Background: Targeting mutated isocitrate dehydrogenase 1 (mIDH1) is one of the key therapeutic strategies for the treatment of glioma. Few inhibitors, such as ivosidenib and vorasidenib, have been identified as selective inhibitors of mIDH1. However, dose-dependent toxicity and limited brain penetration of the blood-brain barrier remain the major limitations of the treatment procedures using these inhibitors.
Objective: In the present study, computational drug repurposing strategies were employed to identify potent mIDH1- specific inhibitors from the 11,808 small molecules listed in the DrugBank repository.
Methods: Tanimoto coefficient (Tc) calculations were initially used to retrieve compounds with structurally similar scaffolds to ivosidenib. The resultant compounds were then subjected to molecular docking to discriminate the binders from the non-binders. The binding affinities and pharmacokinetic properties of the screened compounds were examined using prime Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) and QikProp algorithm, respectively. The conformational stability of these molecules was validated using 100 ns molecular dynamics simulation.
Results: Together, these processes led to the identification of three-hit molecules, namely DB12001, DB08026, and DB03346, as potential inhibitors of the mIDH1 protein. Of note, the binding free energy calculations and MD simulation studies emphasized the greater binding affinity and structural stability of the hit compounds towards the mIDH1 protein.
Conclusion: The collective evidence from our study indicates the activity of DB12001 against recurrent glioblastoma, which, in turn, highlights the accuracy of our adapted strategy. Hence, we hypothesize that the identified lead molecules could be translated for the development of mIDH1 inhibitors in the near future.
Keywords: Mutated IDH1 protein, tanimoto coefficient, glide docking, prime MM-GBSA, molecular dynamics simulation, glioma.