Computer-Aided Design Of Antisense Oligonucleotides

AntisenseOligonucleotides Technology is a important tool for gene silencing and gene therapy. It is a bottleneck to select optimal target sites due to complicated factors influence. However, it is widely thought that Local structures of target mRNAs play a significant role in determining the efficacies of antisense oligonucleotides (ASONs), but some structure-based target site selection methods are limited by uncertainties in RNA secondary structure prediction. The study focus on the rational design of antisense oligonucleotides based on the multiple predicted target mRNA structures, all the predicted structures of a given mRNA within a certain energy limit could be used simultaneously,target site selection would obviously be improved in both reliability and efficiency.AOBase which contains -700 ASONs targeting to 46 mRNAs prepare the datasets for the computer-aided design. Secondary structures of target mRNAs are folding by MFOLD, two representations (SSPP and SUP) of mRNA structure are used to integrate not more than fifty structures within 5 percent of the computed minimum free energy. After correlation analysis, parameters selected serve as the input to Neural network and "minus-one-gene" method is used to cross-validate. A tool, named AODesigner, was developed to predict the ASONs which based on our new algorithm. At last, we selected key genes involved in the drug against HBV's infection pathway to test the tool by means of experiments.The results, that eighteen features-seven from SSPP representation and eleven from SUP representation-was carried out with correlation analysis on a dataset with 448 ASONs against 28 different mRNAs, revealed 9 features quantitatively associated with efficacy. Features of structural consistency seemed to be more highly correlated...