Multitarget Potential Drug Candidates for High-Grade Gliomas Identified by Multiple Reaction Monitoring Coupled with In Silico Drug Repurposing.

High-grade gliomas (HGGs) are extremely aggressive primary brain tumors with high mortality rates. Despite notable progress achieved by clinical research and biomarkers emerging from proteomics studies, efficacious drugs and therapeutic targets are limited. This study used targeted proteomics, in silico molecular docking, and simulation-based drug repurposing to identify potential drug candidates for HGGs. Importantly, we performed multiple reaction monitoring (MRM) on differentially expressed proteins with putative roles in the development and progression of HGGs based on our previous work and the published literature. Furthermore, in silico molecular docking-based drug repurposing was performed with a customized library of FDA-approved drugs to identify multitarget-directed ligands. The top drug candidates such as Pazopanib, Icotinib, Entrectinib, Regorafenib, and Cabozantinib were explored for their drug-likeness properties using the SwissADME. Pazopanib exhibited binding affinities with a maximum number of proteins and was considered for molecular dynamic simulations and cell toxicity assays. HGG cell lines showed enhanced cytotoxicity and cell proliferation inhibition with Pazopanib and Temozolomide combinatorial treatment compared to Temozolomide alone. To the best of our knowledge, this is the first study combining MRM with molecular docking and simulation-based drug repurposing to identify potential drug candidates for HGG. While the present study identified five multitarget-directed potential drug candidates, future clinical studies in larger cohorts are crucial to evaluate the efficacy of these molecular candidates. The research strategy and methodology used in the present study offer new avenues for innovation in drug discovery and development which may prove useful, particularly for cancers with low cure rates.

Delineating the Structure-Dynamics-Binding Differences among BA.1, BA.4/5, and BF.7 SARS-CoV-2 Variants through Atomistic Simulations: Correlation with Structural and Epidemiological Features.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an RNA virus possessing a spike (S) protein that facilitates the entry of the virus into human cells. The emergence of highly transmissible and fit SARS-CoV-2 variants has been driven by the positive selection of mutations within the S-protein. Notable among these variants are alpha, beta, gamma, delta, and omicron (BA.1), with the latter contributing to significant global health challenges and impacting populations worldwide. Recently, a novel subvariant of BA.1, named BF.7, has surfaced, purportedly exhibiting elevated transmissibility and infectivity rates. In order to comprehend and compare the transmissibility and disease progression characteristics of distinct SARS-CoV-2 variants, we performed an extensive comparative analysis utilizing all-atom molecular dynamics (MD) simulations (in triplicate) to investigate the structural, dynamic, and binding features of BA.1, BA.4/5, and BF.7. Our simulation findings, energetic analysis, and assessment of physicochemical properties collectively illuminate the dominance of the BA.1 variant over the others, a trend that is further substantiated by the sustained global prevalence of BA.1 relative to BA.4/5 and BF.7. Additionally, our simulation results align well with the reported cryoelectron microscopy (cryo-EM) structural data and epidemiological characteristics obtained from the Global Initiative on Sharing All Influenza Data (GISAID). This study presents a comprehensive comparative elucidation of the critical structural, dynamic, and binding attributes of these variants, providing insights into the predominance of BA.1 and its propensity to continuously generate numerous novel subvariants.