Abstract
AbstractThe rational targeting of RNA with small molecules is hampered by our still limited understanding of RNA structural and dynamic properties. Mostin silicotools for binding site identification rely on static structures and therefore cannot face the challenges posed by the dynamic nature of RNA molecules. Here we present SHAMAN, a computational technique to identify potential small-molecule binding sites in RNA structural ensembles. SHAMAN enables exploring the conformational landscape of RNA with atomistic molecular dynamics and at the same time identifying RNA pockets in an efficient way with the aid of probes and enhanced-sampling techniques. In our benchmark composed of large, structured riboswitches as well as small, flexible viral RNAs, SHAMAN successfully identified all the experimentally resolved pockets and ranked them among the most favorite probe hotspots. Overall, SHAMAN sets a solid foundation for future drug design efforts targeting RNA with small molecules, effectively addressing the long-standing challenges in the field.
Publisher
Cold Spring Harbor Laboratory
Reference88 articles.
1. Cech, T. R. & Steitz, J. A . The noncoding RNA revolution - Trashing old rules to forge new ones. Cell 157, 77 (2014).
2. Cable, J. et al. Noncoding RNAs: biology and applications—a Keystone Symposia report. Ann N Y Acad Sci 1506, 118 (2021).
3. Mortimer, S. A. , Kidwell, M. A. & Doudna, J. A . Insights into RNA structure and function from genome-wide studies. Nat Rev Genet 15, 469 (2014).
4. Yao, R.-W. , Wang, Y. & Chen, L.-L . Cellular functions of long noncoding RNAs. Nat Cell Biol 21, 542 (2019).
5. Wang, F. , Zuroske, T. & Watts, J. K . RNA therapeutics on the rise. Nat Rev Drug Discov 19, 441 (2020).