Modeling environment effects on spectroscopic properties of biomarkers and catalytic mechanisms in enzymes
Time: Wed 2020-02-12 13.00
Subject area: Theoretical Chemistry and Biology
Doctoral student: Camilla Gustafsson , Teoretisk kemi och biologi, Tillämpad fysikalisk kemi, Royal Institute of Technology
Opponent: Assistant Professor Daniel Escudero, KU Leuven, Department of Chemistry
Supervisor: Professor Patrick Norman, Teoretisk kemi och biologi
Arguably, humans are in need of both better diagnostic tools to prevent pro- gression of diseases as well as greener catalysts for synthesis of chemicals.
Neurodegenerative diseases affecting neurons in the brain leads to demen- tias, where Alzheimer’s disease (AD) is the most prevalent. It is estimated that about 50 million people worldwide suffer from AD, a number that has more than doubled during the last 30 years. Currently, there is no cure for AD, but in order to slow the progression of symptoms it is crucial to develop biomarkers for early detection and initiation of clinical interventions.
With theoretical tools it is possible to better understand the optical prop- erties of fluorescent biomarkers, and thus contribute to steering the design of biomarkers for distinguishing different types of disease-associated proteins. Lu- minescent conjugated oligothiophenes (LCO) is a class of molecules that binds to aggregates of misfolded amyloid-β proteins, facilitating in vivo-detection of the pathological hallmarks of AD. By performing molecular dynamics (MD) simulations and subsequent response theory calculations of a LCO, it could be concluded that the differences in the spectroscopic fingerprints for the bound and free biomarker were predominantly due to conformational changes of the conjugated π-system in the molecular backbone. The introduction of differ- ent central units with donor properties yield donor-acceptor-donor electronic systems that increase the range of spectroscopic detection of LCO biomark- ers, without reducing the selectivity towards amyloid-β. It was also revealed that in order to capture more of the two-photon absorption (TPA) signal it would be optimal to design biomarkers with the dominant TPA signal at longer wavelenghts.
The second part of this work is centered around computational enzyme design, and how single point mutations can alter the flow of water in the active site. The altered flow of water likely impacts the catalysis in the active site of the enzymes. The enzymes considered in this work belongs to two different enzyme classes, and catalyse different kinds of reactions. Squalene hopene cyclase (SHC) is a monotopic membrane enzyme that catalyses the cyclization of squalene to hopene, and ω-transaminase catalyses the transfer of an amino and keto group between an amino acid and a keto acid. Enzyme variants of both SHC and ω-transaminase, where single-point mutations have been introduced, display different experimentally observed properties compared to their corresponding wild-types (WT). By performing MD simulations, the flow of water in the active sites of both enzymes could be tracked. Distinct differences in the flow of water in the WT and enzyme variants could be detected. These changes are proposed to influence the catalysis, and help to explain the experimentally observed differences in the protein variants.