A computational approach to identify efficient RNA cleaving 10-23 DNAzymes

Abstract

DNAzymes are short pieces of DNA with catalytic activity, capable of cleaving RNA. DNAzymes have multiple applications as biosensors and in therapeutics. The high specificity and low toxicity of these molecules make them particularly suitable as therapeutics, and clinical trials have shown that they are effective in patients. However, the development of DNAzymes has been limited due to the lack of specific tools to identify efficient molecules, and users often resort to time-consuming/costly large-scale screens. Here, we propose a computational methodology to identify 10-23 DNAzymes that can be used to triage thousands of potential molecules, specific to a target RNA, to identify those that are predicted to be efficient. The method is based on a logistic regression and can be trained to incorporate additional DNAzyme efficiency data, improving its performance with time. We first trained the method with published data, and then we validated, and further refined it, by testing additional newly synthesized DNAzymes in the laboratory. We found that although binding free energy between the DNAzyme and its RNA target is the primary determinant of efficiency, other factors such as internal structure of the DNAzyme also have an important effect. A program implementing the proposed method is publicly available.

Figure 1.

The structure of the 10–23 DNAzyme with 9 nt substrate binding arms. RNA transcript that acts as substrate is the top strand with an RY cleavage site (R represents A or G and Y is C or U). Arms I and II are the substrate binding arms that complement the RNA via Watson–Crick base pairing.

Figure 2.

Efficiency and free energy of DNAzyme/RNA interactions. Scatter plot of the ΔG (free energy) of the interaction between published DNAzyme and their putative RNA targets and the efficiency measured in the lab and percent of degraded subtract after 60 min.

Figure 3.

Logistic fitted lines for energy features versus successful cleavage. (A) ΔG (free energy) of the DNAzyme–RNA interaction against cleavage success using a threshold of 20% of efficiency. (B) As panel (A) but using a threshold of 40%. (C) Internal free energy of the DNAzyme molecule versus success. (D) Homodimer formation free energy versus success. Color code as in Figure 1 panel.

Figure 4.

Overview of the proposed computational method. This cartoon provides a graphic summary of the process used to identify DNAzymes as described in the main text (see Results for details).