Insilico Investigation of specific mutations in spidroin that alter its interaction with P53

Abstract

Cancer is not only a disease but multiple diseases which pose as a major global health burden with 20 million new cases registered annually, that result in approximately 9.7 million deaths worldwide. There is no universal treatment and management, convectional therapeutic strategies in use have shown limited efficacy, recurrence and drug resistance. Protein-based therapies have emerged as promising strategy, and one under investigation involves fusion of the N-terminal of Masp1 spidroin protein of Euprosthenops australis with p53 tumor suppressor protein to provide structural stability to p53. This study was conducted through in-silico analysis to identify specific mutations in the N-terminal domain of spidroin that could alter its interaction with P53 and potentially affect its therapeutic ability. Through utilization of molecular docking tools such as Autodock vina for protein preparation, Hex 8.0.0 for molecular docking, and PDBsum for analysis of results. The interaction between p53 and N-terminal of spidroin wild type and three key significant mutant forms of spidroin (D40K, A72K and R65K) were analyzed. Results revealed that all the three mutants had increased binding affinity compared to the wild type with D40K revealing the strongest binding interaction and most compact interface with -652.0 kj/mol binding affinity. A72K showed a balanced and stable interaction with -614.4 kj/mol binding affinity while R65K revealed an enhanced electrostatic interaction with -605.2 kj/mol binding affinity despite having fewer hydrogen bonds. The findings of this study suggest that mutations in spidroin can positively affect the interaction with p53 and can enhance structural stability making it therapeutically valuable. Therefore further exploration into mutations that can impact protein interactions can provide a foundation for development of effective and well balanced protein therapies. This study was based on use of computational tools however, experimental validation through in vivo and in vitro assays has to be done to achieve beneficial therapeutic potential and biological significance of the identified mutations.