Title:In Silico Insights on GD2 : A Potential Target for Pediatric Neuroblastoma
Volume: 19
Issue: 30
Author(s): Akanksha Limaye, Jajoriya Sweta, Maddala Madhavi, Urvy Mudgal, Sourav Mukherjee, Shreshtha Sharma, Tajamul Hussain, Anuraj Nayarisseri*Sanjeev Kumar Singh*
Affiliation:
- In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh,India
- Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu,India
Keywords:
GD2, GD2 inhibitors, Pediatric neuroblastoma, Molecular docking, Virtual screening, Tumour.
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.
