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Abstract

Extracting useful information from large data sets can be a daunting task. Topological methods for analysing data sets provide a powerful technique for extracting such information. Persistent homology is a sophisticated tool for identifying topological features and for determining how such features persist as the data is viewed at different scales. 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 identified by Oncolytic virus potential Quantum algorithms for topological and geometric analysis of an in silico rational designed adenovirus library displaying random peptide-mimic pharmacophoric ligand supressor comprising viral naive tropism replication-competent pancreatic cancer therapeutic properties.

Keywords

Quantum algorithms, topological, geometric, analysis, in silico, rational, adenovirus library, displaying, random, peptide-mimic, pharmacophoric, ligand, supressor, vira,l naive, tropism, comprising, replication-competent, Oncolytic, virus, potential, therapeutic, properties pancreatic, cancer.

Article Type

Research Article – Abstract

Publication history

Received: Sep 20, 2017
Accepted: Sep 25, 2017
Published: Oct 01, 2017

Citation

Grigoriadis Ioannis, Grigoriadis George, Grigoriadis Nikolaos, George Galazios (2017) Oncolytic virus potential Quantum algorithms for topological and geometric analysis of an in silico rational designed adenovirus library displaying random peptide-mimic pharmacophoric ligand supressor comprising viral naive tropism replication-competent pancreatic cancer therapeutic properties.

Authors Info

Grigoriadis Nikolaos
Department of IT Computer Aided Personalized Myoncotherapy, Cartigenea-Cardiogenea, Neurogenea-Cellgenea, Cordigenea-HyperoligandorolTM,
Biogenea Pharmaceuticals Ltd,
Thessaloniki, Greece;

Grigoriadis Ioannis
Department of Computer Drug Discovery Science, BiogenetoligandorolTM,
Biogenea Pharmaceuticals Ltd,
Thessaloniki, Greece;

Grigoriadis George
Department of Stem Cell Bank and ViroGeneaTM,
Biogenea Pharmaceuticals Ltd,
Thessaloniki, Greece;

George Galazios
Professor of Obstetrics and Gynecology,
Democritus University of Thrace,
Komotini, Greece;

E-mail: biogeneadrug@gmail.com

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