Validation of Automated Docking Programs for Docking and Database Screening against RNA Drug Targets

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Abstract
The increasing awareness of the essential role of RNA in controlling viral replication and in bacterial protein synthesis emphasizes the potential of ribonucleoproteins as targets for developing new antibacterial and antiviral drugs. RNA forms well defined three-dimensional structures with clefts and binding pockets reminiscent of the active sites of proteins. Furthermore, it precedes proteins in the translation pathway; inhibiting the function of a single RNA molecule would result in inhibition of multiple proteins. Thus, small molecules that bind RNA specifically would combine the advantages of antisense and RNAi strategies with the much more favorable medicinal chemistry of small-molecule therapeutics. The discovery of small-molecule inhibitors of RNA with attractive pharmacological potential would be facilitated if we had available effective computational tools of structure-based drug design. Here, we systematically test automated docking tools developed for proteins using existing three-dimensional structures of RNA−small molecule complexes. The results show that the native structures can generally be reproduced to within 2.5 Å more than 50−60% of the time. For more than half of the test complexes, the native ligand ranked among the top 10% compounds in a database-scoring test. Through this work, we provide parameters for the validated application of automated docking tools to the discovery of new inhibitors of RNA function.