In-silico lead identification of the pan-mutant IDH1 and IDH2 inhibitors to target glioblastoma

Abstract

Glioblastoma (GBM) is an aggressive malignant type of brain tumor. Targeting one single intracellular pathway might not alleviate the disease, rather it activates the other molecular pathways that lead to the worsening of the disease condition. Therefore, in this study, we attempted to target both isocitrate dehydrogenase 1 (IDH1) and IDH2, which are one of the most commonly mutated proteins in GBM and other cancer types. Here, standard precision and extra precision docking, IFD, MM-GBSA, QikProp, and molecular dynamics (MD) simulation were performed to identify the potential dual inhibitor for IDH1 and IDH2 from the enamine database containing 59,161 ligands. Upon docking the ligands with IDH1 (PDB: 6VEI) and IDH2 (PDB: 6VFZ), the top eight ligands were selected, based on the XP Glide score. These ligands produced favourable MMGBSA scores and ADME characteristics. Finally, the top four ligands 12953, 44825, 51295, and 53210 were subjected to MD analysis. Interestingly, 53210 showed maximum interaction with Gln 277 for 99% in IDH1 and Gln 316 for 100% in IDH2, which are the crucial amino acids for the inhibitory function of IDH1 and IDH2 to target GBM. Therefore, the present study attempts to identify the novel molecules which could possess a pan-inhibitory action on both IDH1 and IDH that could be crucial in the management of GBM. Yet further evaluation involving in vitro and in vivo studies is warranted to support the data in our current study.

Communicated by Ramaswamy H. Sarma

Keywords:

• Brain tumor
• glioblastoma
• IDH1
• IDH2
• mutation
• insilico docking
• pan inhibitors
• molecular dynamics

Disclosure statement

The authors report there are no competing interests to declare.

Acknowledgement

The authors thank the All India Council for Technical Education- Research Promotion Scheme (AICTE-RPS). Also, the authors are thankful to the Department of Pharmaceutics, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education (MAHE), Manipal for facilitating the computer simulations (DST-SERB, New Delhi, India EMR/2016/007006) and Manipal- Schrodinger Centre for Molecular Simulations, MAHE. All the authors thank Manipal College of Pharmaceutical Sciences, MAHE for providing the necessary support and research facility to carry out the present research work. Our deepest gratitude to Dr. Raghu Chandrashekhar Hariharapura for his untiring support.

Additional information

Funding

This work was supported by the All India Council for Technical Education- Research Promotion Scheme (AICTE-RPS) and open access funding was provided by Manipal Academy of Higher Education, Manipal