1Department of Biotechnology, School of Applied and Life Sciences, Uttaranchal University, Dehradun-248007, Uttarakhand, India
2Department of Zoology, School of Applied and Life Sciences, Uttaranchal University, Dehradun-248007, Uttarakhand, India
3Department of Zoology, Kalindi College, University of Delhi, New Delhi-110008, India
*Corresponding authors e-mail: par.yadav2011@gmail.com
Glioblastoma multiforme (GBM) is an extremely virulent and treatment-resistant primary brain tumor that has a very rapid course, is commonly recurrent, and has very poor patient prognosis. Discovery of strong molecular targets is still urgent to further precision oncology in GBM. An integrative bioinformatics and computational platform was used to clarify oncogenic applicability and druggability of ribonucleotide reductase subunit M2 (RRM2) in the current study. The clinical value of RRM2 is demonstrated by the significant up-regulation in GBM in both cases of differential expression and survival analysis to accompany the poor prognostic outcome. Functional enrichment studies also highlighted its role in key oncogenic pathways, such as cell cycle, DNA replication, and nucleotide biosynthesis. These were followed by structure-based virtual screening against three validated binding sites of RRM2, which showed that several phytochemicals had better binding affinities than known inhibitors. It is worth noting that nardostachysin, calactin, and oleanolic acid surfaced as promising candidates, and they showed good consistent interaction major functional domains. ADMET and toxicity profiling identified nardostachysin as the most promising lead compound, with the best pharmacokinetic properties and good safety parameters. Taken together, these data make RRM2 an attractive therapeutic candidate in GBM and suggest some phytochemicals as potential inhibitors. This paper provide a logical basis for further experimental validation and creation of new, plant-tailored therapeutic interventions to manage GBM.
Glioblastoma multiforme (GBM), RRM2, bioinformatics analysis, molecular targeting, precision oncology