AlphaCRV: a pipeline for identifying accurate binder topologies in mass-modeling with AlphaFold

Motivation: The speed and accuracy of deep learning-based structure prediction algorithms make it now possible to perform in silico "pull-downs"to identify protein-protein interactions on a proteome-wide scale. However, on such a large scale, existing scoring algorithms are often insufficient to discriminate biologically relevant interactions from false positives. Results: Here, we introduce AlphaCRV, a Python package that helps identify correct interactors in a one-against-many AlphaFold screen by clustering, ranking, and visualizing conserved binding topologies, based on protein sequence and fold.