* in order of percentage of time on the project
Dr. Zoran Štefanić senior research associate and Head of the Laboratory for Chemical and Biological Crystallography at the Ruđer Bošković Institute. His main areas of expertise include: chemical crystallography of small organic molecules and hydrogen bonded networks, macromolecular crystallography, strong background in physics and mathematics, development of computer algorithms mainly in Python programming language, database design and web development. As the principal investigator of the proposed project, he will be responsible for the overall coordination of the research and managing all activities between team members, organizational and financial matters, as well as for the publication of results, annual scientific and financial reports to the Croatian Science Foundation. More specifically in this project his tasks will be data collection and 3D structure determination of new enzyme structures, development of central relational database, programming of algorithms for data extraction, development of web server, and co-mentorship of PhD student.
Is a PhD student and a member of the Laboratory for Chemical and Biological Crystallography at the Ruđer Bošković Institute. His main areas of expertise include biochemistry and enzyme kinetics, molecular dynamics with strong background in biochemistry and molecular biology. As collaborator on the proposed project he will be responsible for crystallization trials and further biophysical characterization of AdSS protein, and MD simulations part of the project.
Full professor at Faculty of Electrical Engineering and Computing, University of Zagreb. Her research interests involve artificial intelligence, machine learning, multivariate statistics and visualisation, text analysis and information retrieval. She is one of the pioneers who introduced the discipline of machine learning in Croatian scientific community. In the proposed project her main role will be to choose the most appropriate set of machine learning techniques to apply to the data in the central relational database and their application to extract allosteric communication pathways. This will also involve mentoring of the PhD student in her/his thesis work on this subject.