Computational design of ligand-binding proteins with high affinity and selectivity
| Autor: | David Baker, Sagar D. Khare, Christine E. Tinberg, Lindsey Doyle, Kai Johnsson, Jorgen Nelson, Wojciech Jankowski, Charalampos G. Kalodimos, Alberto Schena, Jiayi Dou, Barry L. Stoddard |
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| Rok vydání: | 2013 |
| Předmět: |
Models
Molecular Protein design Plasma protein binding Biology Crystallography X-Ray Ligands Article Substrate Specificity Molecular recognition Dig Computer Simulation Binding site Progesterone Computational model Binding Sites Multidisciplinary Estradiol Proteins Reproducibility of Results Ligand (biochemistry) Combinatorial chemistry Small molecule Drug Design Digoxigenin Biotechnology Protein Binding |
| Zdroj: | Nature. 501:212-216 |
| ISSN: | 1476-4687 0028-0836 |
| Popis: | The ability to design proteins with high affinity and selectivity for any given small molecule would have numerous applications in biosensing, diagnostics, and therapeutics, and is a rigorous test of our understanding of the physiochemical principles that govern molecular recognition phenomena. Attempts to design ligand binding proteins have met with little success, however, and the computational design of precise molecular recognition between proteins and small molecules remains an “unsolved problem”1. We describe a general method for the computational design of small molecule binding sites with pre-organized hydrogen bonding and hydrophobic interfaces and high overall shape complementary to the ligand, and use it to design protein binding sites for the steroid digoxigenin (DIG). Of 17 designs that were experimentally characterized, two bind DIG; the highest affinity design has the lowest predicted interaction energy and the most pre-organized binding site in the set. A comprehensive binding-fitness landscape of this design generated by library selection and deep sequencing was used to guide optimization of binding affinity to a picomolar level, and two X-ray co-crystal structures of optimized complexes show atomic level agreement with the design models. The designed binder has a high selectivity for DIG over the related steroids digitoxigenin, progesterone, and β-estradiol, which can be reprogrammed through the designed hydrogen-bonding interactions. Taken together, the binding fitness landscape, co-crystal structures, and thermodynamic binding parameters illustrate how increases in binding affinity can result from distal sequence changes that limit the protein ensemble to conformers making the most energetically favorable interactions with the ligand. The computational design method presented here should enable the development of a new generation of biosensors, therapeutics, and diagnostics. |
| Databáze: | OpenAIRE |
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