Uppsala Computational Biochemistry Initiative
Title: Uppsala Computational Biochemistry Initiative
SNIC Project: SNIC 2013/26-1
Project Type: SNAC Large
Principal Investigator: Lynn Kamerlin <kamerlin@icm.uu.se>
Affiliation: Uppsala University
Duration: 2014-01-01 – 2015-01-01
Classification: 10407 10602 10603
Homepage: http://xray.bmc.uu.se/kamerlin


The Uppsala Computational Biochemistry Initiative (UCBI) is a rapidly expanding initiative at Uppsala University, comprising, at present, two principal investigators, six postdocs, and ten PhD students, as well as assorted short- and long-term visitors to the initiative. Research at UCBI focuses on computational analysis, simulation and the prediction of biomolecular function and interactions based on 3D structural information, as well as the development of methodology for these purposes. Our methodological interests lie predominantly in developing approaches for accurate evaluation of solvation and entropic effects, free energy calculations, binding calculations, and accelerated ab initio QM/MM applications. The applications of this methodology centers on four themes: (i) elucidating the mechanisms of biological catalysis, (ii) computational protein evolution, (iii) transmembrane ion channels and G-protein coupled receptors (GPCRs) and (iv) structure-based ligand design and molecular recognition. Here, our emphasis on obtaining correct energetics is crucial, as this provides the most direct and important link between structure and function, allowing the macromolecular 3D structures of biological systems to be directly translatable to physical properties, such as reaction rates and equilibrium constants. The insight we obtain from this can then be used to manipulate the properties of biological systems, from the development of new drugs to the design of novel enzymatic biocatalysts. Finally, the approaches we develop can be seamlessly integrated with higher-level bioinformatics and systems biology approaches, providing indispensable tools for translating biomolecular structure into function.