X-Ray Crystallography, Fluorescence, and Molecular Simulations Studies on Regulators of SERCA

Abstract

X-ray crystallography was used to solve the structure of the sarco/endoplasmic reticulum Ca-ATPase (SERCA) in complex with a novel small-molecule inhibitor (CXL017) that targets multidrug-resistant leukemia. The structure, solved at 3.0Å resolution, reveals CXL017 bound at a new site that is distinct from those of other known inhibitors of SERCA. This new site is near the ATP binding site, and suggests blockage of the phosphorylation site as the main mechanism of inhibition. This inhibitor binding site explains the synergistic relationship previously uncovered between CXL017 and other SERCA inhibitors. Identifying a novel inhibitor binding site provides insights for structure-guided improvements of this new class of potential anti-cancer agents. Molecular modeling and simulation, in combination with fluorescence spectroscopy, was used to generate new structural and mechanistic models that better describe the conformational landscape and regulation of SERCA by phospholamban (PLB) and sarcolipin (SLN). Fluorescence spectroscopy, including fluorescence resonance energy transfer (FRET) between fluorescent-fusion-protein constructs of SERCA, provided structural dynamics information about the cytosolic headpiece of SERCA and also on its interaction with regulatory peptides. Simulations were performed to sample conformations of fusion protein constructs, CFP-SERCA, YFP-PLB and YFP-SLN. The simulations were based on crystal structures of SERCA/PLB and SERCA/SLN complexes. FRET parameters, such as the inter-probe distance, RDA, and the orientation factor κ2 were calculated from simulations and used to generate predictions of fluorescence lifetimes and FRET efficiency distributions that were compared with experimental data. Based on these results, we propose a model of a super-inhibitory complex of SERCA, in which SERCA first binds SLN and then binds PLB. Spectroscopic studies were performed at the Biophysical Technology Center and computational work at the Minnesota Supercomputing Institute. This work was funded by NIH grants to DDT (GM27906 and AR07612).