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In vitro selection of a DNA-templated small-molecule library reveals a class of macrocyclic kinase inhibitors.

ABSTRACT: DNA-templated organic synthesis enables the translation of DNA sequences into synthetic small-molecule libraries suitable for in vitro selection. Previously, we described the DNA-templated multistep synthesis of a 13,824-membered small-molecule macrocycle library. Here, we report the discovery of small molecules that modulate the activity of kinase enzymes through the in vitro selection of this DNA-templated small-molecule macrocycle library against 36 biomedically relevant protein targets. DNA encoding selection survivors was amplified by PCR and identified by ultra-high-throughput DNA sequencing. Macrocycles corresponding to DNA sequences enriched upon selection against several protein kinases were synthesized on a multimilligram scale. In vitro assays revealed that these macrocycles inhibit (or activate) the kinases against which they were selected with IC(50) values as low as 680 nM. We characterized in depth a family of macrocycles enriched upon selection against Src kinase, and showed that inhibition was highly dependent on the identity of macrocycle building blocks as well as on backbone conformation. Two macrocycles in this family exhibited unusually strong Src inhibition selectivity even among kinases closely related to Src. One macrocycle was found to activate, rather than inhibit, its target kinase, VEGFR2. Taken together, these results establish the use of DNA-templated synthesis and in vitro selection to discover small molecules that modulate enzyme activities, and also reveal a new scaffold for selective ATP-competitive kinase inhibition.

SUBMITTER: Kleiner RE

PROVIDER: S-EPMC2924185 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Applications of synthetic biology spanning human health, industrial bioproduction, and ecosystem monitoring often require small molecule sensing capabilities, typically in the form of genetically encoded small molecule biosensors. Critical to the deployment of greater numbers of these systems are methods that support the rapid development of such biosensors against a broad range of small molecule targets. Here, we use a previously developed method for selection of RNA biosensors against unmodified small molecules (DRIVER) to perform a selection against a densely multiplexed mixture of small molecules, representative of those employed in high-throughput drug screening. Using a mixture of 5,120 target compounds randomly sampled from a large diversity drug screening library, we performed a 95-round selection and then analyzed the enriched RNA biosensor library using next generation sequencing (NGS). From our analysis, we identified RNA biosensors with at least 2-fold change in signal in the presence of at least 217 distinct target compounds with sensitivities down to 25 nM. Although many of these biosensors respond to multiple targets, clustering analysis indicated at least 150 different small-molecule sensing patterns. We also built a classifier that was able to predict whether the biosensors would respond to a new compound with an average precision of 0.82. Since the target compound library was designed to be representative of larger diversity compound libraries, we expect that the described approach can be used with similar compound libraries to identify aptamers against other small molecules with a similar success rate. The new RNA biosensors (or their component aptamers) described in this work can be further optimized and used in applications such as biosensing, gene control, or enzyme evolution. In addition, the data presented here provide an expanded compendium of new RNA aptamers compared to the 82 small molecule RNA aptamers published in the literature, allowing further bioinformatic analyses of the general classes of small molecules for which RNA aptamers can be found.

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In vitro selection of a DNA-templated small-molecule library reveals a class of macrocyclic kinase inhibitors.

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