The therapeutic landscape for COVID-19 and post-COVID-19 medications from genetic profiling of the Vietnamese population and a predictive model of drug-drug interaction for comorbid COVID-19 patients.

Despite the raised awareness of the role of pharmacogenomic (PGx) in personalized medicines for COVID-19, data for COVID-19 drugs is extremely scarce and not even a publication on this topic for post-COVID-19 medications to date. In the current study, we investigated the genetic variations associated with COVID-19 and post-COVID-19 therapies by using whole genome sequencing data of the 1000 Vietnamese Genomes Project (1KVG) in comparison with other populations retrieved from the 1000 Genomes Project Phase 3 (1KGP3) and the Genome Aggregation Database (gnomAD). Moreover, we also evaluated the risk of drug interactions in comorbid COVID-19 and post-COVID-19 patients based on pharmacogenomic profiles of drugs using a computational approach. For COVID-19 therapies, variants related to the response of two causal treatment agents (tolicizumab and ritonavir) and antithrombotic drugs are common in the Vietnamese cohort. Regarding post-COVID-19, drugs for mental manipulations possess the highest number of clinical annotated variants carried by Vietnamese individuals. Among the superpopulations, East Asian populations shared the most similar genetic structure with the Vietnamese population, whereas the African population showed the most difference. Comorbid patients are at an increased drug-drug interaction (DDI) risk when suffering from COVID-19 and after recovering as well due to a large number of potential DDIs which have been identified. Our results presented the population-specific understanding of the pharmacogenomic aspect of COVID-19 and post-COVID-19 therapy to optimize therapeutic outcomes and promote personalized medicine strategy. We also partly clarified the higher risk in COVID-19 patients with underlying conditions by assessing the potential drug interactions.

A green method to extract rutin from Sophora japonica L.

Sophora japonica L. contains high levels of rutin, which has great potential for use in pharmaceutical products for the treatment of diseases related to the cardiovascular and circulatory systems. We proposed a method of extracting rutin from S. japonica by using a green solvent.•Green deep eutectic solvents (DESs) of choline chloride and ethylene glycol (ChCl-Eth) showed the highest extraction efficiency of rutin from S. japonica.•Under optimal conditions, the extraction yield of ChCl-Eth was 1.34 times higher than that of methanol as solvent.•Rutin was recovered from the DES extracts using water as the antisolvent with a high recovery yield, and the DESs of ChCl-Eth could be productively recovered and reused at least 3 times.

Extraction of curcumin from turmeric residue (Curcuma longa L.) using deep eutectic solvents and surfactant solvents.

Using waste materials to extract biologically active ingredients with green solvents is a new trend for sustainable development. Herein, different types of deep eutectic solvents (DESs) and surfactant solvents (SSs) were used to extract curcumin from turmeric residues (TRs), among which choline chloride-propylene glycol (ChCl-Pro) showed the highest yield. The optimized extraction conditions included a ChCl : Pro ratio of 1 : 2, water content in the DESs of 20%, solid : liquid ratio of 1 : 40 maintained for 60 min at 50 °C, and a TR particle size of 0.18 mm. The extraction yield was 54.2 mg g-1, which was 1.31 times higher than when methanol was used as a solvent. Distilled water was used to recover curcumin from the DES extract with a recovery yield of 99.7%. Furthermore, the antioxidant and acetylcholinesterase (AChE) inhibitory activities of the recovered curcumin were evaluated, with IC50 values of 25.58 ± 0.51 and 19.12 ± 0.83 µg mL-1, respectively. This study highlights the promising potential of using green solvents to extract bioactive compounds from waste materials.