Quinolinyl ß-enaminone derivatives exhibit leishmanicidal activity against Leishmania donovani by impairing the mitochondrial electron transport chain complex and inducing ROS-mediated programmed cell death.

OBJECTIVES: Previously, a series of side chain-modified quinolinyl ß-enaminones was identified to possess significant activity against chloroquine-sensitive or -resistant Plasmodium falciparum and Brugia malayi microfilariae. The present study evaluates in vitro and in vivo activity of the series against Leishmania donovani and reports their mode of action. METHODS: The in vitro activity of 15 quinolinyl ß-enaminone derivatives against Leishmania promastigotes and amastigotes was assessed by luciferase assay. The reduction of organ parasite burden was assessed by Giemsa staining in L. donovani-infected BALB/c mice and hamsters. Intracellular Ca2+ and ATP level in active derivative (3D)-treated promastigotes were determined by fluorescence and luminescence assays. Flow cytometry was performed to determine loss of mitochondrial membrane potential (MMP) using JC-1 dye, reactive oxygen species (ROS) generation using 2',7'-dichlorodihydrofluorescein diacetate (DCFDA) dye, phosphatidylserine externalization by Annexin V-FITC staining and cell-cycle arrest by propidium iodide (PI) staining. RESULTS: Compounds 3A, 3B and 3D showed significant in vitro efficacy against L. donovani with IC50 < 6 µM and mild cytotoxicity (∼75% viability) at 25 µM on J774 macrophages. 3A and 3D at 50 mg/kg and 100 mg/kg reduced parasite burden (>84%) in infected mice and hamsters, respectively, whereas 3D-treated animals demonstrated maximum parasite burden reduction without organ toxicity. Mode-of-action analysis revealed that 3D induced apoptosis by inhibiting mitochondrial complex II, reducing MMP and ATP levels, increasing ROS and Ca2+ levels, ultimately triggering phosphatidylserine externalization and sub-G0/G1 cell-cycle arrest in promastigotes. CONCLUSIONS: Compound 3D-mediated inhibition of L. donovani mitochondrial complex induces apoptosis, making it a promising therapeutic candidate for visceral leishmaniasis.

Discovery of 2,3-dihydro-1H-pyrrolo[3,4-b]quinolin-1-one derivatives as possible antileishmanial agents.

A series of uniquely functionalized 2,3,-dihydro-1H-pyyrolo[3,4-b]quinolin-1-one derivatives were synthesized in one to two steps by utilizing a post-Ugi modification strategy and were evaluated for antileishmanial efficacy against visceral leishmaniasis (VL). Among the library compounds, compound 5m exhibited potential in vitro antileishmanial activity (CC50 = 65.11 µM, SI = 7.79, anti-amastigote IC50 = 8.36 µM). In vivo antileishmanial evaluation of 5m demonstrated 56.2% inhibition in liver and 61.1% inhibition in spleen parasite burden in infected Balb/c mice (12.5 mg kg-1, i.p.). In vitro pharmacokinetic study ascertained the stability of 5m in both simulated gastric fluid and simulated intestinal fluid. All the active compounds passed the PAINS filter and showed no toxicity in in silico predictions.

A machine learning-based approach to determine infection status in recipients of BBV152 (Covaxin) whole-virion inactivated SARS-CoV-2 vaccine for serological surveys.

Data science has been an invaluable part of the COVID-19 pandemic response with multiple applications, ranging from tracking viral evolution to understanding the vaccine effectiveness. Asymptomatic breakthrough infections have been a major problem in assessing vaccine effectiveness in populations globally. Serological discrimination of vaccine response from infection has so far been limited to Spike protein vaccines since whole virion vaccines generate antibodies against all the viral proteins. Here, we show how a statistical and machine learning (ML) based approach can be used to discriminate between SARS-CoV-2 infection and immune response to an inactivated whole virion vaccine (BBV152, Covaxin). For this, we assessed serial data on antibodies against Spike and Nucleocapsid antigens, along with age, sex, number of doses taken, and days since last dose, for 1823 Covaxin recipients. An ensemble ML model, incorporating a consensus clustering approach alongside the support vector machine model, was built on 1063 samples where reliable qualifying data existed, and then applied to the entire dataset. Of 1448 self-reported negative subjects, our ensemble ML model classified 724 to be infected. For method validation, we determined the relative ability of a random subset of samples to neutralize Delta versus wild-type strain using a surrogate neutralization assay. We worked on the premise that antibodies generated by a whole virion vaccine would neutralize wild type more efficiently than delta strain. In 100 of 156 samples, where ML prediction differed from self-reported uninfected status, neutralization against Delta strain was more effective, indicating infection. We found 71.8% subjects predicted to be infected during the surge, which is concordant with the percentage of sequences classified as Delta (75.6%-80.2%) over the same period. Our approach will help in real-world vaccine effectiveness assessments where whole virion vaccines are commonly used.