PhD in Bioinformatics And Computational Biology

This project investigates the impact of natural genetic variations on a specific G protein-coupled receptor (GPCR), focusing on its structure, function, and drug interactions. The goal is to contribute to personalized medicine approaches. The project begins with comprehensive data collection, compiling natural GPCR variants from pharmacogenomics databases and literature. You will then perform structural analysis by mapping these variants onto 3D receptor structures and analysing their potential impacts. Using bioinformatics tools, you'll predict the functional effects of these variants on the receptor. Throughout the project, you'll integrate your computational predictions with existing clinical data from literature. Selected variants will be experimentally validated through mutagenesis and cell-based functional assays. Throughout this process, you'll develop a diverse skill set including cutting-edge computational approaches like data mining, molecular dynamics simulations, and cheminformatics. You'll also gain experience with state-of-the-art functional assays, bioinformatics, structural biology analysis, literature review, and data integration. This interdisciplinary work will enhance understanding of how genetic variations influence drug responses in GPCRs, potentially informing future personalized medicine strategies. The project bridges the gap between computational predictions and biological reality, providing you with a well-rounded experience applicable to drug design research in both academia and industry.