Exploring Molecular Docking Simulations To Investigate The Interaction Between Modified Penicillin Structures And PBP2a In Staphylococcus aureus

Author: Omar Emam

Abstract

Penicillin-binding proteins (PBPs) play a pivotal role in the mechanism of bacterial resistance, particularly in Staphylococcus aureus. PBP2a, a resistant form of PBP, poses significant challenges in antibiotic resistance due to its mutated structures that affect the binding to antibiotics. This study leverages computational biology and artificial intelligence to compare the binding affinity between the normal PBP and PBP2a to penicillin. As a result, it confirms the risks of these mutations and helps in understanding resistance mechanisms to guide drug design. When utilizing molecular docking and machine learning models, we explore structural modifications to penicillin that improve its binding to PBP2a. Our findings suggest that strategic alterations in penicillin's active site significantly enhance its binding potential. Consequently, this research highlights the transformative role of AI in drug discovery and positions computational tools as essential for paving the way for new avenues in drug development. This offers a promising solution to combat antibiotic resistance in pathogenic bacteria.

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Exploring Molecular Docking Simulations to Investigate the Interaction Between Modified Pe.

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