Host metabolomic responses in recurrent P. vivax malaria.

Malaria is the leading parasitic disease worldwide, with P. vivax being a major challenge for its control. Several studies have indicated metabolomics as a promising tool for combating the disease. The study evaluated plasma metabolomic profiles of patients with recurrent and non-recurrent P. vivax malaria in the Brazilian Amazon. Metabolites extracted from the plasma of P. vivax-infected patients were subjected to LC-MS analysis. Untargeted metabolomics was applied to investigate the metabolic profile of the plasma in the two groups. Overall, 51 recurrent and 59 non-recurrent patients were included in the study. Longitudinal metabolomic analysis revealed 52 and 37 significant metabolite features from the recurrent and non-recurrent participants, respectively. Recurrence was associated with disturbances in eicosanoid metabolism. Comparison between groups suggest alterations in vitamin B6 (pyridoxine) metabolism, tyrosine metabolism, 3-oxo-10-octadecatrienoate ß-oxidation, and alkaloid biosynthesis II. Integrative network analysis revealed enrichment of other metabolic pathways for the recurrent phenotype, including the butanoate metabolism, aspartate and asparagine metabolism, and N-glycan biosynthesis. The metabolites and metabolic pathways predicted in our study suggest potential biomarkers of recurrence and provide insights into targets for antimalarial development against P. vivax.

Innovative Multistage ML-QSAR Models for Malaria: From Data to Discovery.

Malaria presents a significant challenge to global public health, with around 247 million cases estimated to occur annually worldwide. The growing resistance of Plasmodium parasites to existing therapies underscores the urgent need for new and innovative antimalarial drugs. This study leveraged artificial intelligence (AI) to tackle this complex challenge. We developed multistage Machine Learning Quantitative Structure-Activity Relationship (ML-QSAR) models to effectively analyze large datasets and predict the efficacy of chemical compounds against multiple life cycle stages of Plasmodium parasites. We then selected 16 compounds for experimental evaluation, six of which showed at least dual-stage inhibitory activity and one inhibited all life cycle stages tested. Moreover, explainable AI (XAI) analysis provided insights into critical molecular features influencing model predictions, thereby enhancing our understanding of compound interactions. This study not only empowers the development of advanced predictive AI models but also accelerates the identification and optimization of potential antiplasmodial compounds.

Unveiling the Antiviral Capabilities of Targeting Human Dihydroorotate Dehydrogenase against SARS-CoV-2.

The urgent need for effective treatments against emerging viral diseases, driven by drug-resistant strains and new viral variants, remains critical. We focus on inhibiting the human dihydroorotate dehydrogenase (HsDHODH), one of the main enzymes responsible for pyrimidine nucleotide synthesis. This strategy could impede viral replication without provoking resistance. We evaluated naphthoquinone fragments, discovering potent HsDHODH inhibition with IC50 ranging from 48 to 684 nM, and promising in vitro anti-SARS-CoV-2 activity with EC50 ranging from 1.2 to 2.3 µM. These compounds exhibited low toxicity, indicating potential for further development. Additionally, we employed computational tools such as molecular docking and quantitative structure-activity relationship (QSAR) models to analyze protein-ligand interactions, revealing that these naphthoquinones exhibit a protein binding pattern similar to brequinar, a potent HsDHODH inhibitor. These findings represent a significant step forward in the search for effective antiviral treatments and have great potential to impact the development of new broad-spectrum antiviral drugs.

Pathophysiology of chikungunya virus infection associated with fatal outcomes.

Chikungunya virus (CHIKV) is a mosquito-borne alphavirus that causes acute, subacute, and chronic human arthritogenic diseases and, in rare instances, can lead to neurological complications and death. Here, we combined epidemiological, virological, histopathological, cytokine, molecular dynamics, metabolomic, proteomic, and genomic analyses to investigate viral and host factors that contribute to chikungunya-associated (CHIK) death. Our results indicate that CHIK deaths are associated with multi-organ infection, central nervous system damage, and elevated serum levels of pro-inflammatory cytokines and chemokines compared with survivors. The histopathologic, metabolite, and proteomic signatures of CHIK deaths reveal hemodynamic disorders and dysregulated immune responses. The CHIKV East-Central-South-African lineage infecting our study population causes both fatal and survival cases. Additionally, CHIKV infection impairs the integrity of the blood-brain barrier, as evidenced by an increase in permeability and altered tight junction protein expression. Overall, our findings improve the understanding of CHIK pathophysiology and the causes of fatal infections.