De novo design of high-affinity protein binders with AlphaProteo
Journal:
arXiv
Published Date:
Sep 12, 2024
Abstract
Computational design of protein-binding proteins is a fundamental capability
with broad utility in biomedical research and biotechnology. Recent methods
have made strides against some target proteins, but on-demand creation of
high-affinity binders without multiple rounds of experimental testing remains
an unsolved challenge. This technical report introduces AlphaProteo, a family
of machine learning models for protein design, and details its performance on
the de novo binder design problem. With AlphaProteo, we achieve 3- to 300-fold
better binding affinities and higher experimental success rates than the best
existing methods on seven target proteins. Our results suggest that AlphaProteo
can generate binders "ready-to-use" for many research applications using only
one round of medium-throughput screening and no further optimization.
