Quantifying the Role of OpenFold Components in Protein Structure Prediction

Models such as AlphaFold2 and OpenFold have transformed protein structure prediction, yet their inner workings remain poorly understood. We present a methodology to systematically evaluate the contribution of individual OpenFold components to structure prediction accuracy. We identify several components that are broadly critical, while others vary in importance across proteins. We further show that the contribution of multiple components is statistically significantly correlated with protein length. These findings provide insight into how OpenFold achieves accurate predictions and highlight directions for interpreting protein prediction networks more broadly.