Nigella sativa and its chemical constituents: pre-clinical and clinical evidence for their potential anti-SARS-CoV-2 effects.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused over 500 million reported cases of COVID-19 worldwide with relatively high morbidity and mortality. Although global vaccination drive has helped control the pandemic, the newer variant of the virus still holds the world in ransom. Several medicinal herbs with antiviral properties have been reported, and one such promising herb is Nigella sativa (NS). Recent molecular docking, pre-clinical, and clinical studies have shown that NS extracts may have the potential to prevent the entry of coronaviruses into the host cell as well as to treat and manage COVID-19 symptoms. Several active compounds from NS, such as nigelledine, α-hederin, dithymoquinone (DTQ), and thymoquinone (TQ), have been proposed as excellent ligands to target angiotensin-converting enzyme 2 (ACE2 receptors) and other targets on host cells as well as the spike protein (S protein) on SARS-CoV-2. By binding to these target proteins, these ligands could potentially prevent the binding between ACE2 and S protein. Though several articles have been published on the promising therapeutic role of NS and its constituents against SARS-CoV-2 infection, in this review, we consolidate the published information on NS and SARS-CoV-2, focusing on pre-clinical in silico studies as well as clinical trials reported between 2012 and 2023.

Assessment of potential drug interactions among psychiatric inpatients receiving antipsychotic therapy of a secondary care hospital, United Arab Emirates.

The majority of the antipsychotic drugs are also known to interact with other co-administered drugs. Drug-drug interaction (DDI) reports among patients receiving antipsychotic medications are common. The study aims to identify the potential drug-drug, drug-tobacco, and drug-ethanol interactions associated with antipsychotics and significant predictors of potential DDIs (pDDIs). A prospective observational study was conducted among psychiatric inpatients receiving antipsychotic therapy and met the inclusion criteria that were reviewed for the presence of pDDIs using DRUGDEX-Micromedex database 2.0. The identified pDDIs were graded according to the severity and type of documentation. A total of 110 patients had a minimum of a single interaction, and the overall frequency of pDDIs reported was 64.7%. Of 158 pDDIs, 92 interactions (58.2%) were of major severity, while 66 interactions were of moderate severity (41.8%). Olanzapine with valproate (40 [25.3%]) was the most commonly documented pDDIs, followed by risperidone with valproate (20 [12.6%]). Olanzapine with tobacco (20 [69%]) was the most common drug-tobacco interaction. Simultaneously, olanzapine with ethanol was the most common potential drug and ethanol interaction (9 [50%]). Variables such as the number of drugs and polypharmacy statistically significantly predicted pDDIs (F[7, 162] = 8.155, P < 0.05, R2 = 0.26). Knowing the severity of different pDDIs will help clinicians and prescribers monitor patient safety through regular monitoring for interactions and adverse drug effects in future. The number of medications and polypharmacy was found to be the most significant predictor of pDDIs.