The ability to design proteins with high affinity and selectivity for any given small molecule is a rigorous test of our understanding of the physiochemical principles that govern molecular recognition. Attempts to rationally design ligand-binding proteins have met with little success, however, and the computational design of protein-small-molecule interfaces remains an unsolved problem. Current approaches for designing ligand-binding proteins for medical and biotechnological uses rely on raising antibodies against a target antigen in immunized animals and/or performing laboratory-directed evolution of proteins with an existing low affinity for the desired ligand, neither of which allows complete control over the interactions involved in binding. Here we describe a general computational method for designing pre-organized and shape complementary small-molecule-binding sites, and use it to generate protein binders to the steroid digoxigenin (DIG). Of seventeen experimentally characterized designs, two bind DIG; the model of the higher affinity binder has the most energetically favourable and pre-organized interface in the design set. A comprehensive binding-fitness landscape of this design, generated by library selections and deep sequencing, was used to optimize its binding affinity to a picomolar level, and X-ray co-crystal structures of two variants show atomic-level agreement with the corresponding computational models. The optimized binder is selective for DIG over the related steroids digitoxigenin, progesterone and β-oestradiol, and this steroid binding preference can be reprogrammed by manipulation of explicitly designed hydrogen-bonding interactions. The computational design method presented here should enable the development of a new generation of biosensors, therapeutics and diagnostics.
ID: qFpAZe694
Submitter: Paul Chang
Submission Date: June 27, 2018, 11:49 a.m.
Version: 1
Colors: | D | E | R | H | K | S | T | N | Q | A | V | I | L | M | F | Y | W | C | G | P |
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Percent Identity | Matching Chains | Protein | Accession | Entry Name |
---|---|---|---|---|
396.8 | A,B,C,D | Nuclear transport factor 2 | P33331 | NTF2_YEAST |
368.0 | A,B,C,D | Nuclear transport factor 2 | Q6FRC6 | NTF2_CANGA |
361.6 | A,B,C,D | Nuclear transport factor 2 | Q75AA5 | NTF2_ASHGO |
100.0 | Beta-glucanase | P17989 | GUB_FIBSS | |
100.0 | Endo-1,4-beta-xylanase | P81536 | XYNA_BYSSP | |
100.0 | Uncharacterized PhzA/B-like protein PA3332 | Q9HYR3 | Y3332_PSEAE | |
100.0 | Inosose isomerase | P42419 | IOLI_BACSU | |
400.0 | A,B,C,D | 3-dehydroquinate dehydratase | O30011 | AROD_ARCFU |
197.8 | A,B | Retinol-binding protein 4 | P02753 | RET4_HUMAN |
197.8 | A,B | Retinol-binding protein 4 | P61641 | RET4_PANTR |
189.0 | A,B | Retinol-binding protein 4 | M5AXY1 | RET4_FELCA |
189.0 | A,B | Retinol-binding protein 4 | Q28369 | RET4_HORSE |
185.8 | A,B | Retinol-binding protein 4 | P27485 | RET4_PIG |
181.8 | A,B | Retinol-binding protein 4 | P06912 | RET4_RABIT |
184.6 | A,B | Retinol-binding protein 4 | P18902 | RET4_BOVIN |