Work

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

Year: 2024

Type: article

Abstract: 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. Availability and implementation: AlphaCRV is a Python package for Linux, freely available at https://github.com/strubelab/AlphaCRV.

Source: Bioinformatics Advances

DOI: 10.1093/bioadv/vbae131

Authors: Francisco J Guzmán-Vega, Stefan T Arold

Institution: King Abdullah University of Science and Technology

Language: English

Topic: Protein Structure and Dynamics

Subfield: Molecular Biology

Field: Biochemistry, Genetics and Molecular Biology

Domain: Life Sciences

Open Access status: gold

Estimated APC paid: $2,917

Funder: King Abdullah University of Science and Technology