Generation of 3D models of miRNA implicated in
interactions with NCL
Structural information of miRNA molecules implicated to play a role in
breast cancer (Supporting Table S4 ) and interact with NCL is
unavailable in the databases. The limited structural data available in
the protein databank for the 6 miRNA molecules under study corresponds
to either partial pre-miRNA structures or apical loops (PDB ID: 2MNC,
5UZT) [77,78] and neither provide structural information for the
complete pri-miRNA structures. Therefore, all pri-miRNA molecules were
modeled using the primary sequences of miRNA stem loop structures
obtained from miRbase [79]. The secondary structure of these miRNA
molecules was predicted using various programs including RNAStructure
[80], RNAFold [81], MC-Fold [82], CentroidFold [83], and
SPOT-RNA[84]. Although all these tools provide predictions based on
experimental data found in databases, some of the newer methods such as
CentroidFold and SPOT-RNA also utilize machine learning in making these
predictions. All of the predicted secondary structures (dot bracket
format) obtained from these tools were input into the RNA modeling
software including RNAComposer [85], ifold2 [86], RNAfold3
[87], 3DRNA v2 [88] and simRNAweb [89] to obtain 3D models
of these miRNA molecules. The generated models were evaluated for their
structural quality using MolProbity [90] (Supporting Table
S3 ). The top models were refined using RNAfitme [91], a program
that reconstructs nucleobases and nucleosides while keeping the sugar
phosphate backbone fixed and aiming to reduce steric clashes.