Disney Lab - Research Interests


It's an RNA's World ... but it wouldn't be nothing, nothing without intelligent design

Development of an RNA motif-ligand database and Two-Dimensional Combinatorial Screening (2DCS). 

   RNA is an interesting target for developing therapeutics or chemical genetics probes of function.  At present, however, there is a limited understanding of how to target RNA with small molecules.  Part of this problem is associated with traditional RNA targeting endeavors that involve screening a few validated RNA drug targets (bacterial rRNA A-site or HIV TAR RNA, for example) for binding to a few small molecule RNA binders (aminoglycosides).  In an effort to further understand how to target RNA with small molecules, we probe both RNA space and chemical space in parallel to identify RNA motif-ligand partners.  These efforts allow for understanding what types of RNA structures are amenable for being targeted with a small molecule and what types of ligands like to bind RNA.  Such studies may evolve into a rational approach to design ligands targeting RNA.  In the post genomic era that is rich in new RNA drug targets such as micro-RNAs, this information has the potential to have large impacts in drug discovery efforts.   Read an ACS-Chemical Biology paper that we recently published on this topic here!  

Listen to an ACS-Chemical Biology Podcast with Disney's musings on targeting RNA with small molecules and the potential of 2DCS, here
 

Microarrays to study antibiotic resistance

 Our group is also interested in the design and synthesis of new antibiotics that evade resistance.  Part of the initial impediment in these endeavors was a lack of sensitive high throughput assays to study modification of antibiotics by resistance enzymes and the effect that modification has on binding to the therapeutic target.  Towards this end, we recently developed an antibiotic microarray-based method to study resistance.  In this method, libraries of antibiotics are spatially arrayed and covalently attached onto a microarray surface.  The surface is then probed for modification by a resistance enzyme using radioactive ATP as the modifying substrate.  Upon modification, the tag is transfered to modified antibiotics on the array.  Arrays are then probed for binding to the therapeutic target, in this case a bacterial rRNA A-site, to see how modification affects binding.   Such assays have been successfully applied towards studying both the APH and the ANT classes of aminoglycoside resistance enzymes.  These studies will not only allow for the identification of new antibacterials but for the development of a deeper understanding of how aminoglycosides and derivatives thereof bind to bacterial rRNA A-site and resistance enzymes.   Read a recent Biochemistry paper that we published on this topic here!

Chemical Microarrays to Identify Cell-Specific Ligands

    

 

 

      

 

    Our group is also interested in using our microarray technology to understand molecular recognition at cell surfaces.  Cell surface interactions play important roles in adhesion of cancer cells and metastasis, viral infections, and bacterial infections.  If small molecules were discovered that could specifically recognize cell surfaces they could serve as treatments for these diseases as well as diagnostic tools to study infection and cancer.  Part of the issue in these studies are a lack of high throughput screening methods to study interactions between small molecules and pathogenic cells.  Towards this end, we developed a microarray platform to study the interactions of small organic ligands and whole cells.  The advantage of using a microarray in these applications is that ligands displayed on a microarray surface can multivalently interact with cell surfaces in a manner that mimics biological interactions.  Read a recent ChemBioChem paper that we have published on this topic here!

 

Increasing The Information Content In Sequencing Reactions

 

 

    

    Sequencing reactions are used in a variety of applications such as  decoding mammalian and pathogenic genomes and in deconvoluting nucleic acid-based selections.  Our group has developed simple and general methods to increase the information content in sequencing reactions that are used to deconvolute nucleic acid selections.  This method centers on the oligomerization of multiple copies of a selected sequence.  This concatamer is then sequenced using standard methods to decode multiple active nucleic acids in a single sequencing reaction.  This increase in information content allows for improvements in the development of structure activity relationships and in the statistical analysis of selected structures.  Read a recent RNA paper that we have published on this topic here!