Literature DB >> 18652457

Two-dimensional combinatorial screening identifies specific aminoglycoside-RNA internal loop partners.

Matthew D Disney1, Lucas P Labuda, Dustin J Paul, Shane G Poplawski, Alexei Pushechnikov, Tuan Tran, Sai P Velagapudi, Meilan Wu, Jessica L Childs-Disney.   

Abstract

Herein is described the identification of RNA internal loops that bind to derivatives of neomycin B, neamine, tobramycin, and kanamycin A. RNA loop-ligand partners were identified by a two-dimensional combinatorial screening (2DCS) platform that probes RNA and chemical spaces simultaneously. In 2DCS, an aminoglycoside library immobilized onto an agarose microarray was probed for binding to a 3 x 3 nucleotide RNA internal loop library (81,920 interactions probed in duplicate in a single experiment). RNAs that bound aminoglycosides were harvested from the array via gel excision. RNA internal loop preferences for three aminoglycosides were identified from statistical analysis of selected structures. This provides consensus RNA internal loops that bind these structures and include: loops with potential GA pairs for the neomycin derivative, loops with potential GG pairs for the tobramycin derivative, and pyrimidine-rich loops for the kanamycin A derivative. Results with the neamine derivative show that it binds a variety of loops, including loops that contain potential GA pairs that also recognize the neomycin B derivative. All studied selected internal loops are specific for the aminoglycoside that they were selected to bind. Specificity was quantified for 16 selected internal loops by studying their binding to each of the arrayed aminoglycosides. Specificities ranged from 2- to 80-fold with an average specificity of 20-fold. These studies show that 2DCS is a unique platform to probe RNA and chemical space simultaneously to identify specific RNA motif-ligand interactions.

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Year:  2008        PMID: 18652457     DOI: 10.1021/ja803234t

Source DB:  PubMed          Journal:  J Am Chem Soc        ISSN: 0002-7863            Impact factor:   15.419


  75 in total

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2.  Targeted Degradation of a Hypoxia-Associated Non-coding RNA Enhances the Selectivity of a Small Molecule Interacting with RNA.

Authors:  Matthew G Costales; Blessy Suresh; Kamalakannan Vishnu; Matthew D Disney
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3.  A Massively Parallel Selection of Small Molecule-RNA Motif Binding Partners Informs Design of an Antiviral from Sequence.

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4.  A Macrocyclic Peptide Ligand Binds the Oncogenic MicroRNA-21 Precursor and Suppresses Dicer Processing.

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5.  Dynamic combinatorial selection of molecules capable of inhibiting the (CUG) repeat RNA-MBNL1 interaction in vitro: discovery of lead compounds targeting myotonic dystrophy (DM1).

Authors:  Peter C Gareiss; Krzysztof Sobczak; Brian R McNaughton; Prakash B Palde; Charles A Thornton; Benjamin L Miller
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6.  Two-dimensional combinatorial screening identifies specific 6'-acylated kanamycin A- and 6'-acylated neamine-RNA hairpin interactions.

Authors:  Olga Aminova; Dustin J Paul; Jessica L Childs-Disney; Matthew D Disney
Journal:  Biochemistry       Date:  2008-12-02       Impact factor: 3.162

7.  Controlling the specificity of modularly assembled small molecules for RNA via ligand module spacing: targeting the RNAs that cause myotonic muscular dystrophy.

Authors:  Melissa M Lee; Jessica L Childs-Disney; Alexei Pushechnikov; Jonathan M French; Krzysztof Sobczak; Charles A Thornton; Matthew D Disney
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8.  Selection of bead-displayed, PNA-encoded chemicals.

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9.  The role of flexibility in the rational design of modularly assembled ligands targeting the RNAs that cause the myotonic dystrophies.

Authors:  Matthew D Disney; Melissa M Lee; Alexei Pushechnikov; Jessica L Childs-Disney
Journal:  Chembiochem       Date:  2010-02-15       Impact factor: 3.164

10.  Two-dimensional combinatorial screening and the RNA Privileged Space Predictor program efficiently identify aminoglycoside-RNA hairpin loop interactions.

Authors:  Dustin J Paul; Steven J Seedhouse; Matthew D Disney
Journal:  Nucleic Acids Res       Date:  2009-09-02       Impact factor: 16.971

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