@article{open2564,
           month = {April},
           title = {Computer-aided designing of oncolytic viruses for overcoming translational challenges of cancer immunotherapy.},
          author = {Anjali  Lathwal and Rajesh  Kumar and G.P.S. Raghava},
       publisher = {Elsevier Science},
            year = {2020},
            note = {Copyright of this article belongs to Elsevier Science.},
         journal = {Drug discovery today},
             url = {http://crdd.osdd.net/open/2564/},
        abstract = {Wild-type and genetically engineered oncolytic viruses (OVs) represent powerful therapeutic agents in cancer immunotherapy. Several OV species are in clinical trials for cancer treatment. Preclinical and clinical trials revealed several issues related to OV therapy in terms of viral delivery, spread, antiviral immune response, and tumor resistance. Here, we suggest some promising computational strategies that can overcome these issues. The strategies include predicting and prioritizing tumor-homing peptides, anticancer peptides, neoantigens, and miRNA response elements in the viral genome. The combination of computational approaches with genetic engineering could enhance the safety, delivery, oncolysis, and antitumor immune responses of OVs.}
}