De novo design of drug-binding proteins with predictable binding energy and specificity
Copyright policy )De novo design of drug-binding proteins with predictable binding energy and specificity
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.
- Dana-Farber Cancer Institute United States
- University of California, Riverside United States
- University of California System United States
- UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- Harvard University United States
Design, 33 Built Environment and Design (for-2020), General Science & Technology, Ligands (mesh), General Science & Technology (science-metrix), 34 Chemical Sciences (for-2020), Bioengineering, Protein Engineering (mesh), Binding Sites (mesh), Biotechnology (rcdc), Molecular Dynamics Simulation, Poly(ADP-ribose) Polymerase Inhibitors, Ligands, Protein Engineering, Proteins (mesh), Article, Molecular Dynamics Simulation (mesh), Medicinal and Biomolecular Chemistry, 5.1 Pharmaceuticals (hrcs-rac), Protein Binding (mesh), 3303 Design (for-2020), Humans, Pharmacophore (mesh), Humans (mesh), Networking and Information Technology R&D (NITRD) (rcdc), Binding Sites, 3404 Medicinal and Biomolecular Chemistry (for-2020), Patient Safety (rcdc), Pharmacophore, Bioengineering (rcdc), Proteins, 540, Networking and Information Technology R&D (NITRD), Poly(ADP-ribose) Polymerase Inhibitors (mesh), Built Environment and Design, 5.1 Pharmaceuticals, Chemical Sciences, Patient Safety, Biotechnology, Protein Binding
Design, 33 Built Environment and Design (for-2020), General Science & Technology, Ligands (mesh), General Science & Technology (science-metrix), 34 Chemical Sciences (for-2020), Bioengineering, Protein Engineering (mesh), Binding Sites (mesh), Biotechnology (rcdc), Molecular Dynamics Simulation, Poly(ADP-ribose) Polymerase Inhibitors, Ligands, Protein Engineering, Proteins (mesh), Article, Molecular Dynamics Simulation (mesh), Medicinal and Biomolecular Chemistry, 5.1 Pharmaceuticals (hrcs-rac), Protein Binding (mesh), 3303 Design (for-2020), Humans, Pharmacophore (mesh), Humans (mesh), Networking and Information Technology R&D (NITRD) (rcdc), Binding Sites, 3404 Medicinal and Biomolecular Chemistry (for-2020), Patient Safety (rcdc), Pharmacophore, Bioengineering (rcdc), Proteins, 540, Networking and Information Technology R&D (NITRD), Poly(ADP-ribose) Polymerase Inhibitors (mesh), Built Environment and Design, 5.1 Pharmaceuticals, Chemical Sciences, Patient Safety, Biotechnology, Protein Binding
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