LazyAF, a pipeline for accessible medium-scale in silico prediction of protein-protein interactions

ABSTRACT

Artificial intelligence has revolutionized the field of protein structure prediction. However, with more powerful and complex software being developed, it is accessibility and ease of use rather than capability that is quickly becoming a limiting factor to end users. Here, I present a Google Colaboratory-based pipeline, named LazyAF, which integrates the existing ColabFold BATCH to streamline the process of medium-scale protein-protein interaction prediction. I apply LazyAF to predict the interactome of the 76 proteins encoded on a broad-host-range multi-drug resistance plasmid RK2, demonstrating the ease and accessibility the pipeline provides.