Research Plan for the Scientific Project: Title: Preforming Machine learning models for recognition of Antibiotic Resistant Protein structures vs non-Antibiotic Resistant Protein structures Background: Antibiotics are crucial in the fight against bacterial infections. However, with the rise of antibiotic resistance, there is an increasing need to understand the structures of antibiotic resistant proteins and differentiate them from non-antibiotic resistant proteins. Machine learning offers a promising approach to recognize and classify these structures efficiently. Relevance: Machine learning models have revolutionized various scientific fields by enabling the analysis of complex datasets, predicting outcomes, and automating tasks that were previously manual and time-consuming. In the realm of biomedicine, these models can provide insights into intricate biological structures, such as proteins, leading to advancements in drug design and understanding of molecular mechanisms. This research will aid in the realm of structural biology. Aim: To develop and validate machine learning models capable of recognizing and differentiating antibiotic resistant protein structures from non-antibiotic resistant protein structures.