Differential Scanning Fluorimetry (DSF) Methods for Studying Protein Stability

点击翻译按钮获取中文摘要

Abstract. There is great interest in technologies that measure protein stability, because many devastating diseases (e.g. cystic fibrosis, Alzheimer’s disease) are linked to protein misfolding and instability. One especially promising way to treat these diseases is to use small molecules, termed “correctors” that bind to the damaged protein and partially restore its folding. Multiple correctors have received FDA approval (e.g. ivacaftor, tafamadis, migalastat), but there are hundreds of additional misfolding diseases. What are the hurdles to the rapid discovery of additional correctors? One important barrier is that previous correctors have been uncovered through prolonged searches, using specialized (i.e. target-specific) technologies that are not versatile enough for use across many proteins-of-interest (POIs). Here, we propose next-generation Differential Scanning Fluorimetry (DSF) to fill this gap. In a typical DSF experiment, a POI is heated in a qPCR instrument and its un-folding is monitored by its binding to a solvatochromatic dye (e.g. Sypro Orange, SO). The resulting temperature vs. fluorescence curves are then used to estimate the melting transition (Tm), with putative correctors identified by their effect on this value (DTm). DSF is versatile because it does not require protein labeling or structural knowledge. Moreover, unlike comparable platforms, such as circular dichroism (CD) or differential scanning calorimetry (DSC), DSF is amenable to 384-well plate format, facilitating large-scale chemical screens. While DSF has the potential to transform corrector discovery, there are major hurdles to overcome. For example, DSF often fails because SO does not bind the target protein or it binds to hydrophobic patches on the native state, obscuring the Tm. Further, for some POIs, the temperature-fluorescence curves are complex, with multiple transitions, and therefore not readily analyzed or fit using standard equations. Based on our preliminary screens of ~50 different proteins, these issues cause DSF to fail in more than 60% of cases. We propose to solve these issues through disruptive innovations: (SA1) Design and synthesis of next-generation dye libraries that significantly expand the scope of DSF and (SA2) Theory- and experiment-driven, dramatic improvements in data analysis, enabled by machine learning and made publicly available through a web portal (DSFWorld). Encouraged by preliminary success, we also propose to: (SA3) Expand the scope of DSF applications by pioneering studies of multi-protein complexes and conformational changes. Importantly, we will benchmark each of these innovations against current state-of-the-art approaches, with a focus on a critical understanding of strengths and weaknesses. Together, these studies are expected to dramatically expand the scope of DSF technology.