Marina Gorostiola Gonzalez
Marina is a PhD student at the division of Drug Discovery and Safety under the supervision of of Prof. Dr. Adriaan IJzerman, Prof.Dr. Gerard van Westen, and Dr. Laura Heitman. She works on artificial intelligence and structure-based approaches to characterize the role of selected membrane proteins in breast cancer.
Before I started a PhD a Leiden University, I studied Pharmacy at University of Salamanca (Spain), with an exchange program at the University of Malta. I finished my five-year Bachelor & Master program with honors in 2017 with a thesis on the use of computational tools to improve drug dosing in celiac patients in the department of Bio-Pharmaceutical Sciences. This was my first contact with computational drug research, but definitely not my last. After that, I decided to move to the Netherlands to do a research master in Bio-Pharmaceutical Sciences at Leiden University. Here, I focused on computational drug discovery, which led me to do a research project in the group of Prof.Dr. Gerard van Westen on screening of cancer mutations directed towards rational design of kinase inhibitors. Seeking industrial experience, I conducted a second research project at Galapagos NV in Mechelen (Belgium) in the Molecular Modeling & Design group, under the supervision of Dr. Bart Lenselink. My work there focused on the development of a 3D machine learning-based scoring function for kinase-ligand interactions. In 2019 I graduated Cum Laude from my master, having completed a full track for a computational drug discovery specialization, including several courses from Uppsala University (Sweden).
From December 2019, I am engaged in a PhD track at the Leiden Academic Centre for Drug Research (LACDR) in the division of Drug Discovery and Safety. My project is under the umbrella of the ONCODE institute for cancer research and is performed under the supervision of Prof. Dr. Adriaan IJzerman, Prof. Dr. Gerard van Westen, and Dr. Laura Heitman. Within my project, I will focus on artificial intelligence and structure-based approaches to characterize the role of selected membrane proteins in breast cancer. In this project, I will use data analysis tools in combination with structure-based methods (i.e. docking, molecular dynamics), as well as machine learning approaches, to rationalize the possibility of targeting such proteins in the context of cancer, which potentially could lead to novel oncology therapies.
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