-19 disease and potential therapeutic strategy

Neuropilin-1 (NRP1) is a transmembrane protein involved in many physiological and pathological processes, and it functions as a co-receptor to facilitate the entry of SARS-CoV-2 into host cells. Therefore, it is critical to predict the susceptibility to SARS-CoV-2 and prognosis after infection among healthy people and cancer patients based on expression of NRP1. In the current study, we analyzed the conservation and isoform of NRP1 using public databases. NRP1 expression landscape in healthy people, COVID-19 patients, and cancer patients at both bulk and single-cell RNA-seq level was also depicted. We also analyzed the relationship between tissue-specific NRP1 expression and overall survival (OS), as well as tumor immune environment at a pan-cancer level, providing a comprehensive insight into the relationship between the vulnerability to SARS-CoV-2 infection and tumorigenesis. In conclusion, we identified NRP1 as a potential biomarker in predicting susceptibility to SARS-CoV-2 infection among healthy people and cancer patients.

Neuropilin (NRPs) Related Pathological Conditions and Their Modulators

Neuropilin 1 (NRP1) represents one of the two homologous neuropilins (NRP, splice variants of neuropilin 2 are the other) found in all vertebrates. It forms a transmembrane glycoprotein distributed in many human body tissues as a (co)receptor for a variety of different ligands. In addition to its physiological role, it is also associated with various pathological conditions. Recently, NRP1 has been discovered as a coreceptor for the SARS-CoV-2 viral entry, along with ACE2, and has thus become one of the COVID-19 research foci. However, in addition to COVID-19, the current review also summarises its other pathological roles and its involvement in clinical diseases like cancer and neuropathic pain. We also discuss the diversity of native NRP ligands and perform a joint analysis. Last but not least, we review the therapeutic roles of NRP1 and introduce a series of NRP1 modulators, which are typical peptidomimetics or other small molecule antagonists, to provide the medicinal chemistry community with a state-of-the-art overview of neuropilin modulator design and NRP1 druggability assessment.

Identification of Potential Insect Growth Inhibitor against Aedes aegypti: A Bioinformatics Approach

Aedes aegypti is the main vector that transmits viral diseases such as dengue, hemorrhagic dengue, urban yellow fever, zika, and chikungunya. Worldwide, many cases of dengue have been reported in recent years, showing significant growth. The best way to manage diseases transmitted by Aedes aegypti is to control the vector with insecticides, which have already been shown to be toxic to humans; moreover, insects have developed resistance. Thus, the development of new insecticides is considered an emergency. One way to achieve this goal is to apply computational methods based on ligands and target information. In this study, sixteen compounds with acceptable insecticidal activities, with 100% larvicidal activity at low concentrations (2.0 to 0.001 mg·L−1), were selected from the literature. These compounds were used to build up and validate pharmacophore models. Pharmacophore model 6 (AUC = 0.78; BEDROC = 0.6) was used to filter 4793 compounds from the subset of lead-like compounds from the ZINC database; 4142 compounds (dG < 0 kcal/mol) were then aligned to the active site of the juvenile hormone receptor Aedes aegypti (PDB: 5V13), 2240 compounds (LE < −0.40 kcal/mol) were prioritized for molecular docking from the construction of a chitin deacetylase model of Aedes aegypti by the homology modeling of the Bombyx mori species (PDB: 5ZNT), which aligned 1959 compounds (dG < 0 kcal/mol), and 20 compounds (LE < −0.4 kcal/mol) were predicted for pharmacokinetic and toxicological prediction in silico (Preadmet, SwissADMET, and eMolTox programs). Finally, the theoretical routes of compounds M01, M02, M03, M04, and M05 were proposed. Compounds M01−M05 were selected, showing significant differences in pharmacokinetic and toxicological parameters in relation to positive controls and interaction with catalytic residues among key protein sites reported in the literature. For this reason, the molecules investigated here are dual inhibitors of the enzymes chitin synthase and juvenile hormonal protein from insects and humans, characterizing them as potential insecticides against the Aedes aegypti mosquito.

Multi-Level Biological Network Analysis and Drug Repurposing Based on Leukocyte Transcriptomics in Severe COVID-19: In Silico Systems Biology to Precision Medicine

The coronavirus disease 2019 (COVID-19) pandemic causes many morbidity and mortality cases. Despite several developed vaccines and antiviral therapies, some patients experience severe conditions that need intensive care units (ICU); therefore, precision medicine is necessary to predict and treat these patients using novel biomarkers and targeted drugs. In this study, we proposed a multi-level biological network analysis framework to identify key genes via protein–protein interaction (PPI) network analysis as well as survival analysis based on differentially expressed genes (DEGs) in leukocyte transcriptomic profiles, discover novel biomarkers using microRNAs (miRNA) from regulatory network analysis, and provide candidate drugs targeting the key genes using drug–gene interaction network and structural analysis. The results show that upregulated DEGs were mainly enriched in cell division, cell cycle, and innate immune signaling pathways. Downregulated DEGs were primarily concentrated in the cellular response to stress, lysosome, glycosaminoglycan catabolic process, and mature B cell differentiation. Regulatory network analysis revealed that hsa-miR-6792-5p, hsa-let-7b-5p, hsa-miR-34a-5p, hsa-miR-92a-3p, and hsa-miR-146a-5p were predicted biomarkers. CDC25A, GUSB, MYBL2, and SDAD1 were identified as key genes in severe COVID-19. In addition, drug repurposing from drug–gene and drug–protein database searching and molecular docking showed that camptothecin and doxorubicin were candidate drugs interacting with the key genes. In conclusion, multi-level systems biology analysis plays an important role in precision medicine by finding novel biomarkers and targeted drugs based on key gene identification.

Immune-Related Protein Interaction Network in Severe COVID-19 Patients toward the Identification of Key Proteins and Drug Repurposing

Coronavirus disease 2019 (COVID-19) is still an active global public health issue. Although vaccines and therapeutic options are available, some patients experience severe conditions and need critical care support. Hence, identifying key genes or proteins involved in immune-related severe COVID-19 is necessary to find or develop the targeted therapies. This study proposed a novel construction of an immune-related protein interaction network (IPIN) in severe cases with the use of a network diffusion technique on a human interactome network and transcriptomic data. Enrichment analysis revealed that the IPIN was mainly associated with antiviral, innate immune, apoptosis, cell division, and cell cycle regulation signaling pathways. Twenty-three proteins were identified as key proteins to find associated drugs. Finally, poly (I:C), mitomycin C, decitabine, gemcitabine, hydroxyurea, tamoxifen, and curcumin were the potential drugs interacting with the key proteins to heal severe COVID-19. In conclusion, IPIN can be a good representative network for the immune system that integrates the protein interaction network and transcriptomic data. Thus, the key proteins and target drugs in IPIN help to find a new treatment with the use of existing drugs to treat the disease apart from vaccination and conventional antiviral therapy.

Graph Convolutional Network-Based Screening Strategy for Rapid Identification of SARS-CoV-2 Cell-Entry Inhibitors

The cell entry of SARS-CoV-2 has emerged as an attractive drug development target. We previously reported that the entry of SARS-CoV-2 depends on the cell surface heparan sulfate proteoglycan (HSPG) and the cortex actin, which can be targeted by therapeutic agents identified by conventional drug repurposing screens. However, this drug identification strategy requires laborious library screening, which is time consuming, and often limited number of compounds can be screened. As an alternative approach, we developed and trained a graph convolutional network (GCN)-based classification model using information extracted from experimentally identified HSPG and actin inhibitors. This method allowed us to virtually screen 170,000 compounds, resulting in ∼2000 potential hits. A hit confirmation assay with the uptake of a fluorescently labeled HSPG cargo further shortlisted 256 active compounds. Among them, 16 compounds had modest to strong inhibitory activities against the entry of SARS-CoV-2 pseudotyped particles into Vero E6 cells. These results establish a GCN-based virtual screen workflow for rapid identification of new small molecule inhibitors against validated drug targets.