Efforts to control mammalian gene expression with ligand-responsive riboswitches have been hindered by lack of a general method for generating efficient switches in mammalian systems. Here we describe a rational-design approach that enables rapid development of efficient cis-acting aptazyme riboswitches. We identified communication-module characteristics associated with aptazyme functionality through analysis of a 32-aptazyme test panel. We then developed a scoring system that predicts an aptazymes's activity by integrating three characteristics of communication-module bases: hydrogen bonding, base stacking, and distance to the enzymatic core. We validated the power and generality of this approach by designing aptazymes responsive to three distinct ligands, each with markedly wider dynamic ranges than any previously reported. These aptayzmes efficiently regulated adeno-associated virus (AAV)-vectored transgene expression in cultured mammalian cells and mice, highlighting one application of these broadly usable regulatory switches. Our approach enables efficient, protein-independent control of gene expression by a range of small molecules.
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Animal experimentation: This study was performed in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All of the animals were handled according to approved institutional animal care and use committee (IACUC) protocol (#14-028) of the Scripps Florida.
© 2016, Zhong et al.
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Deep Mutational Scanning (DMS) is an emerging method to systematically test the functional consequences of thousands of sequence changes to a protein target in a single experiment. Because of its utility in interpreting both human variant effects and protein structure-function relationships, it holds substantial promise to improve drug discovery and clinical development. However, applications in this domain require improved experimental and analytical methods. To address this need, we report novel DMS methods to precisely and quantitatively interrogate disease-relevant mechanisms, protein-ligand interactions, and assess predicted response to drug treatment. Using these methods, we performed a DMS of the melanocortin-4 receptor (MC4R), a G-protein-coupled receptor (GPCR) implicated in obesity and an active target of drug development efforts. We assessed the effects of >6600 single amino acid substitutions on MC4R’s function across 18 distinct experimental conditions, resulting in >20 million unique measurements. From this, we identified variants that have unique effects on MC4R-mediated Gαs- and Gαq-signaling pathways, which could be used to design drugs that selectively bias MC4R’s activity. We also identified pathogenic variants that are likely amenable to a corrector therapy. Finally, we functionally characterized structural relationships that distinguish the binding of peptide versus small molecule ligands, which could guide compound optimization. Collectively, these results demonstrate that DMS is a powerful method to empower drug discovery and development.
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