A conditionally replicative adenovirus is a novel anticancer agent designed to replicate selectively in tumor cells. However, a leak of the virus into systemic circulation from the tumors often causes ectopic infection of various organs. Therefore, suppression of naive viral tropism and addition of tumor-targeting potential are necessary to secure patient safety and increase the therapeutic effect of an oncolytic adenovirus in the clinical setting. It has also recently been developed a direct selection method of targeted vector from a random peptide library displayed on an adenoviral fiber knob to overcome the limitation that many cell type-specific ligands for targeted adenovirus vectors are not known. In previous studies it has also been further examined whether the addition of a tumor-targeting ligand to a replication-competent adenovirus ablated for naive tropism enhances its therapeutic index. Structure-based drug design is an iterative process, following cycles of structural biology, computer-aided design, synthetic chemistry and bioassay. In favorable circumstances, this process can lead to the structures of hundreds of protein-ligand crystal structures. In addition, molecular dynamics simulations are increasingly being used to further explore the conformational landscape of these complexes. Currently, methods capable of the analysis of ensembles of crystal structures and MD trajectories are limited and usually rely upon least squares superposition of coordinates. Novel methodologies are described for the analysis of multiple short linear motif like peptide structures of a protein-drug active binding conserved site. Statistical approaches that rely upon residue equivalence, but not superposition, are developed as chemogenomic informatic tasks can be performed includinig the identification of hinge regions, allosteric conformational changes and transient binding sites. Here, we have for the first time discovered an in silico rational designed adenovirus library displaying random peptide-mimic pharmacophore comprising Oncolytic virus therapeutic promising properties for pancreatic cancer using a KNIME-based BiogenetoligandorolTM directed polyphony superposition independent method for ensemble-based drug discoveries.