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Figure 1. Visualization of 3D models by YASARA. Left: mir-135b, Right: mir-135b’s siRNA. The YASARA Visualization Tool (Krieger & Vriend, 2014) was utilized to visualize the 3D model of mir-135b and its siRNA obtained from RNAComposer (Fig. 1). YASARA was chosen due to its compatibility with most forms of PDB files, including nucleotide 3D structure format. The data restriction to only RNA inputs prevent- ed the de novo models from binding to other proteins.

Figure 1 Visualization of 3D models by YASARA. Left: mir-135b, Right: mir-135b’s siRNA. The YASARA Visualization Tool (Krieger & Vriend, 2014) was utilized to visualize the 3D model of mir-135b and its siRNA obtained from RNAComposer (Fig. 1). YASARA was chosen due to its compatibility with most forms of PDB files, including nucleotide 3D structure format. The data restriction to only RNA inputs prevent- ed the de novo models from binding to other proteins.

Related Figures (4)

Figure 2. RNA-RNA interaction of mir-135b and its siRNA visualized from RILogo Web Server. Intramolecular reaction is shown in blue-colorec arcs. Figure 3. mir-135b and its siRNA best docking conformation viewed from AutoDockTools. Purple-red: mir-135, Blue-red: mir-135b’s siR- NA.
Figure 2. RNA-RNA interaction of mir-135b and its siRNA visualized from RILogo Web Server. Intramolecular reaction is shown in blue-colorec arcs. Figure 3. mir-135b and its siRNA best docking conformation viewed from AutoDockTools. Purple-red: mir-135, Blue-red: mir-135b’s siR- NA.
eral being highly unstable. The docking analysis was run 10 times to make sure all the possible bind- ings/interactions between the 2 molecules. Results showed a consensus cluster conformation from all 10 runs [Fig. 3] meaning the parameters chosen were enough to provide accurate results (Morris & Lim-Wilby,
eral being highly unstable. The docking analysis was run 10 times to make sure all the possible bind- ings/interactions between the 2 molecules. Results showed a consensus cluster conformation from all 10 runs [Fig. 3] meaning the parameters chosen were enough to provide accurate results (Morris & Lim-Wilby,
ergy while negative binding energy is usually preferred (Table 1). In AutoDock4, high or positive binding ener- gy is interpreted as reversible and non-permanent inter- action. In this regard, the negative binding energy or high energy score is catered for a permanent interaction be- tween siRNA and mir-135b. Figure 4. PatchDock result of mir-135b and its siRNA visualized using AutoDockTools. Large molecule: mir-135b, small molecule highlight- ed yellow: mir-135b’s siRNA.
ergy while negative binding energy is usually preferred (Table 1). In AutoDock4, high or positive binding ener- gy is interpreted as reversible and non-permanent inter- action. In this regard, the negative binding energy or high energy score is catered for a permanent interaction be- tween siRNA and mir-135b. Figure 4. PatchDock result of mir-135b and its siRNA visualized using AutoDockTools. Large molecule: mir-135b, small molecule highlight- ed yellow: mir-135b’s siRNA.
Table 1. Summary of AutoDockTools docking results ranked based on binding energy values.
Table 1. Summary of AutoDockTools docking results ranked based on binding energy values.
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BioinformaticsStructural BioinformaticsncRNAs, miRNAs
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