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The de novo design of small molecule–binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase–1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from <5 nM to low micromolar. 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 were in excellent agreement with the experimentally measured affinities. We conclude that de novo design of high-affinity small molecule–binding proteins with tuned interaction energies is feasible entirely from computation.
Design, Binding Sites, Pharmacophore, General Science & Technology, Proteins, Bioengineering, Molecular Dynamics Simulation, Poly(ADP-ribose) Polymerase Inhibitors, 540, Ligands, Protein Engineering, Article, Medicinal and Biomolecular Chemistry, Networking and Information Technology R&D (NITRD), Built Environment and Design, 5.1 Pharmaceuticals, Chemical Sciences, Humans, Patient Safety, Biotechnology, Protein Binding
Design, Binding Sites, Pharmacophore, General Science & Technology, Proteins, Bioengineering, Molecular Dynamics Simulation, Poly(ADP-ribose) Polymerase Inhibitors, 540, Ligands, Protein Engineering, Article, Medicinal and Biomolecular Chemistry, Networking and Information Technology R&D (NITRD), Built Environment and Design, 5.1 Pharmaceuticals, Chemical Sciences, Humans, Patient Safety, Biotechnology, Protein Binding
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citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 17 | |
popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |