Chemical reactivities and molecular docking studies of parthenolide with the main protease of HEP-G2 and SARS-CoV-2

Chromatography Scrutiny, Molecular Docking, Clarifying the Selectivities and the Mechanism of [3 + 2] Cycloloaddition Reaction between Linallol and Chlorobenzene-Nitrile-oxide

Employing the Molecular Electron Density Theory, [3 + 2] cycloaddition processes between 4-chlorobenzenenitrileoxide and linalool, have been applied using the DFT/B3LYP/6-311(d,p) method, activation, reaction energies and the reactivity indices are calculated. In an investigation of conceptual DFT indices, LIL-1 will contribute to this reaction as a nucleophile, whilst NOX-2 will participate as an electrophile. This cyclization is regio, chemo and stereospecific, as demonstrated by the reaction and activation energies, in clear agreement with the experiment's results, in addition, ELF analysis revealed that the mechanism for this cycloaddition occurs in two steps. Furthermore, a docking study was conducted on the products studied, and the interaction with the protein protease COVID-19 (PDB ID: 6LU7), our results indicate that the presence of the -OH group increases the affinity of these products, moreover, adsorption study by chromatography was made on silica gel as support; our outcome reveals that the -OH group creates an intramolecular hydrogen bond in the product P2, while in the product P3 will create a hydrogen bond with the silica gel which makes the two products P2 and P3 are very easy to separate by chromatography, this result is in excellent agreement with the Rf retention value. The study might provide a fundamental for developing natural anti-viral compound in promoting human health.

ADME Study, Molecular Docking, Elucidating the Selectivities and the Mechanism of [4 + 2] Cycloaddition Reaction Between (E)-N ((dimethylamino)methylene)benzothioamide and (S)-3-acryloyl-4-phenyloxazolidin-2-one

The molecular electron density theory (MEDT) was employed to examine the [4 + 2] cycloaddition reaction between (E)-N-((dimethylamino)methylene)benzothioamide (1) and (S)-3-acryloyl-4-phenyloxazolidin-2-one (2) at the B3LYP/6-311++G(d,p) design level. Parr functions and energy studies clearly show that this reaction is regio- and stereoselective, in perfect agreement with experimental results. By evaluating the chemical mechanism in terms of bond evolution theory (BET) and electron localization function (ELF), which divulges a variety of variations in the electron density along the reaction path, a single-step mechanism with highly asynchronous transition states structures was revealed. Additionally, we conducted a docking study on compounds P1, P2, P3, and P4 in the SARS-CoV-2 main protease (6LU7) in comparison to Nirmatrelvir. Our findings provide confirmation that product P4 may serve as a potent antiviral drug.

Monkeypox Virus Crosstalk with HIV: An Integrated Skin Transcriptome and Machine Learning Study

The emergence of the monkeypox virus (MPXV) outbreak presents a formidable challenge to human health. Emerging evidence suggests that individuals with HIV have been disproportionately affected by MPXV, with adverse clinical outcomes and higher mortality rates. However, the shared molecular mechanisms underlying MPXV and HIV remain elusive. We identified differentially expressed genes (DEGs) from two public data sets, GSE219036 and GSE184320, and extracted common DEGs between MPXV and HIV. We further performed gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), protein-protein interactions (PPI), candidate drug assessment, and immune correlation of hub genes analysis. We validated the key biomarkers using multiple machine learning (ML) methods including random forest (RF), t-distributed stochastic neighbor embedding (tSNE), and uniform manifold approximation and projection (UMAP). A total of 59 common DEGs were identified between MPXV and HIV. Our functional analysis highlighted multiple pathways, including the ERK cascade, NF-κB signaling, and various immune responses, playing a collaborative role in the progression of both diseases. The PPI and gene co-expression networks were constructed, and five key genes with significant immune correlations were identified and validated by multiple ML models, including SPRED1, SPHK1, ATF3, AKT3, and AKT1S1. Our study emphasizes the common pathogenesis of HIV and MPXV and highlights the pivotal genes and shared pathways, providing new opportunities for evidence-based management strategies in HIV patients co-infected with MPXV.

The therapeutic effect and mechanism of parthenolide in skeletal disease, cancers, and cytokine storm

Parthenolide (PTL or PAR) was first isolated from Magnolia grandiflora and identified as a small molecule cancer inhibitor. PTL has the chemical structure of C15H20O3 with characteristics of sesquiterpene lactones and exhibits the biological property of inhibiting DNA biosynthesis of cancer cells. In this review, we summarise the recent research progress of medicinal PTL, including the therapeutic effects on skeletal diseases, cancers, and inflammation-induced cytokine storm. Mechanistic investigations reveal that PTL predominantly inhibits NF-κB activation and other signalling pathways, such as reactive oxygen species. As an inhibitor of NF-κB, PTL appears to inhibit several cytokines, including RANKL, TNF-α, IL-1β, together with LPS induced activation of NF-κB and NF-κB -mediated specific gene expression such as IL-1β, TNF-α, COX-2, iNOS, IL-8, MCP-1, RANTES, ICAM-1, VCAM-1. It is also proposed that PTL could inhibit cytokine storms or hypercytokinemia triggered by COVID-19 via blocking the activation of NF-κB signalling. Understanding the pharmacologic properties of PTL will assist us in developing its therapeutic application for medical conditions, including arthritis, osteolysis, periodontal disease, cancers, and COVID-19-related disease.

Promising natural products against SARS-CoV-2: Structure, function, and clinical trials

The corona virus disease 2019 (COVID‐19) caused by severe acute respiratory syndrome coronavirus type 2 (SARS‐COV‐2) poses a severe threat to human health and still spreads globally. Due to the high mutation ratio and breakthrough infection rate of the virus, vaccines and anti‐COVID‐19 drugs require continual improvements. Drug screening research has shown that some natural active products can target the critical proteins of SARS‐CoV‐2, including 3CLpro, ACE2, FURIN, and RdRp, which could produce great inhibitory effects on SARS‐COV‐2. In addition, some natural products have displayed activities of immunomodulation, antiinflammatory, and antihepatic failure in COVID‐19 clinical trials, which may relate to their non‐monomeric structures. However, further evaluation and high‐quality assessments, including safety verification tests, drug interaction tests, and clinical trials, are needed to substantiate natural products' multi‐target and multi‐pathway effects on COVID‐19. Here, we review the literature on several promising active natural products that may act as vaccine immune enhancers or provide targeted anti‐COVID‐19 drugs. The structures, mechanisms of action, and research progress of these natural products are analyzed, to hopefully provide effective ideas for the development of targeted drugs that possess better structure, potency, and safety.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.