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Protein folding activity of ribosomal RNA is a selective target of two unrelated antiprion drugs.

ABSTRACT: 6-Aminophenanthridine (6AP) and Guanabenz (GA, a drug currently in use for the treatment of hypertension) were isolated as antiprion drugs using a yeast-based assay. These structurally unrelated molecules are also active against mammalian prion in several cell-based assays and in vivo in a mouse model for prion-based diseases.Here we report the identification of cellular targets of these drugs. Using affinity chromatography matrices for both drugs, we demonstrate an RNA-dependent interaction of 6AP and GA with the ribosome. These specific interactions have no effect on the peptidyl transferase activity of the ribosome or on global translation. In contrast, 6AP and GA specifically inhibit the ribosomal RNA-mediated protein folding activity of the ribosome.6AP and GA are therefore the first compounds to selectively inhibit the protein folding activity of the ribosome. They thus constitute precious tools to study the yet largely unexplored biological role of this protein folding activity.

SUBMITTER: Tribouillard-Tanvier D

PROVIDER: S-EPMC2374897 | biostudies-literature | 2008 May

REPOSITORIES: biostudies-literature

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Protein folding activity of ribosomal RNA is a selective target of two unrelated antiprion drugs.

Tribouillard-Tanvier Déborah D Dos Reis Suzana S Gug Fabienne F Voisset Cécile C Béringue Vincent V Sabate Raimon R Kikovska Ema E Talarek Nicolas N Bach Stéphane S Huang Chenhui C Desban Nathalie N Saupe Sven J SJ Supattapone Surachai S Thuret Jean-Yves JY Chédin Stéphane S Vilette Didier D Galons Hervé H Sanyal Suparna S Blondel Marc M

PloS one 20080514 5

<h4>Background</h4>6-Aminophenanthridine (6AP) and Guanabenz (GA, a drug currently in use for the treatment of hypertension) were isolated as antiprion drugs using a yeast-based assay. These structurally unrelated molecules are also active against mammalian prion in several cell-based assays and in vivo in a mouse model for prion-based diseases.<h4>Methodology/principal findings</h4>Here we report the identification of cellular targets of these drugs. Using affinity chromatography matrices for b ...[more]

PMID: 18478094

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Project description:RNA secondary structure prediction, or folding, is a classic problem in bioinformatics: given a sequence of nucleotides, the aim is to predict the base pairs formed in its three dimensional conformation. The inverse problem of designing a sequence folding into a particular target structure has only more recently received notable interest. With a growing appreciation and understanding of the functional and structural properties of RNA motifs, and a growing interest in utilising biomolecules in nano-scale designs, the interest in the inverse RNA folding problem is bound to increase. However, whereas the RNA folding problem from an algorithmic viewpoint has an elegant and efficient solution, the inverse RNA folding problem appears to be hard.In this paper we present a genetic algorithm approach to solve the inverse folding problem. The main aims of the development was to address the hitherto mostly ignored extension of solving the inverse folding problem, the multi-target inverse folding problem, while simultaneously designing a method with superior performance when measured on the quality of designed sequences. The genetic algorithm has been implemented as a Python program called Frnakenstein. It was benchmarked against four existing methods and several data sets totalling 769 real and predicted single structure targets, and on 292 two structure targets. It performed as well as or better at finding sequences which folded in silico into the target structure than all existing methods, without the heavy bias towards CG base pairs that was observed for all other top performing methods. On the two structure targets it also performed well, generating a perfect design for about 80% of the targets.Our method illustrates that successful designs for the inverse RNA folding problem does not necessarily have to rely on heavy biases in base pair and unpaired base distributions. The design problem seems to become more difficult on larger structures when the target structures are real structures, while no deterioration was observed for predicted structures. Design for two structure targets is considerably more difficult, but far from impossible, demonstrating the feasibility of automated design of artificial riboswitches. The Python implementation is available at http://www.stats.ox.ac.uk/research/genome/software/frnakenstein.

Dataset Information

Protein folding activity of ribosomal RNA is a selective target of two unrelated antiprion drugs.

Publications

Protein folding activity of ribosomal RNA is a selective target of two unrelated antiprion drugs.

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