Towards multi-target glioblastoma therapy: Structural, distribution, and functional insights into protein target candidates

Abstract

Glioblastoma is the most commonly occurring and most lethal primary brain tumor. Treatment options are limited in number and therapeutic development remains a major challenge. However, substantial progress has been made in better understanding the underlying biology of the disease. A recent proteomic meta-analysis revealed that 270 proteins were commonly dysregulated in glioblastoma, highlighting the complexity of the disease. This motivated us to explore potential protein targets which may be collectively inhibited, based on common upregulation, as part of a multi-target therapeutic strategy. Herein, we identify and characterize structural attributes relevant to the druggability of six protein target candidates. Computational analysis of crystal structures revealed druggable cavities in each of these proteins, and various parameters of these cavities were determined. For proteins with inhibitor-bound structures available, inhibitor compounds were found to overlap with the computationally determined cavities upon structural alignment. We also performed bioinformatic analysis for normal transcriptional expression distribution of these proteins across various brain regions and various tissues, as well as gene ontology curation to gain functional insights, as this information is useful for understanding the potential for off-target adverse effects. Our findings represent initial steps towards the development of multi-target glioblastoma therapy and may aid future work exploring similar therapeutic strategies.