Biology subjects

Vaidya, H.

Publications and source records attributed to Vaidya, H..

2 recordsLinked to original sources

bioRxiv2026

Dihydroartemisinin inhibits Epstein-Barr virus reactivation and replication targeting lytic proteins: insights for drug repurposing

Epstein-Barr virus (EBV) is an oncogenic virus which is responsible for various malignant as well as non-malignant diseases and leads to about 200,000 deaths each year. Despite efforts, there are no FDA-approved drugs targeting EBV. Reactivation of EBV plays a critical role in the transition from latency to lytic cycle, leading to viral replication and disease progression, and is primarily regulated by the transactivator BZLF1. In this study, we combined computational screening with experimental validation to identify repurposing drugs that inhibit EBV reactivation and replication. FDA-approved compounds predicted using in-house AI/ML-based model (Anti-EBV) and miRNA-seq and RNA-seq analyses, were selected for further evaluation. Molecular docking against BZLF1, supported by in silico alanine scanning to identify critical DNA-binding residues, led to the selection of seven candidate drugs. Among these, an antimalarial drug, dihydroartemisinin (DHA), showed the strongest inhibitory activity in vitro, with an IC99 of 1 {micro}M and an SI Index of 113.5. DHA reduced both EBV viral copy number and the expression of early and late lytic genes. Molecular docking and simulation studies demonstrated stable binding of DHA within the BZLF1 DNA-binding pocket, inhibiting the key residues involved in BZLF1 activation and DNA binding. Analysis at the gene level confirmed its inhibitory effect on EBV replication, while expression analysis at the transcriptional and protein levels, along with immunofluorescence analysis, indicated its inhibitory effect on EBV reactivation and virion assembly. These findings suggest DHA as a promising repurposing antiviral candidate targeting EBV lytic proteins and offers an effective target-based therapeutic strategy. ImportanceThis study identifies a repurposed small-molecule inhibitor of EBV reactivation and replication. Here, we proposed target-based therapy, integrating computational and experimental approaches to target the EBV lytic transactivator BZLF1. Since early lytic EBV protein BZLF1 plays a critical role in viral reactivation and replication, inhibition of its activation and DNA-binding function represents a promising therapeutic approach to prevent EBV infection. Molecular docking and simulation studies revealed stable binding of DHA within the BZLF1 DNA-binding pocket. Furthermore, in vitro analyses demonstrated significant inhibition of viral gene copy number and reduced mRNA and protein levels of key lytic proteins. Thus, this study demonstrated DHA as a safe and effective repurposed therapeutic candidate against EBV infection.

microbiology↗

bioRxiv2025

Integrative plasma lipidomics and proteomics profiling to decipher potential biomarkers of dilated cardiomyopathy

BackgroundDilated cardiomyopathy (DCM), primarily characterised by left ventricular dilatation and systolic dysfunction, is one of the leading causes of heart failure and requires a critical clinical investigative strategy. However, conventional imaging techniques such as echocardiography and MRI, along with some classical CVD markers (NTproBNP, cTnT), fall short in diagnosing DCM-specific phenotypes. Thus, the need for biochemical markers with enhanced accuracy to DCM is of enormous importance. Lipids and proteins play essential roles in maintaining myocardial function. The homeostatic disruption of such biomolecules might contribute to DCM pathogenesis, thus offering to serve as potential biomarkers for DCM. Moreover, the lack of global lipidomics studies and specific protein markers in DCM patients prompted us to explore the disease pathophysiology through an integrative omics-based analysis coupled with an ML-derived approach. ObjectiveTo identify accurate, precise and specific circulatory lipidomic and proteomic biomarkers of DCM using high-resolution mass spectrometry and machine learning (ML)-based approaches. MethodsHigh-resolution-mass-spectrometry-based lipidomics and proteomics were applied to identify lipid and protein biomarkers in a cohort (n=360) of healthy and DCM patients. Top protein classifiers were further evaluated using single-cell transcriptomics on publicly available datasets from DCM myocardium and validated using ELISA. A biomarker panel was built by the integration of lipidomics and validated proteomics data using machine-learning-based approaches. ResultsA total of 125 lipids and 10 proteins have been primarily discovered with significant alterations in DCM (0.8 [≥] FC [≥] 1.2; padj < 0.05). Using a Boruta-based ML approach, we identified 39 lipids and 10 proteins as primary discriminators between DCM and controls. ELISA validation confirmed the potential of B2M (6.85 {+/-} 2.86 g/ml vs. 4.26 {+/-} 1.25 g/ml; p < 0.0001) and Tetranectin (CLEC3B) (1.99 {+/-} 0.88 g/ml vs. 2.49 {+/-} 0.90 g/ml; p = 0.0006) to emerge as protein biomarkers of DCM. In line with that, the single-cell transcriptomic analysis showed a similar trend of alteration of tetranectin (CLEC3B) in cardiomyocytes and {beta}2microglobulin (B2M) in varied cell types of the myocardium. Further, Integrated ROC analysis combining the top 8 lipid discriminators with B2M and CLEC3B achieved an AUC of 0.995, demonstrating enhanced diagnostic precision compared to the classical CVD marker NTproBNP (0.965). ConclusionThis study offers a system-omics-based perspective on first-global lipidomic and proteomic changes associated with DCM pathophysiology, with a high potential for diagnostic application.

systems biology↗