Implementation of machine learning and other simulation protocols for the representation of G-Quadruplex stabilizer

Abstract

Human chromosomal telomeres are capable of forming G-Quadruplex structures, which can inhibit the activity of telomerase, an enzyme commonly found in cancerous cells and largely responsible for their immortality. The inhibition may therefore lead to cell apoptosis in these cancer cells. As such, there have been growing interest in the research for G-Quadruplex stabilizers. This thesis focusses on the exploration and development of new representations for the structure-function relationship of G-Quadruplex-ligand biomolecular system using machine learning (ML) techniques. Two main models, namely