Analysis on the in-silico ensemble methods for 3D modelling of ssDNA aptamers.

Biophys Chem

Department of Biosciences and Bioengineering, Indian Institute of Technology Guwahati, Assam 781039, India. Electronic address:

Published: December 2023

Understanding the 3-D structure of nucleic acid aptamers is important for the rational design of aptamer-based constructs in various applications, including for developing aptasensors. Herein, a simple approach for 3D modelling of ssDNA aptamers through an ensemble of web applications has been described. The procedure utilized 30 aptamers whose 3D XRD or NMR experimental structures are available for validation. As a first step, the primary sequences of ssDNA aptamers were transformed into 2D structures using six widely used web applications: RNA fold, Vector builder, RNA Structure, UNA fold, Centroid fold, and IP Knot. The generated 2D structures were then passed through the RNA composer web application to generate 3D RNA structure, which in turn was converted to 3D DNA structures using various Visual Molecular Dynamics web applications that also include conversion of ribose sugar into deoxyribose sugar backbone and uracil to thiamine. The energy-minimized generated 3D structures were matched well with high accuracy to their experimental counterparts. This study identified that the Guanine residues are crucial in the aptamer 3D structure prediction and in algorithms that generate secondary structures. Further, the GC content (<50%), GC bond percentage (<60%), and G:C ratio (<1.12) act as limiting factors in predicting the 2D structures of aptamers. There were variations in the 2D structure predictions by the web applications, even though all these applications were a combination of the MFE, MEA, and McCaskill functions. Processing these structures through the web applications described above produced best-fit 3D structures with the experimental one, thus offering the present ensemble approach to reliably predict the 3D structure of aptamers for various applications.

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http://dx.doi.org/10.1016/j.bpc.2023.107111DOI Listing

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