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Small molecule drug discovery is strongly supported by biophysical data. In the reach of this thesis, cell free protein expression was used to produce human target proteins for ligand binding assays using Surface Plasmon Resonance spectroscopy (SPR). In the second step the binding and interaction characteristics of small molecules and fragments were analyzed using Nuclear Magnetic Resonance spectroscopy (NMR).
The first target protein was the human acid sensing channel 1 (ASIC1a). ASIC1a was expressed in a cell free expression system based on E.coli lysate. To optimize the expression, several parameters including fusion tags, ion concentrations and different hydrophobic environments were tested.
The adaption of the folding environment for ASIC1a needed more optimization, because it is a very challenging target to express in an in vitro system. Three different expression modes were employed to find a suitable folding environment.
SPR binding studies with ASIC1a were performed with chicken ASIC1a expressed in insect cells. The immobilization of cASIC1a and the used buffer conditions were tested using Psalmotoxin 1, a naturally occurring peptide venom which binds strong to the trimeric form of ASIC1a. Compound characterization experiments were performed with a variety of different ligands including amiloride, a general blocker of the whole ENaC protein family. None of the used ligands showed titration curves that would match a simple 1:1 binding model. The experiments either show no binding signal or signal that could be interpreted as unspecific binding. Even amiloride that should be binding the protein shows no signals that fit a simple binding model.
Another target protein that was investigated is the soluble prolyl cis/trans isomerase Cyclophilin D (or peptidyl prolyl isomerase F – PPIF). This protein is involved in the regulation of the mitochondrial permeability transition pore and therefore a potential drug target to treat neurodegenerative diseases. Small molecule binding was tested with CypD using SPR. Following the kinetic analysis of small molecule ligands, the binding position of different binding fragments was analyzed. These fragments originated from a SPR based fragment screen and gave no co-crystal structures with CypD. Therefore NMR was used to investigate the binding position of these fragments. An analysis of the chemical shift perturbations upon ligand addition revealed that the NMR analysis was in line with the results gathered by x-ray crystallography. The fragments with unknown binding position however, all bind to a specific patch slightly outside the binding pocket.
The ligand CL1 showed a special behavior in the NMR experiments. Upon addition to CypD, it produced large shifts on many signals of the protein, accompanied by a severe line broadening. The shift perturbations were so numerous and large that the spectrum had to be reassigned in complex with the ligand. Triple selective labeling was applied to allow a fast and nearly complete signal assignment. The possibility to use highly sophisticated labeling schemes, is one of the advantages of cell free protein expression. After the assignment of the complex spectrum, the chemical shift perturbations were analyzed and quantified. The residues showing the strongest CSPs are also identified in the crystal structure to be involved in the binding of CL1, giving a consistent picture. The numerous and large shift perturbations, produced by CL1 led to the assumption, that the ligand induces a conformational change in CypD, which is not represented in the co-crystal structure. This conformational change was characterized by a NMR based structure determination. CypD apo yielded a defined bundle, whose folded regions overlap well with the corresponding crystal structure.
For the calculation of the CypD-CL1 complex structure, the sidechain resonances were assigned using an automated assignment approach with the software FLYA. The calculation of the CypD-CL1 complex structure did not result in a defined bundle. While parts of the protein converge in a well folded state, the region around the active site shows no defined folding. Careful analysis of the structure calculation suggests that the problems during structure calculation did not originate from an incorrect resonance assignment, but rather from a lack of NOE crosspeaks. This might be due to a broadening of the corresponding NOE crosspeaks or the coexistence of many different conformations. This leads to the conclusion, that the protein conformation is not defined by the NMR data and could be in a dynamic interchange between multiple structures.
This hypothesis is supported by other observations. The line broadening of the signals in the complex is pronounced in the area around the active site and the substrate binding pocket, hinting to a connection between catalytic activity and protein dynamics. In addition many NMR signals are sensitive to changes in the measurement field strength and the temperature. This field dependent signal splitting suggests dynamic conformational changes in the protein between at least two different conformations on a millisecond timescale.
The current working model is that CL1 binds to CypD and induces the catalytic cycle and the connected conformational changes in CypD. As a result the proline like moiety in CL1 is constantly switching between the cis and the trans conformation. Due to the high affinity of CL1, the inhibitor does not leave the binding pocket after successful catalysis, but stays bound in the pocket stimulating further catalytic cycles. These findings as well as the working model are well in line with data published for Cyclophilin A, another member of the cyclophilin family, thereby supporting the model.
The knowledge of three-dimensional structures of biomolecules is fundamental for the understanding of their function. Nuclear magnetic resonance (NMR) spectroscopy represents besides X-ray crystallography one of the two most widely used techniques to study macromolecules at atomic resolution. Its application has long been a laborious task that could take months and required the expertise of an experienced scientist, however, owing to the tremendous effort that has been put into the development of respective computer algorithms, structure determination by NMR spectroscopy of small- to medium sized proteins is nowadays routinely performed. CYANA is one widely used software package, which combines the majority of individual steps towards a three-dimensional structure. The most common application of the program, however, restricts to the combined automated NOE assignment and structure calculation based on NOESY peak lists and an existing chemical shift assignment. Completely automated structure determination starting from NMR spectra is to date technically possible with CYANA, however, not yet routinely applied. In order to achieve this long-term goal, the individual steps need to become more robust with regard to data imperfections such as peak overlap, spectral artifacts or a limited amount of NMR data. The work presented in this thesis should be placed within the context of increasing the reliability and improving the accuracy of structures determined by CYANA on the basis of solution- as well as solid-state NMR data.
The chapter “Systematic evaluation of combined automated NOE assignment and structure calculation with CYANA” comprises an extensive study on the robustness of the combined automated NOE assignment and structure calculation algorithm based on experimental solution NMR data sets that were modified in multiple ways to mimic different kinds of data imperfections. The results show that the algorithm is remarkably robust with regard to imperfections of the NOESY peak lists and the chemical shift tolerances but susceptible to lacking or erroneous resonance assignments, in particular for nuclei that are involved in many NOESY cross peaks.
In the chapter “Peakmatch – A simple and robust tool for peaklist matching” a method to achieve self-consistency of the chemical shift referencing among a set of peak lists is presented. The Peakmatch algorithm matches a set of peak lists to a specified reference peak list, neither of which have to be assigned, by optimizing an assignment-free match-score function. The algorithm has been extensively tested on the basis of experimental NMR data sets of five different proteins. The results show that peak lists from many different types of spectra can be matched reliably as long as they contain at least two corresponding dimensions.
NMR structures are represented by bundles of conformers whose spread indicates the precision of the atomic coordinates. However, there is as yet no reliable measure of structural accuracy, i.e. how close NMR conformers are to the “true” structure. Instead, the precision of structure bundles is widely (mis)interpreted as a measure of structural quality. Attempts to increase the precision thus often yield tight structure bundles where the precision overestimates the accuracy. To overcome this problem, the chapter “Increased reliability of NMR protein structures by consensus structure bundles” introduces a new protocol for NMR structure determination with the software package CYANA that produces bundles of conformers with a realistic precision that is throughout a large number of test data sets a much better estimate of the structural accuracy than the precision of conventional structure bundles.
Solid-state NMR is a powerful technique to study molecules which are not amenable to either solution NMR or X-ray crystallography. Despite the reporting of individual atomic resolution structures of membrane proteins and amyloid fibrils based on solid-state NMR data, the application is far from routine. One major obstacle that hinders structure determination by solid-state NMR is the overall lower quality of the solid-state NMR spectra. It is therefore necessary to increase the robustness of the computer algorithms in order to improve the results when using lower quality solid-state NMR spectra. The chapter “Structure calculations of the model protein GB1 from solid-state NMR data” presents structure calculations on the basis of a set of two-dimensional solid-state NMR experiments of the model protein GB1. The most important result obtained from these test calculations is that the limitation of structural accuracy can be attributed to inaccurate distance information resulting from the limited correlation between peak intensities and distance, which is especially severe in spin diffusion-based solid-state NMR experiments.
The chapter “Full relaxation matrix-based correction of relayed polarization transfer for solid-state NMR structure calculation” therefore introduces a method which corrects experimental peak intensities for spin diffusion in order to improve the distance information from solid-state NMR spectra. The results show that the structural accuracy can be significantly improved when using the corrected distance information, however, strongly dependent on the preliminary structural model that is required as input for the method.