Novel and simple simulation method to design and development of antisense template

Antisense technology is emerging as potential therapeutics against lethal infections. Basically, Antisense-mRNA complex inhibits the protein translation of pathogens and thus it is used for treatment. Based on previous online tools and literatures and difficulties for designing antisense template, finding high conserved regions from large number of long sequences, by taking all those factors in consideration, we proposed new innovative offline target simulation methods i.e. Deletion of unwanted region from viral sequence alignment (DURVA) and Most frequent region (MFR) for designing and developing antisense template from large number of long sequence or genomic data. Based on current pandemic crisis and long genomic sequence of SARS-CoV-2, we chose coronavirus for simulation. Initially, we hypothesized that DURVA-MFR would find stable region from large annotated sequencing data. As per Chan et.al. guidelines for antisense designing and development, we designed couple of algorithms and python scripts to process the data of approximately 30kbp sequence length and 1Gb file size in short turnaround time. The steps involved were as: 1) Simplifying whole genome sequence in single line; 2) Deletion of unwanted region from Virus sequence alignment(DURVA); 3)Most frequent antisense target region(MFR) and 4)Designing and development of antisense template. This simulation method is identifying most frequent regions between 20-30bp long, GC count[≥]10. Our study concluded that targets were highly identical with large population and similar with high number of remaining sequences. In addition, designed antisense sequences were stable and each sequence is having tighter binding with targets. After studying each parameter, here we suggested that our proposed method would be helpful for finding best antisense against all present and upcoming lethal infection.The initial design of this logic was published in Indian Patent Office Journal No.08/2021withApplication number202121005964A. Simple summaryThe antisense development is state of the art for modern therapeutics. There are number of online soft-wares and open sources for designing of antisense template. But all other tools did not consider frequency as major factor for designing antisense. Also; all sources excepting our simulation approach does not process large file or long sequences. Therefore; we designed an offline innovative simulation method which deletes the unwanted region from sequences and stores the data which are fulfilled antisense criteria. Further; the calculation of frequency from these short listed target regions; the most frequent region is desire antisense target and further antisense template will be designed according to Watson-Crick model. This article explained all information about how our new approach is best for designing antisense template against SARS-CoV-2 and many lethal infectious viruses etc.