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De novo design of drug-binding proteins with predictable binding energy and specificity

Lu, L.; Gou, X.; Tan, S.; Mann, S.; Yang, H.; Zhong, X.; Gazgalis, D.; Valdiviezo, J.; Jo, H.; Wu, Y.; Diolaiti, M.; Ashworth, A.; Polizzi, N.; DeGrado, W.

2023-12-23 biophysics
10.1101/2023.12.23.573178 bioRxiv
Show abstract

The de novo design of small-molecule-binding proteins has seen exciting recent progress; however, the ability to achieve exquisite affinity for binding small molecules while tuning specificity has not yet been demonstrated directly from computation. Here, we develop a computational procedure that results in the highest affinity binders to date with predetermined relative affinities, targeting a series of PARP1 inhibitors. Two of four designed proteins bound with affinities ranging from < 5 nM to low M, in a predictable manner. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free-energy calculations performed directly on the designed models are in excellent agreement with the experimentally measured affinities, suggesting that the de novo design of small-molecule-binding proteins with tuned interaction energies is now feasible entirely from computation. We expect these methods to open many opportunities in biomedicine, including rapid sensor development, antidote design, and drug delivery vehicles. One Sentence SummaryWe use informatic sampling to design low nM drug-binding proteins, and physics-based calculations to accurately predict affinities.

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