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Abstract

Anticancer peptides (ACPs) are polycationic amphiphiles capable of preferentially killing a widespectrum of cancer cells relative to non-cancerous cells. Their primary mode of action is aninteraction with the cell membrane and subsequent activation of lytic effects, however it remainscontroversial the exact mechanism responsible for this mode of action. It has in previous studies been shown that utilizing zeta potential analyses it was possible to demonstrate the interaction of a small anticancer peptide with membrane modelsystems and cancer cells. Electrostatic interactions have a pivotal role in the cell killing processand in contrast to the AMPs action cell death occurs without achieving full neutralization of themembrane charge. The advent of microarray technology has revolutionized the search for genes that are differentially expressed across a range of cell types or experimental conditions. Traditional clustering methods, such as hierarchical clustering, are often difficult to deploy effectively since genes rarely exhibit similar expression pattern across a wide range of conditions. Web-enabled service called GEMS (Gene Expression Mining Server) for biclustering microarray data where Users may upload expression data and specify a set of criteria.GEMS performs bicluster mining based on a Gibbs sampling paradigm. Here, in Biogenea we have for the first time discovered an Anticancer Peptide SVS-1 multipharmacophore with an ini silico evaluated Efficacy in Preceding Membrane Neutralization using a web server for biclustering analysis of expression data.

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) In silico designed of an Anticancer Peptide SVS-1 multipharmacophore as a potential drug-like efficator in Preceding Membrane Neutralization using a web server multi-mimotopic algorithmic approach for biclustering analysis of expression data.

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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