Boesenbergia stenophylla-Derived Stenophyllol B Exerts Antiproliferative and Oxidative Stress Responses in Triple-Negative Breast Cancer Cells with Few Side Effects in Normal Cells.

Triple-negative breast cancer (TNBC) is insensitive to target therapy for non-TNBC and needs novel drug discovery. Extracts of the traditional herb Boesenbergia plant in Southern Asia exhibit anticancer effects and contain novel bioactive compounds but merely show cytotoxicity. We recently isolated a new compound from B. stenophylla, stenophyllol B (StenB), but the impact and mechanism of its proliferation-modulating function on TNBC cells remain uninvestigated. This study aimed to assess the antiproliferative responses of StenB in TNBC cells and examine the drug safety in normal cells. StenB effectively suppressed the proliferation of TNBC cells rather than normal cells in terms of an ATP assay. This preferential antiproliferative function was alleviated by pretreating inhibitors for oxidative stress (N-acetylcysteine (NAC)) and apoptosis (Z-VAD-FMK). Accordingly, the oxidative-stress-related mechanisms were further assessed. StenB caused subG1 and G2/M accumulation but reduced the G1 phase in TNBC cells, while normal cells remained unchanged between the control and StenB treatments. The apoptosis behavior of TNBC cells was suppressed by StenB, whereas that of normal cells was not suppressed according to an annexin V assay. StenB-modulated apoptosis signaling, such as for caspases 3, 8, and 9, was more significantly activated in TNBC than in normal cells. StenB also caused oxidative stress in TNBC cells but not in normal cells according to a flow cytometry assay monitoring reactive oxygen species, mitochondrial superoxide, and their membrane potential. StenB induced greater DNA damage responses (γH2AX and 8-hydroxy-2-deoxyguanosine) in TNBC than in normal cells. All these StenB responses were alleviated by NAC pretreatment. Collectively, StenB modulated oxidative stress responses, leading to the antiproliferation of TNBC cells with little cytotoxicity in normal cells.

In-Silico Approaches for the Screening and Discovery of Broad-Spectrum Marine Natural Product Antiviral Agents Against Coronaviruses

The urgent need for SARS-CoV-2 controls has led to a reassessment of approaches to identify and develop natural product inhibitors of zoonotic, highly virulent, and rapidly emerging viruses. There are yet no clinically approved broad-spectrum antivirals available for beta-coronaviruses. Discovery pipelines for pan-virus medications against a broad range of betacoronaviruses are therefore a priority. A variety of marine natural product (MNP) small molecules have shown inhibitory activity against viral species. Access to large data caches of small molecule structural information is vital to finding new pharmaceuticals. Increasingly, molecular docking simulations are being used to narrow the space of possibilities and generate drug leads. Combining in-silico methods, augmented by metaheuristic optimization and machine learning (ML) allows the generation of hits from within a virtual MNP library to narrow screens for novel targets against coronaviruses. In this review article, we explore current insights and techniques that can be leveraged to generate broad-spectrum antivirals against betacoronaviruses using in-silico optimization and ML. ML approaches are capable of simultaneously evaluating different features for predicting inhibitory activity. Many also provide a semi-quantitative measure of feature relevance and can guide in selecting a subset of features relevant for inhibition of SARS-CoV-2.

Contemporary Approaches to the Discovery and Development of Broad-Spectrum Natural Product Prototypes for the Control of Coronaviruses.

The pressing need for SARS-CoV-2 controls has led to a reassessment of strategies to identify and develop natural product inhibitors of zoonotic, highly virulent, and rapidly emerging viruses. This review article addresses how contemporary approaches involving computational chemistry, natural product (NP) and protein databases, and mass spectrometry (MS) derived target-ligand interaction analysis can be utilized to expedite the interrogation of NP structures while minimizing the time and expense of extraction, purification, and screening in BioSafety Laboratories (BSL)3 laboratories. The unparalleled structural diversity and complexity of NPs is an extraordinary resource for the discovery and development of broad-spectrum inhibitors of viral genera, including Betacoronavirus, which contains MERS, SARS, SARS-CoV-2, and the common cold. There are two key technological advances that have created unique opportunities for the identification of NP prototypes with greater efficiency: (1) the application of structural databases for NPs and target proteins and (2) the application of modern MS techniques to assess protein-ligand interactions directly from NP extracts. These approaches, developed over years, now allow for the identification and isolation of unique antiviral ligands without the immediate need for BSL3 facilities. Overall, the goal is to improve the success rate of NP-based screening by focusing resources on source materials with a higher likelihood of success, while simultaneously providing opportunities for the discovery of novel ligands to selectively target proteins involved in viral infection.