Search

Visceral leishmaniasis (VL), caused by protozoa of the genus Leishmania, remains a significant public health concern due to its potentially lethal nature if untreated. Current chemotherapy options are limited by severe toxicity and drug resistance. Derivatives of 1,2,4-oxadiazole have emerged as promising drug candidates due to their broad biological activity. This study investigated the effects of novel 1,2,4-oxadiazole derivatives (Ox1–Ox7) on Leishmania infantum, the etiological agent of VL. In silico predictions using SwissADME suggest that these compounds have high oral absorption and good bioavailability. Among them, Ox1 showed the most promise, with higher selectivity against promastigotes and lower cytotoxicity towards L929 fibroblasts and J774.G8 macrophages. Ox1 exhibited selectivity indices of 18.7 and 61.7 against L. infantum promastigotes and amastigotes, respectively, compared to peritoneal macrophages. Ultrastructural analyses revealed severe morphological damage in both parasite forms, leading to cell death. Additionally, Ox1 decreased the mitochondrial membrane potential in promastigotes, as shown by flow cytometry. Molecular docking and dynamic simulations indicated a strong affinity of Ox1 for the L. infantum CYP51 enzyme. Overall, Ox1 is a promising and effective compound against L. infantum. [ABSTRACT FROM AUTHOR]

The design of antibody mimetics holds great promise for revolutionizing therapeutic interventions by offering alternatives to conventional antibody therapies. Structure-based computational approaches have emerged as indispensable tools in the rational design of those molecules, enabling the precise manipulation of their structural and functional properties. This review covers the main classes of designed antigen-binding motifs, as well as alternative strategies to develop tailored ones. We discuss the intricacies of different computational protein-protein interaction design strategies, showcased by selected successful cases in the literature. Subsequently, we explore the latest advancements in the computational techniques including the integration of machine and deep learning methodologies into the design framework, which has led to an augmented design pipeline. Finally, we verse onto the current challenges that stand in the way between high-throughput computer design of antibody mimetics and experimental realization, offering a forward-looking perspective into the field and the promises it holds to biotechnology., (© 2024 The Author(s). FEBS Open Bio published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)