SMEpred workbench: A web server for predicting efficacy of chemicallymodified siRNAs

Abstract

Chemical modifications have been extensively exploited to circumvent shortcomings in therapeutic applications of small interfering RNAs (siRNAs). However, experimental designing and testing of these siRNAs or chemically modified siRNAs (cm-siRNAs) involves enormous resources. Therefore, in-silico intervention in designing cm-siRNAs would be of utmost importance. We developed SMEpred workbench to predict the efficacy of normal siRNAs as well as cm-siRNAs using 3031 heterogeneous cm-siRNA sequences from siRNAmod database. These include 30 frequently used chemical modifications on different positions of either siRNA strand. Support Vector Machine (SVM) was employed to develop predictive models utilizing various sequence features namely mono-, di-nucleotide composition, binary pattern and their hybrids. We achieved highest Pearson Correlation Coefficient (PCC) of 0.80 during 10-fold cross validation and similar PCC value in independent validation. We have provided the algorithm in the 'SMEpred' pipeline to predict the normal siRNAs from the gene or mRNA sequence. For multiple modifications, we have assembled 'MultiModGen' module to design multiple modifications and further process them to evaluate their predicted efficacies. SMEpred webserver will be useful to scientific community engaged in use of RNAi-based technology as well as for therapeutic development. Web server is available for public use at following URL address: http://bioinfo.imtech.res.in/manojk/smepred .

Keywords: Chemically modified siRNA; RNAi; cm-siRNAs; efficacy prediction; siRNA; siRNA modifications; small interfering RNA; webserver.

Figure 1.

Diagramatic representation of of SMEpred workbench development and its components.

Figure 2.

Scatter plot of percentage activities between actual and predicted chemically modified siRNA activities from independent validation data set Hetero-V³⁰³. (A) Model-A; Mononucleotide nucleotide composition (MNC); (B) Model-B; Composition (MNC) and antisense strand binary (5′-end 13 nucleotides); (C) Model-C; Composition (MNC) and antisense strand binary (3′-end 8 nucleotides).

Figure 3.

Pictorial representation of working of SMEpred pipeline. (A) Write or paste the gene or mRNA sequence in the space provided, in fasta format and click submit button. (B) Normal siRNAs that are 21-mer long nucleotides are generated from the provided sequence along with their predicted efficacy scores. (C) Further select one of the siRNA (by clicking on it) and it will redirect to the next page with 1260 cm-siRNA. This page displays cm-siRNA sequence, chemical modification highlighted in the red color predicted efficacy and value of modulated efficacy.