Structure-guided pharmacophore based virtual screening, docking, and molecular dynamics to discover repurposed drugs as novel inhibitors against endoribonuclease Nsp15 of SARS-CoV-2

COVID-19 (Corona Virus Disease of 2019) caused by the novel ‘Severe Acute Respiratory Syndrome Coronavirus-2’ (SARS-CoV-2) has wreaked havoc on human health and the global economy. As a result, for new medication development, it's critical to investigate possible therapeutic targets against the novel virus. ‘Non-structural protein 15’ (Nsp15) endonuclease is one of the crucial targets which helps in the replication of virus and virulence in the host immune system. Here, in the current study, we developed the structure-based pharmacophore model based on Nsp15-UMP interactions and virtually screened several databases against the selected model. To validate the screening process, we docked the top hits obtained after secondary filtering (Lipinski’s rule of five, ADMET & Topkat) followed by 100 ns molecular dynamics (MD) simulations. Next, to revalidate the MD simulation studies, we have calculated the binding free energy of each complex using the MM-PBSA procedure. The discovered repurposed drugs can aid the rational design of novel inhibitors for Nsp15 of the SARS-CoV-2 enzyme and may be considered for immediate drug development. Communicated by Ramaswamy H. Sarma</p

Structure-based drug discovery to identify SARS-CoV2 spike protein–ACE2 interaction inhibitors

After the emergence of the COVID-19 pandemic in late 2019, the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has undergone a dynamic evolution driven by the acquisition of genetic modifications, resulting in several variants that are further classified as variants of interest (VOIs), variants under monitoring (VUM) and variants of concern (VOC) by World Health Organization (WHO). Currently, there are five SARS-CoV-2 VOCs (Alpha, Beta, Delta, Gamma and Omicron), two VOIs (Lambda and Mu) and several other VOIs that have been reported globally. In this study, we report a natural compound, Curcumin, as the potential inhibitor to the interactions between receptor binding domain (RBD(S1)) and human angiotensin-converting enzyme 2 (hACE2) domains and showcased its inhibitory potential for the Delta and Omicron variants through a computational approach by implementing state of the art methods. The study for the first time revealed a higher efficiency of Curcumin, especially for hindering the interaction between RBD(S1) and hACE-2 domains of Delta and Omicron variants as compared to other lead compounds. We investigated that the mutations in the RBD(S1) of VOC especially Delta and Omicron variants affect its structure compared to that of the wild type and other variants and therefore altered its binding to the hACE2 receptor. Molecular docking and molecular dynamics (MD) simulation analyses substantially supported the findings in terms of the stability of the docked complexes. This study offers compelling evidence, warranting a more in-depth exploration into the impact of these alterations on the binding of identified drug molecules with the Spike protein. Further investigation into their potential therapeutic effects in vivo is highly recommended. Communicated by Ramaswamy H. Sarma</p

Identification of novel inhibitors of <i>Neisseria gonorrhoeae</i> MurI using homology modeling, structure-based pharmacophore, molecular docking, and molecular dynamics simulation-based approach

MurI is one of the most significant role players in the biosynthesis of the peptidoglycan layer in Neisseria gonorrhoeae (Ng). We attempted to highlight the structural and functional relationship between Ng-MurI and D-glutamate to design novel molecules targeting this interaction. The three-dimensional (3D) model of the protein was constructed by homology modeling and the quality and consistency of generated model were assessed. The binding site of the protein was identified by molecular docking studies and a pharmacophore was identified using the interactions of the control ligand. The structure-based pharmacophore model was validated and employed for high-throughput virtual screening and molecular docking to identify novel Ng-MurI inhibitors. Finally, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with the substrate glutamate and novel molecules facilitated us to confirm the stability of the protein-ligand docked complexes. The 100 ns MD simulations of the potential lead compounds with protein confirmed that the modeled complexes were stable. This study identifies novel potential compounds with good fitness and docking scores, which made the interactions of biological significance within the protein active site. Hence, the identified compounds may act as new leads to design and develop Ng-MurI inhibitors. Communicated by Ramaswamy H. Sarma</p

Poly(ethylene glycol)-<i>co</i>-methacrylamide-<i>co</i>-acrylic acid based nanogels for delivery of doxorubicin

<p>Polymeric nanogels have been widely explored for their potential application as delivery carriers for cancer therapeutics. The ability of nanogels to encapsulate therapeutics by simple diffusion mechanism and the ease of their fabrication to impart target specificity in addition to their ability to get internalized into target cells make them good candidates for drug delivery. The present study aims to investigate the applicability of poly(ethylene glycol)-<i>co</i>-methacrylamide-<i>co</i>-acrylic acid (PMA)-based nanogels as a viable option for the delivery of doxorubicin (DOX). The nanogels were synthesized by free radical polymerization in an inverse mini-emulsion and characterized by nuclear magnetic resonance spectroscopy (¹H NMR), Fourier transform infrared spectroscopy, dynamic light scattering, transmission electron microscopy (TEM), X-ray diffraction and differential scanning calorimetry. DOX was physically incorporated into the nanogels (PMA-DOX) and the mechanism of its <i>in vitro</i> release was studied. TEM experiment revealed spherical morphology of nanogels and the hydrodynamic diameter of the neat nanogels was in the range of 160 ± 46.95 nm. The size of the nanogels increased from 235.1 ± 28.46 to 403.7 ± 89.89 nm with the increase in drug loading capacity from 4.68 ± 0.03 to 13.71 ± 0.01%. The sustained release of DOX was observed upto 80 h and the release rate decreased with increased loading capacity following anomalous release mechanism as indicated by the value of diffusion exponent (<i>n</i> = 0.64–0.75) obtained from Korsmeyer–Peppas equation. Further, cytotoxicity evaluation of PMA-DOX nanogels on HeLa cells resulted in relatively higher efficacy (IC₅₀~5.88 μg/mL) as compared to free DOX (IC₅₀~7.24 μg/mL) thus demonstrating that the preparation is potentially a promising drug delivery carrier.</p

Combined Multiomics and In Silico Approach Uncovers PRKAR1A as a Putative Therapeutic Target in Multi-Organ Dysfunction Syndrome

Despite all epidemiological, clinical, and experimental research efforts, therapeutic concepts in sepsis and sepsis-induced multi-organ dysfunction syndrome (MODS) remain limited and unsatisfactory. Currently, gene expression data sets are widely utilized to discover new biomarkers and therapeutic targets in diseases. In the present study, we analyzed MODS expression profiles (comprising 13 sepsis and 8 control samples) retrieved from NCBI-GEO and found 359 differentially expressed genes (DEGs), among which 170 were downregulated and 189 were upregulated. Next, we employed the weighted gene co-expression network analysis (WGCNA) to establish a MODS-associated gene co-expression network (weighted) and identified representative module genes having an elevated correlation with age. Based on the results, a turquoise module was picked as our hub module. Further, we constructed the PPI network comprising 35 hub module DEGs. The DEGs involved in the highest-confidence PPI network were utilized for collecting pathway and gene ontology (GO) terms using various libraries. Nucleotide di- and triphosphate biosynthesis and interconversion was the most significant pathway. Also, 3 DEGs within our PPI network were involved in the top 5 significantly enriched ontology terms, with hypercortisolism being the most significant term. PRKAR1A was the overlapping gene between top 5 significant pathways and GO terms, respectively. PRKAR1A was considered as a therapeutic target in MODS, and 2992 ligands were screened for binding with PRKAR1A. Among these ligands, 3 molecules based on CDOCKER score (molecular dynamics simulated-based score, which allows us to rank the binding poses according to their quality and to identify the best pose for each system) and crucial interaction with human PRKAR1A coding protein and protein kinase-cyclic nucleotide binding domains (PKA RI alpha CNB-B domain) via active site binding residues, viz. Val283, Val302, Gln304, Val315, Ile327, Ala336, Ala337, Val339, Tyr373, and Asn374, were considered as lead molecules