In Silico Insights on GD2 : A Potential Target for Pediatric Neuroblastoma

Abstract

Background: Originating from the abnormal growth of neuroblasts, pediatric neuroblastoma affects the age group below 15 years. It is an aggressive heterogenous cancer with a high morbidity rate. Biological marker GD2 synthesised by the GD2 gene acts as a powerful predictor of neuroblastoma cells. GD2 gangliosides are sialic acid-containing glycosphingolipids. Differential expression during brain development governs the function of the GD2. The present study explains the interaction of the GD2 with its established inhibitors and discovers the compound having a high binding affinity against the target protein. Technically, during the development of new compounds through docking studies, the best drug among all pre-exist inhibitors was filtered. Hence in reference to the best docked compound, the study proceeded further. Methodology: The In silico approach provides a platform to determine and establish potential inhibitor against GD2 in Pediatric neuroblastoma. The 3D structure of GD2 protein was modelled by homology base fold methods using Smith-Watermans’ Local alignment. A total of 18 established potent compounds were subjected to molecular docking and Etoposide (CID: 36462) manifested the highest affinity. The similarity search presented 336 compounds similar to Etoposide. Results: Through virtual screening, the compound having PubChem ID 10254934 showed a better affinity towards GD2 than the established inhibitor. The comparative profiling of the two compounds based on various interactions such as H-bond interaction, aromatic interactions, electrostatic interactions and ADMET profiling and toxicity studies were performed using various computational tools. Conclusion: The docking separated the virtual screened drug (PubChemID: 10254934) from the established inhibitor with a better re-rank score of -136.33. The toxicity profile of the virtual screened drug was also lesser (less lethal) than the established drug. The virtual screened drug was observed to be bioavailable as it does not cross the blood-brain barrier. Conclusively, the virtual screened compound obtained in the present investigation is better than the established inhibitor and can be further augmented by In vitro analysis, pharmacodynamics and pharmacokinetic studies.

Potential Benefits of Dietary Plant Compounds on Normal and Tumor Brain Cells in Humans: In Silico and In Vitro Approaches

“…Finally, the high efficacy in neuroblastoma of DNA-topoisomerase I inhibitors (e.g., camptotechin and its derivatives irinotecan and topotecan) was demonstrated decades ago [ 63 , 64 , 65 ]; at the same time, there were many chemical–chemical and chemical–natural combinations tested to manage tumor resistance or to obtain synergistic activity [ 66 , 67 , 68 ]. In addition, in silico studies have also revealed new molecular targets and tumor inhibitors as potential cancer approaches and combined therapies [ 69 , 70 , 71 ].…”

Integrated Transcriptome Profiling Identifies Prognostic Hub Genes as Therapeutic Targets of Glioblastoma: Evidenced by Bioinformatics Analysis

“…Glioblastoma (GBM) is the most devastating and frequent type of primary brain tumor with high morbidity and mortality. Despite treatment regimens that include surgical resection with radiation and concomitant adjuvant chemotherapy, the median survival time for patients with GBM is 12–15 months, with survival rates of 25% and 10% after 2 and 5 years, respectively. − Accumulating evidence in recent years shows that GBM consists of the subpopulation of cells displaying various stem cell-like properties including long-term self-renewal with the capacity to generate phenotypically diverse hierarchical neoplastic progeny and stromal cells referred as glioma stem cells (GSCs) . GSCs also can recapitulate the essential phenotypes of the original tumor, such as tumor cell heterogeneity, invasiveness, and vascularity promoting resistance to chemotherapy and radiotherapy. , Thus, neoplastic cells displaying stem-like phenotypes are currently believed to be the main barriers for successful treatment of GBM that associated inexplicably in tumor growth and recurrence after therapy. − …”

An In silico approach for the identification of GRB2 inhibitors for the treatment of <em>Polycystic ovary syndrome</em> <em>(</em><em>PCOS</em><em>)</em>

“…This helps to develop more efficient drug candidates which would essentially help in the curing of the syndrome. The aim of the present investigation is to identify a potential GRB2 inhibitor towards the clinical treatment of Polycystic ovary syndrome (PCOS) using various molecular docking [8][9][10][11][12][13][14][15] and virtual screening approaches [16][17][18][19][20][21][22][23][24][25][26][27][28] .…”