Antiplasmodial Activity and Phytochemical Constituents of Selected Antimalarial Plants Used by Native People in West Timor Indonesia

Untargeted Chemical Profile, Antioxidant, and Enzyme Inhibition Activity of Physalis angulata L. from the Peruvian Amazon: A Contribution to the Validation of Its Pharmacological Potential

Physalis angulata is a plant of great value in traditional medicine known for its content of bioactive compounds, such as physalins and withanolides, which possess diverse biological activities. In this study, the chemical profile, antioxidant activity, and enzyme inhibition capacity of aqueous and ethanolic extracts obtained from the root, stem, leaves, calyx, and fruits of P. angulata collected in Peru were evaluated. A total of forty-two compounds were detected in the extracts using UHPLC-ESI-QTOF-MS analysis. In vitro analyses revealed that leaf extracts contained the highest concentration of phenolic compounds, while leaf and fruit extracts showed the best results in FRAP, DPPH, and ABTS antioxidant tests; on the other hand, inhibition of AChE, BChE, α-glucosidase, and α-amylase enzymes was variable, but calyx and fruit extracts showed higher effectiveness. In silico analyses indicated that the compounds physagulin A, physagulin F, physagulide P, physalin B, and withaminimin showed stable interactions and favorable binding affinities with the catalytic sites of the enzymes studied. These results confirm the pharmacological potential of extracts and compounds derived from different organs of P. angulata, suggesting their promising use in treating diseases related to the central nervous system and metabolic syndrome.

Quest for malaria management using natural remedies

Malaria, transmitted through the bite of a Plasmodium-infected Anopheles mosquito, remains a significant global health concern. This review examines the complex life cycle of Plasmodium, emphasizing the role of humans and mosquitoes in its transmission and proliferation. Malarial parasites are transmitted as sporozoites to the human body by biting an infected female Anopheles mosquito. These sporozoites then invade liver cells, multiply, and release merozoites, which infect red blood cells, perpetuating the cycle. As this cycle continues, the affected person starts experiencing the clinical symptoms of the disease. The current treatments for malaria, including chloroquine, artemisinin-based combination therapy, and quinine, are discussed alongside the challenges of drug resistance and misdiagnosis. Although efforts have been made to develop a malarial vaccine, they have so far been unsuccessful. Additionally, the review explores the potential of medicinal plants as remedies for malaria, highlighting the efficacy of compounds derived from Artemisia annua, Cinchona species, and Helianthus annuus L., as well as exploration of plants and phytocompounds like cryptolepine, and isoliquiritigenin against drug-resistant Plasmodium species. Moreover, studies from Pakistan further highlight the diverse vegetal resources utilized in malaria treatment, emphasizing the need for further research into natural remedies. Despite the advantages of herbal medicines, including cost-effectiveness, and fewer side effects; their limitations must be taken into account, including variations in potency and potential drug interactions. The review concludes by advocating for a balanced approach to malaria treatment and prevention, emphasizing the importance of early detection, accurate diagnosis, and integrated efforts to combat the disease in the endemic regions.

Machine learning enhances prediction of plants as potential sources of antimalarials

Plants are a rich source of bioactive compounds and a number of plant-derived antiplasmodial compounds have been developed into pharmaceutical drugs for the prevention and treatment of malaria, a major public health challenge. However, identifying plants with antiplasmodial potential can be time-consuming and costly. One approach for selecting plants to investigate is based on ethnobotanical knowledge which, though having provided some major successes, is restricted to a relatively small group of plant species. Machine learning, incorporating ethnobotanical and plant trait data, provides a promising approach to improve the identification of antiplasmodial plants and accelerate the search for new plant-derived antiplasmodial compounds. In this paper we present a novel dataset on antiplasmodial activity for three flowering plant families - Apocynaceae, Loganiaceae and Rubiaceae (together comprising c. 21,100 species) - and demonstrate the ability of machine learning algorithms to predict the antiplasmodial potential of plant species. We evaluate the predictive capability of a variety of algorithms - Support Vector Machines, Logistic Regression, Gradient Boosted Trees and Bayesian Neural Networks - and compare these to two ethnobotanical selection approaches - based on usage as an antimalarial and general usage as a medicine. We evaluate the approaches using the given data and when the given samples are reweighted to correct for sampling biases. In both evaluation settings each of the machine learning models have a higher precision than the ethnobotanical approaches. In the bias-corrected scenario, the Support Vector classifier performs best - attaining a mean precision of 0.67 compared to the best performing ethnobotanical approach with a mean precision of 0.46. We also use the bias correction method and the Support Vector classifier to estimate the potential of plants to provide novel antiplasmodial compounds. We estimate that 7677 species in Apocynaceae, Loganiaceae and Rubiaceae warrant further investigation and that at least 1300 active antiplasmodial species are highly unlikely to be investigated by conventional approaches. While traditional and Indigenous knowledge remains vital to our understanding of people-plant relationships and an invaluable source of information, these results indicate a vast and relatively untapped source in the search for new plant-derived antiplasmodial compounds.

Potential Plant-Based New Antiplasmodial Agent Used in Papua Island, Indonesia

Resistance to antimalarial medicine remains a threat to the global effort for malaria eradication. The World Health Organization recently reported that artemisinin partial resistance, which was defined as delayed parasite clearance, was detected in Southeast Asia, particularly in the Greater Mekong subregion, and in Africa, particularly in Rwanda and Uganda. Therefore, the discovery of a potential new drug is important to overcome emerging drug resistance. Natural products have played an important role in drug development over the centuries, including the development of antimalarial drugs, with most of it influenced by traditional use. Recent research on traditional medicine used as an antimalarial treatment on Papua Island, Indonesia, reported that 72 plant species have been used as traditional medicine, with Alstonia scholaris, Carica papaya, Andrographis paniculata, and Physalis minima as the most frequently used medicinal plants. This review aimed to highlight the current research status of these plants for potential novel antiplasmodial development. In conclusion, A. paniculata has the highest potential to be developed as an antiplasmodial, and its extract and known bioactive isolate andrographolide posed strong activity both in vitro and in vivo. A. scholaris and C. papaya also have the potential to be further investigated as both have good potential for their antiplasmodial activities in vivo. However, P. minima is a less studied medicinal plant; nevertheless, it opens the opportunity to explore the potential of this plant.