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

Author:

Limaye Akanksha1,Sweta Jajoriya1,Madhavi Maddala2,Mudgal Urvy1,Mukherjee Sourav1,Sharma Shreshtha1,Hussain Tajamul3,Nayarisseri Anuraj1,Singh Sanjeev Kumar4

Affiliation:

1. In silico Research Laboratory, Eminent Biosciences, Mahalakshmi Nagar, Indore – 452010, Madhya Pradesh, India

2. Department of Zoology, Nizam College, Osmania University, Hyderabad - 500001, Telangana State, India

3. Center of Excellence in Biotechnology Research, College of Science, King Saud University, Riyadh, Saudi Arabia

4. Computer Aided Drug Designing and Molecular Modeling Lab, Department of Bioinformatics, Alagappa University, Karaikudi-630 003, Tamil Nadu, India

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.

Funder

Ministry of Human Resource Developmen

Department of Science and Technology, Ministry of Science and Technology

Department of Biotechnology (DBT), New Delhi

Publisher

Bentham Science Publishers Ltd.

Subject

Drug Discovery,General Medicine

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