Comparing AlphaFold2 and ESMFold Protein Structure Predictions for Structural Bioinformatics Applications
This project explores the comparison of AI-based protein structure prediction methods, AlphaFold2 and ESMFold, for biological research applications. Protein structure predictions were analyzed using computational methods to evaluate accuracy, confidence, and efficiency. Python and MDAnalysis were used to process structural data, calculate metrics such as pLDDT scores, RMSD, residue contacts, and structural clashes, and assess tradeoffs between prediction accuracy and computational speed.
