Discovery of novel TMPRSS2 inhibitors for COVID-19 using in silico fragment-based drug design, molecular docking, molecular dynamics, and quantum mechanics studies

Unveiling the potential of phytochemicals to inhibit nuclear receptor binding SET domain protein 2 for cancer: Pharmacophore screening, molecular docking, ADME properties, and molecular dynamics simulation investigations

Nuclear receptor binding SET domain protein 2 (NSD2) significantly contributes to the development of cancer, making it a promising target for cancer drug discovery. This research explores natural compounds as potential selective inhibitors for NSD2 in cancer treatment. Employing a comprehensive in silico approach, the study utilized pharmacophore modeling, molecular docking, pharmacokinetic profiling, and molecular dynamics simulations. An e-pharmacophore model-based screening using the first selective and potent ligand bound to NSD2 identified 49,248 natural compounds from the SuperNatural 3.0 database (containing 449,008 molecules) with acceptable alignment with the developed pharmacophore hypotheses. Subsequently, molecular docking was executed to assess the standout compounds which led to the selection of ten candidates that surpassed the reference inhibitor in accordance w the binding affinity expressed as a G score. Ligand-residue interaction analyses of the top three hits (SN0450102, SN0410255, and SN0142336) revealed diverse crucial interactions with the NSD2 active site, including hydrogen bonds, pi-pi stacking, and hydrophobic contacts with key amino acid residues in the NSD2-PWWP1 domain. Pharmacokinetic profiling confirmed the drug-likability for the refined hits, indicating good cellular permeability and minimal blood-brain barrier penetration. Molecular dynamics simulations for 200 nanoseconds affirmed the stability of protein-ligand complexes, with minimal fluctuations in root mean square deviation and root mean square fluctuation analyses. Overall, this study identified promising natural compounds as potential pharmaceutical agents in the treatment of NSD2-associated cancers.

Integrating Artificial Intelligence for Drug Discovery in the Context of Revolutionizing Drug Delivery

Drug development is expensive, time-consuming, and has a high failure rate. In recent years, artificial intelligence (AI) has emerged as a transformative tool in drug discovery, offering innovative solutions to complex challenges in the pharmaceutical industry. This manuscript covers the multifaceted role of AI in drug discovery, encompassing AI-assisted drug delivery design, the discovery of new drugs, and the development of novel AI techniques. We explore various AI methodologies, including machine learning and deep learning, and their applications in target identification, virtual screening, and drug design. This paper also discusses the historical development of AI in medicine, emphasizing its profound impact on healthcare. Furthermore, it addresses AI's role in the repositioning of existing drugs and the identification of drug combinations, underscoring its potential in revolutionizing drug delivery systems. The manuscript provides a comprehensive overview of the AI programs and platforms currently used in drug discovery, illustrating the technological advancements and future directions of this field. This study not only presents the current state of AI in drug discovery but also anticipates its future trajectory, highlighting the challenges and opportunities that lie ahead.

DON/DRP-104 as potent serine protease inhibitors implicated in SARS-CoV-2 infection: Comparative binding modes with human TMPRSS2 and novel therapeutic approach

Human transmembrane serine protease 2 (TMPRSS2) is an important member of the type 2 transmembrane serine protease (TTSP) family with significant therapeutic markings. The search for potent TMPRSS2 inhibitors against severe acute respiratory syndrome coronavirus 2 infection with favorable tissue specificity and off-site toxicity profiles remains limited. Therefore, probing the anti-TMPRSS2 potential of enhanced drug delivery systems, such as nanotechnology and prodrug systems, has become compelling. We report the first in silico study of TMPRSS2 against a prodrug, [isopropyl(S)-2-((S)-2-acetamido-3-(1H-indol-3-yl)-propanamido)-6-diazo-5-oxo-hexanoate] also known as DRP-104 synthesized from 6-Diazo-5-oxo-l-norleucine (DON). We performed comparative studies on DON and DRP-104 against a clinically potent TMPRSS2 inhibitor, nafamostat, and a standard serine protease inhibitor, 4-(2-Aminoethyl) benzenesulfonyl fluoride (AEBSF) against TMPRSS2 and found improved TMPRSS2 inhibition through synergistic binding of the S1/S1' subdomains. Both DON and DRP-104 had better thermodynamic profiles than AEBSF and nafamostat. DON was found to confer structural stability with strong positive correlated inter-residue motions, whereas DRP-104 was found to confer kinetic stability with restricted residue displacements and reduced loop flexibility. Interestingly, the Scavenger Receptor Cysteine-Rich (SRCR) domain of TMPRSS2 may be involved in its inhibition mechanics. Two previously unidentified loops, designated X (270-275) and Y (293-296) underwent minimal and major structural transitions, respectively. In addition, residues 273-277 consistently transitioned to a turn conformation in all ligated systems, whereas unique transitions were identified for other transitioning residue groups in each TMPRSS2-inhibitor complex. Intriguingly, while both DON and DRP-104 showed similar loop transition patterns, DRP-104 preserved loop structural integrity. As evident from our systematic comparative study using experimentally/clinically validated inhibitors, DRP-104 may serve as a potent and novel TMPRSS2 inhibitor and warrants further clinical investigation.

Integrating computational methods guided the discovery of phytochemicals as potential Pin1 inhibitors for cancer: pharmacophore modeling, molecular docking, MM-GBSA calculations and molecular dynamics studies

Pin1 is a pivotal player in interactions with a diverse array of phosphorylated proteins closely linked to critical processes such as carcinogenesis and tumor suppression. Its axial role in cancer initiation and progression, coupled with its overexpression and activation in various cancers render it a potential candidate for the development of targeted therapeutics. While several known Pin1 inhibitors possess favorable enzymatic profiles, their cellular efficacy often falls short. Consequently, the pursuit of novel Pin1 inhibitors has gained considerable attention in the field of medicinal chemistry. In this study, we employed the Phase tool from Schrödinger to construct a structure-based pharmacophore model. Subsequently, 449,008 natural products (NPs) from the SN3 database underwent screening to identify compounds sharing pharmacophoric features with the native ligand. This resulted in 650 compounds, which then underwent molecular docking and binding free energy calculations. Among them, SN0021307, SN0449787 and SN0079231 showed better docking scores with values of -9.891, -7.579 and -7.097 kcal/mol, respectively than the reference compound (-6.064 kcal/mol). Also, SN0021307, SN0449787 and SN0079231 exhibited lower free binding energies (-57.12, -49.81 and -46.05 kcal/mol, respectively) than the reference ligand (-37.75 kcal/mol). Based on these studies, SN0021307, SN0449787, and SN0079231 showed better binding affinity that the reference compound. Further the validation of these findings, molecular dynamics simulations confirmed the stability of the ligand-receptor complex for 100 ns with RMSD ranging from 0.6 to 1.8 Å. Based on these promising results, these three phytochemicals emerge as promising lead compounds warranting comprehensive biological screening in future investigations. These compounds hold great potential for further exploration regarding their efficacy and safety as Pin1 inhibitors, which could usher in new avenues for combating cancer.

After the Hurricane: Anti-COVID-19 Drugs Development, Molecular Mechanisms of Action and Future Perspectives

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is a new coronavirus in the Coronaviridae family. The COVID-19 pandemic, caused by SARS-CoV-2, has undoubtedly been the largest crisis of the twenty-first century, resulting in over 6.8 million deaths and 686 million confirmed cases, creating a global public health issue. Hundreds of notable articles have been published since the onset of this pandemic to justify the cause of viral spread, viable preventive measures, and future therapeutic approaches. As a result, this review was developed to provide a summary of the current anti-COVID-19 drugs, as well as their timeline, molecular mode of action, and efficacy. It also sheds light on potential future treatment options. Several medications, notably hydroxychloroquine and lopinavir/ritonavir, were initially claimed to be effective in the treatment of SARS-CoV-2 but eventually demonstrated inadequate activity, and the Food and Drug Administration (FDA) withdrew hydroxychloroquine. Clinical trials and investigations, on the other hand, have demonstrated the efficacy of remdesivir, convalescent plasma, and monoclonal antibodies, 6-Thioguanine, hepatitis C protease inhibitors, and molnupiravir. Other therapeutics, including inhaled medicines, flavonoids, and aptamers, could pave the way for the creation of novel anti-COVID-19 therapies. As future pandemics are unavoidable, this article urges immediate action and extensive research efforts to develop potent specialized anti-COVID-19 medications.

Repurposing immune boosting and anti-viral efficacy of Parkia bioactive entities as multi-target directed therapeutic approach for SARS-CoV-2: exploration of lead drugs by drug likeness, molecular docking and molecular dynamics simulation methods

The COVID-19 pandemic has caused adverse health (severe respiratory, enteric and systemic infections) and environmental impacts that have threatened public health and the economy worldwide. Drug repurposing and small molecule multi-target directed herbal medicine therapeutic approaches are the most appropriate exploration strategies for SARS-CoV-2 drug discovery. This study identified potential multi-target-directed Parkia bioactive entities against SARS-CoV-2 receptors (S-protein, ACE2, TMPRSS2, RBD/ACE2, RdRp, MPro, and PLPro) using ADMET, drug-likeness, molecular docking (AutoDock, FireDock and HDOCK), molecular dynamics simulation and MM-PBSA tools. One thousand Parkia bioactive entities were screened out by virtual screening and forty-five bioactive phytomolecules were selected based on favorable binding affinity and acceptable pharmacokinetic and pharmacodynamics properties. The binding affinity values of Parkia phyto-ligands (AutoDock: -6.00--10.40 kcal/mol; FireDock: -31.00--62.02 kcal/mol; and HDOCK: -150.0--294.93 kcal/mol) were observed to be higher than the reference antiviral drugs (AutoDock: -5.90--9.10 kcal/mol; FireDock: -35.64--59.35 kcal/mol; and HDOCK: -132.82--211.87 kcal/mol), suggesting a potent modulatory action of Parkia bioactive entities against the SARS-CoV-2. Didymin, rutin, epigallocatechin gallate, epicatechin-3-0-gallate, hyperin, ursolic acid, lupeol, stigmasta-5,24(28)-diene-3-ol, ellagic acid, apigenin, stigmasterol, and campesterol strongly bound with the multiple targets of the SARS-CoV-2 receptors, inhibiting viral entry, attachment, binding, replication, transcription, maturation, packaging and spread. Furthermore, ACE2, TMPRSS2, and MPro receptors possess significant molecular dynamic properties, including stability, compactness, flexibility and total binding energy. Residues GLU-589, and LEU-95 of ACE2, GLN-350, HIS-186, and ASP-257 of TMPRSS2, and GLU-14, MET-49, and GLN-189 of MPro receptors contributed to the formation of hydrogen bonds and binding interactions, playing vital roles in inhibiting the activity of the receptors. Promising results were achieved by developing multi-targeted antiviral Parkia bioactive entities as lead and prospective candidates under a small molecule strategy against SARS-CoV-2 pathogenesis. The antiviral activity of Parkia bioactive entities needs to be further validated by pre-clinical and clinical trials.

Molecular Dynamics as a Tool for Virtual Ligand Screening

Rational drug design is essential for new drugs to emerge, especially when the structure of a target protein or nucleic acid is known. To that purpose, high-throughput virtual ligand screening campaigns aim at discovering computationally new binding molecules or fragments to modulate particular biomolecular interactions or biological activities, related to a disease process. The structure-based virtual ligand screening process primarily relies on docking methods which allow predicting the binding of a molecule to a biological target structure with a correct conformation and the best possible affinity. The docking method itself is not sufficient as it suffers from several and crucial limitations (lack of full protein flexibility information, no solvation and ion effects, poor scoring functions, and unreliable molecular affinity estimation).At the interface of computer techniques and drug discovery, molecular dynamics (MD) allows introducing protein flexibility before or after a docking protocol, refining the structure of protein-drug complexes in the presence of water, ions, and even in membrane-like environments, describing more precisely the temporal evolution of the biological complex and ranking these complexes with more accurate binding energy calculations. In this chapter, we describe the up-to-date MD, which plays the role of supporting tools in the virtual ligand screening (VS) process.Without a doubt, using docking in combination with MD is an attractive approach in structure-based drug discovery protocols nowadays. It has proved its efficiency through many examples in the literature and is a powerful method to significantly reduce the amount of required wet experimentations (Tarcsay et al, J Chem Inf Model 53:2990-2999, 2013; Barakat et al, PLoS One 7:e51329, 2012; De Vivo et al, J Med Chem 59:4035-4061, 2016; Durrant, McCammon, BMC Biol 9:71-79, 2011; Galeazzi, Curr Comput Aided Drug Des 5:225-240, 2009; Hospital et al, Adv Appl Bioinforma Chem 8:37-47, 2015; Jiang et al, Molecules 20:12769-12786, 2015; Kundu et al, J Mol Graph Model 61:160-174, 2015; Mirza et al, J Mol Graph Model 66:99-107, 2016; Moroy et al, Future Med Chem 7:2317-2331, 2015; Naresh et al, J Mol Graph Model 61:272-280, 2015; Nichols et al, J Chem Inf Model 51:1439-1446, 2011; Nichols et al, Methods Mol Biol 819:93-103, 2012; Okimoto et al, PLoS Comput Biol 5:e1000528, 2009; Rodriguez-Bussey et al, Biopolymers 105:35-42, 2016; Sliwoski et al, Pharmacol Rev 66:334-395, 2014).

Design of new Mcl-1 inhibitors for cancer using fragments hybridization, molecular docking, and molecular dynamics studies

Apoptosis is a critical process that regulates cell survival and death and plays an essential role in cancer development. The Bcl-2 protein family, including myeloid leukemia 1 (Mcl-1), is a key regulator of the intrinsic apoptosis pathway, and its overexpression in many human cancers has prompted efforts to develop Mcl-1 inhibitors as potential anticancer agents. In this study, we aimed to design new Mcl-1 inhibitors using various computational techniques. First, we used the Mcl-1 receptor-ligand complex to build an e-pharmacophore hypothesis and screened a library of 567,000 fragments from the Enamine database. We obtained 410 fragments and used them to design 92,384 novel compounds, which we then docked into the Mcl-1 binding cavity using HTVS, SP, and XP docking modes of Glide. To assess their suitability as drug candidates, we conducted MM-GBSA calculations and ADME prediction, leading to the identification of 10 compounds with excellent binding affinity and favorable pharmacokinetic properties. To further investigate the interaction strength, we performed molecular dynamics simulations on the top three Mcl-1 receptor-ligand complexes to study their interaction stability. Overall, our findings suggest that these compounds have promising potential as anticancer agents, pending further experimental validation such as Mcl-1 apoptosis Assay. By combining experimental methods with various in silico approaches, these techniques prove to be invaluable for identifying novel drug candidates with distinct therapeutic applications using fragment-based drug design. This methodology has the potential to expedite the drug discovery process while also reducing its costs.Communicated by Ramaswamy H. Sarma.

Targeting the omicron variant of SARS-CoV-2 with phytochemicals from Saudi medicinal plants: molecular docking combined with molecular dynamics investigations

The new health crises caused by SARS-CoV-2 have resulted in millions of deaths worldwide. First discovered in November 2021, the omicron variant is more transmissible and is able to evade the immune system better than other previously identified SARS-CoV-2 variants, leading to a spike in cases. Great efforts have been made to discover inhibitors against SARS-CoV-2. Main protease (Mpro) inhibitors are considered promising anti-SARS-CoV-2 agents. The U.S. FDA has issued an Emergency Use Authorization for ritonavir-boosted nirmatrelvir. Nirmatrelvir is the first orally bioavailable inhibitor of SARS-CoV-2 Mpro. There is an urgent need to monitor the mutations and solve the problem of resistance, especially omicron Mpro, which contains one mutation - P132H. In the present study, 132,57 phytochemicals from 80 medicinal plants grown in Saudi Arabia were docked into the active site of Mpro omicron variant. Free binding energies were also calculated. This led to the discovery of five phytochemicals that showed better docking scores than the bound ligand nirmatrelvir. In addition, these molecules exhibited favorable free binding energies. The stability of compounds 1-5 with the protein was studied using molecular dynamics (MD) simulations. These compounds showed acceptable ADMET properties. The results were compared with the wild type. These candidates could be envisioned as new hits against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Evaluation interaction of graphene oxide with heparin for antiviral blockade: a study of ab initio simulations, molecular docking, and experimental analysis

CONTEXT

Heparin, one of the drugs reused in studies with antiviral activity, was chosen to investigate a possible blockade of the SARS-CoV-2 spike protein for viral entry through computational simulations and experimental analysis. Heparin was associated to graphene oxide to increase in the binding affinity in biological system. First, the electronic and chemical interaction between the molecules was analyzed through ab initio simulations. Later, we evaluate the biological compatibility of the nanosystems, in the target of the spike protein, through molecular docking. The results show that graphene oxide interacts with the heparin with an increase in the affinity energy with the spike protein, indicating a possible increment in the antiviral activity. Experimental analysis of synthesis and morphology of the nanostructures were carried out, indicating heparin absorption by graphene oxide, confirming the results of the first principle simulations. Experimental tests were conducted on the structure and surface of the nanomaterial, confirming the heparin aggregation on the synthesis with a size between the GO layers of 7.44 Å, indicating a C-O type bond, and exhibiting a hydrophilic surface characteristic (36.2°).

METHODS

Computational simulations of the ab initio with SIESTA code, LDA approximations, and an energy shift of 0.05 eV. Molecular docking simulations were performed in the AutoDock Vina software integrated with the AMDock Tools Software using the AMBER force field. GO, GO@2.5Heparin, and GO@5Heparin were synthesized by Hummers and impregnation methods, respectively, and characterized by X-ray diffraction and surface contact angle.

In Silico Models for Anti-COVID-19 Drug Discovery: A Systematic Review

The coronavirus disease 2019 (COVID-19) is a severe worldwide pandemic. Due to the emergence of various SARS-CoV-2 variants and the presence of only one Food and Drug Administration (FDA) approved anti-COVID-19 drug (remdesivir), the disease remains a mindboggling global public health problem. Developing anti-COVID-19 drug candidates that are effective against SARS-CoV-2 and its various variants is a pressing need that should be satisfied. This systematic review assesses the existing literature that used in silico models during the discovery procedure of anti-COVID-19 drugs. Cochrane Library, Science Direct, Google Scholar, and PubMed were used to conduct a literature search to find the relevant articles utilizing the search terms "In silico model," "COVID-19," "Anti-COVID-19 drug," "Drug discovery," "Computational drug designing," and "Computer-aided drug design." Studies published in English between 2019 and December 2022 were included in the systematic review. From the 1120 articles retrieved from the databases and reference lists, only 33 were included in the review after the removal of duplicates, screening, and eligibility assessment. Most of the articles are studies that use SARS-CoV-2 proteins as drug targets. Both ligand-based and structure-based methods were utilized to obtain lead anti-COVID-19 drug candidates. Sixteen articles also assessed absorption, distribution, metabolism, excretion, toxicity (ADMET), and drug-likeness properties. Confirmation of the inhibitory ability of the candidate leads by in vivo or in vitro assays was reported in only five articles. Virtual screening, molecular docking (MD), and molecular dynamics simulation (MDS) emerged as the most commonly utilized in silico models for anti-COVID-19 drug discovery.

Standardization of in-house anti-IgG and IgA ELISAs for the detection of COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19). RT-PCR detection of viral RNA represents the gold standard method for diagnosis of COVID-19. However, multiple diagnostic tests are needed for acute disease diagnosis and assessing immunity during the COVID-19 outbreak. Here, we developed in-house anti-RBD IgG and IgA enzyme-linked immunosorbent assays (ELISAs) using a well-defined serum sample panel for screening and identification of human SARS-CoV-2 infection. We found that our in-house anti-SARS-CoV-2 IgG ELISA displayed a 93.5% sensitivity and 98.8% specificity whereas our in-house anti-SARS-CoV-2 IgA ELISA provided assay sensitivity and specificity at 89.5% and 99.4%, respectively. The agreement kappa values of our in-house anti-SARS-CoV-2 IgG and IgA ELISA assays were deemed to be excellent and fair, respectively, when compared to RT-PCR and excellent for both assays when compared to Euroimmun anti-SARS-CoV-2 IgG and IgA ELISAs. These data indicate that our in-house anti-SARS-CoV-2 IgG and IgA ELISAs are compatible performing assays for the detection of SARS-CoV-2 infection.

Design of Novel Phosphatidylinositol 3-Kinase Inhibitors for Non-Hodgkin's Lymphoma: Molecular Docking, Molecular Dynamics, and Density Functional Theory Studies on Gold Nanoparticles

Non-Hodgkin's lymphomas are a diverse collection of lymphoproliferative cancers that are much less predictable than Hodgkin's lymphomas with a far greater tendency to metastasize to extranodal sites. A quarter of non-Hodgkin's lymphoma cases develop at extranodal sites and the majority of them involve nodal and extranodal sites. The most common subtypes include follicular lymphoma, chronic/small lymphocytic leukaemia, mantel cell lymphoma, and marginal zone lymphoma. Umbralisib is one of the latest PI3Kδ inhibitors in clinical trials for several hematologic cancer indications. In this study, new umbralisib analogues were designed and docked to the active site of PI3Kδ, the main target of the phosphoinositol-3-kinase/Akt/mammalian target of the rapamycin pathway (PI3K/AKT/mTOR). This study resulted in eleven candidates, with strong binding to PI3Kδ with a docking score between -7.66 and -8.42 Kcal/mol. The docking analysis of ligand-receptor interactions between umbralisib analogues bound to PI3K showed that their interactions were mainly controlled by hydrophobic interactions and, to a lesser extent, by hydrogen bonding. In addition, the MM-GBSA binding free energy was calculated. Analogue 306 showed the highest free energy of binding with -52.22 Kcal/mol. To identify the structural changes and the complexes' stability of proposed ligands, molecular dynamic simulation was used. Based on this research finding, the best-designed analogue, analogue 306, formed a stable ligand-protein complex. In addition, pharmacokinetics and toxicity analysis using the QikProp tool demonstrated that analogue 306 had good absorption, distribution, metabolism, and excretion properties. Additionally, it has a promising predicted profile in immune toxicity, carcinogenicity, and cytotoxicity. In addition, analogue 306 had stable interactions with gold nanoparticles that have been studied using density functional theory calculations. The best interaction with gold was observed at the oxygen atom number 5 with -29.42 Kcal/mol. Further in vitro and in vivo investigations are recommended to be carried out to verify the anticancer activity of this analogue.

Turning down PI3K/AKT/mTOR signalling pathway by natural products: an in silico multi-target approach

The PI3K/AKT/mTOR pathway is a significant target for cancer drug discovery. Many efforts have focused on discovering new inhibitors against key kinase proteins involved in this pathway for cancer treatment. PI3K/mTOR dual inhibitors, such as PKI-179, have been reported to be more effective than agents that act only on a single protein target. The present computational study aimed to discover triple target inhibitors against PI3K, AKT, and mTOR proteins. Accordingly, the PI3K protein bound with the ligand was used as input for e-pharmacophore modelling to generate the pharmacophore hypothesis and then screened for a library of 270,540 natural products from the Zinc database resulting in 57,220 compounds that matched the hypothesis. These compounds were then docked into the active site of PI3K, resulting in 292 compounds with better docking scores than the co-crystallized ligand. These compounds were re-docked into AKT and mTOR proteins. Besides, MM-GBSA binding free energy calculations, MD simulations, and ADMET prediction were carried out, leading to 5 potential triple-target inhibitors namely, ZINC000014644152, ZINC000014760695, ZINC000014644839, ZINC000095099451, and ZINC000005998557. In conclusion, these inhibitors may be possible leads for inhibiting PI3K/AKT/mTOR pathway, and they may be further evaluated in vitro and clinically as anticancer agents.

Use of Antiandrogens as Therapeutic Agents in COVID-19 Patients

COVID-19, caused by the severe acute respiratory syndrome coronavirus 2 (SARS CoV-2), is estimated to have caused over 6.5 million deaths worldwide. The emergence of fast-evolving SARS-CoV-2 variants of concern alongside increased transmissibility and/or virulence, as well as immune and vaccine escape capabilities, highlight the urgent need for more effective antivirals to combat the disease in the long run along with regularly updated vaccine boosters. One of the early risk factors identified during the COVID-19 pandemic was that men are more likely to become infected by the virus, more likely to develop severe disease and exhibit a higher likelihood of hospitalisation and mortality rates compared to women. An association exists between SARS-CoV-2 infectiveness and disease severity with sex steroid hormones and, in particular, androgens. Several studies underlined the importance of the androgen-mediated regulation of the host protease TMPRSS2 and the cell entry protein ACE2, as well as the key role of these factors in the entry of the virus into target cells. In this context, modulating androgen signalling is a promising strategy to block viral infection, and antiandrogens could be used as a preventative measure at the pre- or early hospitalisation stage of COVID-19 disease. Different antiandrogens, including commercial drugs used to treat metastatic castration-sensitive prostate cancer and other conditions, have been tested as antivirals with varying success. In this review, we summarise the most recent updates concerning the use of antiandrogens as prophylactic and therapeutic options for COVID-19.

Insights from computational studies on the potential of natural compounds as inhibitors against SARS-CoV-2 spike omicron variant

Coronavirus disease 2019 (COVID-19) is a major global health emergency, with more than six million deaths worldwide. It is becoming increasingly challenging to treat COVID-19 due to the emergence of novel variants. The omicron variant is capable to evade defences and spread quickly. Among many validated COVID-19 targets, the spike (S) protein plays an important role in receptor recognition (via the S1 subunit) and membrane fusion (via the S2 subunit). The S protein is one of the vital targets for the development of drugs to combat this illness. In this research, we applied various computational methods such as molecular docking, molecular dynamics, MM-GBSA calculations, and ADMET prediction to identify potential natural products from Saudi medicinal plants against the spike omicron variant. As a result, three compounds (LTS0002490, LTS0117007, and LTS0217912) were identified with better binding affinity to the spike omicron variant compared to the reference compound (VE607). In addition, these compounds showed stable interactions with the target during molecular dynamics simulations for 140 ns. Last, these compounds have optimal ADMET properties. We suggest that these compounds may be considered promising hits to treat COVID-19 if experimentally validated.

The SARS-CoV-2 Antibodies, Their Diagnostic Utility, and Their Potential for Vaccine Development

Antibodies (Abs) are important immune mediators and powerful diagnostic markers in a wide range of infectious diseases. Understanding the humoral immunity or the development of effective antibodies against SARS-CoV-2 is a prerequisite for limiting disease burden in the community and aids in the development of new diagnostic, therapeutic, and vaccination options. Accordingly, the role of antiviral antibodies in the resistance to and diagnosis of SARS-CoV-2 infection was explored. Antibody testing showed the potential in adding important diagnostic value to the routine diagnosis and clinical management of COVID-19. They could also play a critical role in COVID-19 surveillance, allowing for a better understanding of the full scope of the disease. The development of several vaccines and the success of passive immunotherapy suggest that anti-SARS-CoV-2 antibodies have the potential to be used in the treatment and prevention of SARS-CoV-2 infection. In this review, we highlight the role of antibodies in the diagnosis of SARS-CoV-2 infection and provide an update on their protective roles in controlling SARS-CoV-2 infection as well as vaccine development.