In Silico Screening of Novel TMPRSS2 Inhibitors for Treatment of COVID-19

Molecular docking and molecular dynamics studies of natural products unravel potential inhibitors against OmpA of Acinetobacter baumannii

Emerging antimicrobial resistance has highlighted the need to design more effective antibiotics to treat deadly bacterial infections. Acinetobacter baumannii's outer membrane protein A (OmpA) is a critical virulence component involved in biofilm formation, immunomodulation, and antibiotic resistance, which characterizes it as a potential therapeutic target. The present study aimed to screen the natural product database (>1,00,000) to identify the potential inhibitor against OmpA. Molecular docking studies revealed that 10 compounds had good docking scores (≤ -7 kcal/mol) compared to the reported inhibitor epiestriol (-3.079). Further, these 10 compounds were subjected to ADME analysis and MMGBSA analysis. Based on MMGBSA results, we selected 5 compounds [NP-1 (MolPort-039-337-117), NP-5(MolPort-019-932-973), NP-6 (MolPort-005-948-336), NP-8(MolPort-042-673-978) and NP-9(MolPort-042-673-766)] with high binding affinity. Molecular dynamics simulation found that NP-5, NP-8, and NP-9 were stable after analysing their RMSD, RMSF, the radius of gyration, and hydrogen interactions of complexes. Our study revealed that NP-5, NP-8, and NP-9 bind perfectly with OmpA and can act as its potential inhibitors. The results of this study imply that the identified inhibitors have the potential for further investigation.Communicated by Ramaswamy H. Sarma.

Quercetin and taxifolin inhibits TMPRSS2 activity and its interaction with EGFR in paclitaxel-resistant breast cancer cells: An in silico and in vitro study

Transmembrane protease/serine (TMPRSS2), a type II transmembrane serine protease, plays a crucial role in different stages of cancer. Recent studies have reported that the triggering epidermal growth factor receptor (EGFR) activation through protease action promotes metastasis. However, there are no reports on the interaction of TMPRSS2 with EGFR, especially in triple-negative triple negative (TNBC). The current study investigates the unexplored interaction between TMPRSS2 and EGFR, which are key partners mediating metastasis. This interaction is explored for potential targeting using quercetin (QUE) and taxifolin (TAX). TMPRSS2 expression patterns in breast cancer (BC) tissues and subtypes have been predicted, with the prognostic significance assessed using the GENT2.0 database. Validation of TMPRSS2 expression was performed in normal and TNBC tissues, including drug-resistant cell lines, utilizing GEO datasets. TMPRSS2 was further validated as a predictive biomarker for FDA-approved chemotherapeutics through transcriptomic data from BC patients. The study demonstrated the association of TMPRSS2 with EGFR through in silico analysis and validates the findings in TNBC cohorts using the TIMER2.0 web server and the TCGA dataset through C-Bioportal. Molecular docking and molecular dynamic simulation studies identified QUE and TAX as best leads targeting TMPRSS2. They inhibited cell-free TMPRSS2 activity like clinical inhibitor of TMPRSS2, Camostat mesylate. In cell-based assays focused on paclitaxel-resistant TNBC (TNBC/PR), QUE and TAX demonstrated potent inhibitory activity against extracellular and membrane-bound TMPRSS2, with low IC50 values. Furthermore, ELISA and cell-based AlphaLISA assays demonstrated that QUE and TAX inhibit the interaction of TMPRSS2 with EGFR. Additionally, QUE and TAX exhibited significant inhibition of proliferation and cell cycle accompanied by notable alterations in the morphology of TNBC/PR cells. This study provides valuable insights into potential of QUE and TAX targeting TMPRSS2 overexpressing TNBC.

Recent advances in application of computer-aided drug design in anti-COVID-19 Virials Drug Discovery

Corona Virus Disease 2019 (COVID-19) is a global pandemic epidemic caused by severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2), which poses a serious threat to human health worldwide and results in significant economic losses. With the continuous emergence of new virus strains, small molecule drugs remain the most effective treatment for COVID-19. The traditional drug development process usually requires several years; however, the development of computer-aided drug design (CADD) offers the opportunity to develop innovative drugs quickly and efficiently. The literature review describes the general process of CADD, the viral proteins that play essential roles in the life cycle of SARS-CoV-2 and can serve as therapeutic targets, and examples of drug screening of viral target proteins by applying CADD methods. Finally, the potential of CADD in COVID-19 therapy, the deficiency, and the possible future development direction are discussed.

Discovery of druggable potent inhibitors of serine proteases and farnesoid X receptor by ligand-based virtual screening to obstruct SARS-CoV-2

The coronavirus, a subfamily of the coronavirinae family, is an RNA virus with over 40 variations that can infect humans, non-human mammals and birds. There are seven types of human coronaviruses, including SARS-CoV-2, is responsible for the recent COVID-19 pandemic. The current study is focused on the identification of drug molecules for the treatment of COVID-19 by targeting human proteases like transmembrane serine protease 2 (TMPRSS2), furin, cathepsin B, and a nuclear receptor named farnesoid X receptor (FXR). TMPRSS2 and furin help in cleaving the spike protein of the SARS-CoV-2 virus, while cathepsin B plays a critical role in the entry and pathogenesis. FXR, on the other hand, regulates the expression of ACE2, and its inhibition can reduce SARS-CoV-2 infection. By inhibiting these four protein targets with non-toxic inhibitors, the entry of the infectious agent into host cells and its pathogenesis can be obstructed. We have used the BioSolveIT suite for pharmacophore-based computational drug designing. A total of 1611 ligands from the ligand library were docked with the target proteins to obtain potent inhibitors on the basis of pharmacophore. Following the ADMET analysis and protein ligand interactions, potent and druggable inhibitors of the target proteins were obtained. Additionally, toxic substructures and the less toxic route of administration of the most potent inhibitors in rodents were also determined computationally. Compounds namely N-(diaminomethylene)-2-((3-((1R,3R)-3-(2-(methoxy(methyl)amino)-2-oxoethyl)cyclopentyl)propyl)amino)-2-oxoethan-1-aminium (26), (1R,3R)-3-(((2-ammonioethyl)ammonio)methyl)-1-((4-propyl-1H-imidazol-2-yl)methyl)piperidin-1-ium (29) and (1R,3R)-3-(((2-ammonioethyl)ammonio)methyl)-1-((1-propyl-1H-pyrazol-4-yl)methyl)piperidin-1-ium (30) were found as the potent inhibitors of TMPRSS2, whereas, 1-(1-(1-(1H-tetrazol-1-yl)cyclopropane-1‑carbonyl)piperidin-4-yl)azepan-2-one (6), (2R)-4-methyl-1-oxo-1-((7R,11S)-4-oxo-6,7,8,9,10,11-hexahydro-4H-7,11-methanopyrido[1,2-a]azocin-9-yl)pentan-2-aminium (12), 4-((1-(3-(3,5-dimethylisoxazol-4-yl)propanoyl)piperidin-4-yl)methyl)morpholin-4-ium (13), 1-(4,6-dimethylpyrimidin-2-yl)-N-(3-oxocyclohex-1-en-1-yl)piperidine-4-carboxamide (14), 1-(4-(1,5-dimethyl-1H-1,2,4-triazol-3-yl)piperidin-1-yl)-3-(3,5-dimethylisoxazol-4-yl)propan-1-one (25) and N,N-dimethyl-4-oxo-4-((1S,5R)-8-oxo-5,6-dihydro-1H-1,5-methanopyrido[1,2-a][1,5]diazocin-3(2H,4H,8H)-yl)butanamide (31) inhibited the FXR preferentially. In case of cathepsin B, N-((5-benzoylthiophen-2-yl)methyl)-2-hydrazineyl-2-oxoacetamide (2) and N-([2,2'-bifuran]-5-ylmethyl)-2-hydrazineyl-2-oxoacetamide (7) were identified as the most druggable inhibitors whereas 1-amino-2,7-diethyl-3,8-dioxo-6-(p-tolyl)-2,3,7,8-tetrahydro-2,7-naphthyridine-4‑carbonitrile (5) and (R)-6-amino-2-(2,3-dihydroxypropyl)-1H-benzo[de]isoquinoline-1,3(2H)-dione (20) were active against furin.

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.

In Silico Analysis Reveals the Inhibitory Potential of Madecassic Acid against Entry Factors of SARS-CoV-2

Coronavirus disease 19 (COVID-19) is the ongoing global health emergency caused by SARS-CoV-2 infection. The virus is highly contagious, affecting millions of people worldwide. SARS-CoV-2, with its trimeric spike glycoprotein, interacts with the angiotensin-converting enzyme 2 (ACE2) receptor and other co-receptors like basigin to invade the host cell. Moreover, certain host proteases like transmembrane serine proteases, furin, neuropilin 1 (NRP1), and endosomal cathepsins are involved in the priming of spike glycoproteins at the S1/S2 interface. This is critical for the entry of viral genome and its replication in the host cytoplasm. Vaccines and anti-SARS-CoV-2 drugs have been developed to overcome the infection. Nonetheless, the frequent emergence of mutant variants of the virus has imposed serious concerns regarding the efficacy of therapeutic agents, including vaccines that were developed for previous strains. Thus, screening and development of pharmaceutical agents with multi-target potency could be a better choice to restrain SARS-CoV-2 infection. Madecassic acid (MDCA) is a pentacyclic triterpenoid found in Centella asiatica. It has multiple medicinal properties like anti-oxidative, anti-inflammatory, and anti-diabetic potential. However, its implication as an anti- SARS-CoV-2 agent is still obscure. Hence, in the present in silico study, the binding affinities of MDCA for spike proteins, their receptors, and proteases were investigated. Results indicated that MDCA interacts with ligand-binding pockets of the spike receptor binding domain, ACE2, basigin, and host proteases, viz. transmembrane serine proteinase, furin, NRP1, and endosomal cathepsins, with greater affinities. Moreover, the MDCA-protein interface was strengthened by prominent hydrogen bonds and several hydrophobic interactions. Therefore, MDCA could be a promising multi-target therapeutic agent against SARS-CoV-2 infection.