Uppsala Computational Biochemistry Initiative
Title: Uppsala Computational Biochemistry Initiative
DNr: NAISS 2023/3-5
Project Type: NAISS Large Compute
Principal Investigator: Hugo Gutierrez de Teran <hugo.gutierrez@icm.uu.se>
Affiliation: Uppsala universitet
Duration: 2024-01-01 – 2025-01-01
Classification: 10407 10602 10603
Homepage: https://sites.google.com/view/ucbinitiative/home


Over the past decades, computers have played an ever-increasing role in elucidating complex biochemical processes, with constant progress in the scope of the problems that can be addressed. Research at the Uppsala Computational Biochemistry Initiative (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. As some examples, our activities are centered on (but not limited to) the following four topics: (i) Elucidating the mechanisms of biological catalysis and studying protein evolution / design. (ii) New strategies for chemical modulation of G-protein coupled receptors (GPCRs) and other transmembrane proteins. Methodological developments for (iii) structure-based ligand design, and (iv) dissecting protein allostery. To address these problems, we develop and apply different computational approaches for the characterization of the energetics and dynamics of various biochemical processes, including: the thermodynamics of ligand binding, the catalytic activity of enzymes, or the thermal stability of proteins. Here, quantifying energetics through simulation is crucial, as it provides the most important link between structure and function, allowing the 3D structures of biological systems of interest to be directly translatable to physical properties such as reaction rates and equilibrium constants. The insight this provides can then in turn be used to manipulate the properties of biological systems, from developing new drugs to target malfunctioning signaling pathways, to the development 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.