Investigating Ligand-Mediated Conformational Dynamics of Pre-miR21: A Machine-Learning-Aided Enhanced Sampling Study

MicroRNAs (miRs) are short, noncoding RNA strands that
regulate
the activity of mRNAs by affecting the repression of protein translation,
and their dysregulation has been implicated in several pathologies.
miR21 in particular has been implicated in tumorigenesis and anticancer
drug resistance, making it a critical target for drug design. miR21
biogenesis involves precise biochemical pathways, including the cleavage
of its precursor, pre-miR21, by the enzyme Dicer. The present work
investigates the conformational dynamics of pre-miR21, focusing on
the role of adenine29 in switching between Dicer-binding-prone and
inactive states. We also investigated the effect of L50, a cyclic
peptide binder of pre-miR21 and a weak inhibitor of its processing.
Using time series data and our novel collective variable-based enhanced
sampling technique, OneOPES, we simulated these conformational changes
and assessed the effect of L50 on the conformational plasticity of
pre-miR21. Our results provide insight into peptide-induced conformational
changes and pave the way for the development of a computational platform
for the screening of inhibitors of pre-miR21 processing that considers
RNA flexibility, a stepping stone for effective structure-based drug
design, with potentially broad applications in drug discovery.