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

结合亲和力 亲缘关系 小分子 结合能 结合位点 分子动力学 计算生物学 血浆蛋白结合 化学 药物发现 生物医学 分子 纳米技术 生物物理学 计算化学 生物 立体化学 材料科学 物理 生物信息学 生物化学 受体 有机化学 核物理学
作者
Lei Lu,Xuxu Gou,Sophia K. Tan,Samuel I. Mann,Hyunjun Yang,Xiaofang Zhong,Dimitrios Gazgalis,Jesús Valdiviezo,Hyunil Jo,Yibing Wu,Morgan E. Diolaiti,Alan Ashworth,Nicholas F. Polizzi,William F. DeGrado
标识
DOI:10.1101/2023.12.23.573178
摘要

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 μM, 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.
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