Toward Development of Novel Peptide-Based Cancer Therapeutics: Computational Design and Experimental Evaluation

Abstract

Drug research and discovery are of critical importance in human health care. Computational approaches for drug lead discovery and optimization have proven successful in many recent research programs. These methods have grown in their effectiveness not only because of improved understanding of the basic science, the biological events and molecular interactions that define a target for therapeutic intervention, but also because of advances in algorithms, representations, and mathematical procedures for studying such processes. Advances in genomics and proteomics and development of new bioinformatics methods contribute greatly to the process of rational drug design, which can be a cost-effective solution to drug discovery. Peptides are emerging as a novel class of drugs for cancer therapy, and many efforts have been made to develop peptide-based pharmacologically active compounds. In this study, we present and discuss three novel bioactive peptide ­analogues, designed using the Resonant Recognition Model (RRM), and discuss their biological effects on normal and tumor cells from mouse and human origins.