Topology-based protein classification: A deep learning approach

Abstract

Utilizing Artificial Intelligence (AI) in computational biology techniques could offer significant advantages in alleviating the growing workloads faced by structural biologists, especially with the emergence of big data. In this study, we employed Delaunay tessellation as a promising method to obtain the overall structural topology of proteins. Subsequently, we developed multi-class deep neural network models to classify protein superfamilies based on their local topology. Our models achieved a test accuracy of approximately 0.92 in classifying proteins into 18 well-populated superfamilies. We believe that the results of this study hold substantial value since, to the best of our knowledge, no previous studies have reported the utilization of protein topological data for protein classification through deep learning and Delaunay tessellation.