From Gene to HSQC in under Five Hours: High-Throughput NMR Proteomics

Controlling the diameter, monodispersity, and solubility of ApoA1 nanolipoprotein particles using telodendrimer chemistry

Nanolipoprotein particles (NLPs) are nanometer-scale discoidal particles that feature a phospholipid bilayer confined within an apolipoprotein "scaffold," which are useful for solubilizing hydrophobic molecules such as drugs and membrane proteins. NLPs are synthesized either by mixing the purified apolipoprotein with phospholipids and other cofactors or by cell-free protein synthesis followed by self-assembly of the nanoparticles in the reaction mixture. Either method can be problematic regarding the production of homogeneous and monodispersed populations of NLPs, which also currently requires multiple synthesis and purification steps. Telodendrimers (TD) are branched polymers made up of a dendritic oligo-lysine core that is conjugated to linear polyethylene glycol (PEG) on one end, and the lysine "branches" are terminated with cholic acid moieties that enable the formation of nanomicelles in aqueous solution. We report herein that the addition of TD during cell-free synthesis of NLPs produces unique hybrid nanoparticles that have drastically reduced polydispersity as compared to NLPs made in the absence of TD. This finding was supported by dynamic light scattering, fluorescence correlation spectroscopy, and cryo transmission electron microscopy (Cryo-EM). These techniques demonstrate the ability of TDs to modulate both the NLP size (6-30 nm) and polydispersity. The telodendrimer NLPs (TD-NLPs) also showed 80% less aggregation as compared to NLPs alone. Furthermore, the versatility of these novel nanoparticles was shown through direct conjugation of small molecules such as fluorescent dyes directly to the TD as well as the insertion of a functional membrane protein.

Characterization of de novo synthesized GPCRs supported in nanolipoprotein discs

The protein family known as G-protein coupled receptors (GPCRs) comprises an important class of membrane-associated proteins, which remains a difficult family of proteins to characterize because their function requires a native-like lipid membrane environment. This paper focuses on applying a single step method leading to the formation of nanolipoprotein particles (NLPs) capable of solubilizing functional GPCRs for biophysical characterization. NLPs were used to demonstrate increased solubility for multiple GPCRs such as the Neurokinin 1 Receptor (NK1R), the Adrenergic Receptor â2 (ADRB2) and the Dopamine Receptor D1 (DRD1). All three GPCRs showed affinity for their specific ligands using a simple dot blot assay. The NK1R was characterized in greater detail to demonstrate correct folding of the ligand pocket with nanomolar specificity. Electron paramagnetic resonance (EPR) spectroscopy validated the correct folding of the NK1R binding pocket for Substance P (SP). Fluorescence correlation spectroscopy (FCS) was used to identify SP-bound NK1R-containing NLPs and measure their dissociation rate in an aqueous environment. The dissociation constant was found to be 83 nM and was consistent with dot blot assays. This study represents a unique combinational approach involving the single step de novo production of a functional GPCR combined with biophysical techniques to demonstrate receptor association with the NLPs and binding affinity to specific ligands. Such a combined approach provides a novel path forward to screen and characterize GPCRs for drug discovery as well as structural studies outside of the complex cellular environment.

Phase-sensitive spectral estimation by the hybrid filter diagonalization method

A more robust way to obtain a high-resolution multidimensional NMR spectrum from limited data sets is described. The Filter Diagonalization Method (FDM) is used to analyze phase-modulated data and cast the spectrum in terms of phase-sensitive Lorentzian "phase-twist" peaks. These spectra are then used to obtain absorption-mode phase-sensitive spectra. In contrast to earlier implementations of multidimensional FDM, the absolute phase of the data need not be known beforehand, and linear phase corrections in each frequency dimension are possible, if they are required. Regularization is employed to improve the conditioning of the linear algebra problems that must be solved to obtain the spectral estimate. While regularization smoothes away noise and small peaks, a hybrid method allows the true noise floor to be correctly represented in the final result. Line shape transformation to a Gaussian-like shape improves the clarity of the spectra, and is achieved by a conventional Lorentzian-to-Gaussian transformation in the time-domain, after inverse Fourier transformation of the FDM spectra. The results obtained highlight the danger of not using proper phase-sensitive line shapes in the spectral estimate. The advantages of the new method for the spectral estimate are the following: (i) the spectrum can be phased by conventional means after it is obtained; (ii) there is a true and accurate noise floor; and (iii) there is some indication of the quality of fit in each local region of the spectrum. The method is illustrated with 2D NMR data for the first time, but is applicable to n-dimensional data without any restriction on the number of time/frequency dimensions.

Filter diagonalization using a "sensitivity-enhanced basis": improved performance for noisy NMR spectra

The Filter Diagonalization Method (FDM) has been used to process NMR data in liquids and can be advantageous when the spectrum is sparse enough, the lines are sharp and Lorentzian, raw sensitivity is adequate, and the measured time-domain data is short, so that the Fourier Transform spectrum exhibits distorted line shapes. Noise can adversely impact resolution and/or frequency accuracy in FDM spectral estimates. Paradoxically, more complete data can lead to worse FDM spectra if there is appreciable noise. However, by modifying the numerical method, the FDM noise performance improves significantly, without apparently losing any of the existing advantages. The two key modifications are to adjust the FDM basis functions so that matrix elements computed from them have less noise contribution on average, and to regularize each dimension of a multidimensional spectrum independently. The modifications can be recommended for general-purpose use in the case of somewhat noisy, incomplete data.

In vitro protein expression: an emerging alternative to cell-based approaches

Protein expression remains a bottleneck in the production of proteins. Owing to several advantages, cell-free translation is emerging as an alternative to cell-based methods for the generation of proteins. Recent advances have led to many novel applications of cell-free systems in biotechnology, proteomics and fundamental biological research. This special issue of New Biotechnology describes recent advances in cell-free protein expression systems and their applications.

Quantitative two-dimensional HSQC experiment for high magnetic field NMR spectrometers

The finite RF power available on carbon channel in proton-carbon correlation experiments leads to non-uniform cross peak intensity response across carbon chemical shift range. Several classes of broadband pulses are available that alleviate this problem. Adiabatic pulses provide an excellent magnetization inversion over a large bandwidth, and very recently, novel phase-modulated pulses have been proposed that perform 90 degrees and 180 degrees magnetization rotations with good offset tolerance. Here, we present a study how these broadband pulses (adiabatic and phase-modulated) can improve quantitative application of the heteronuclear single quantum coherence (HSQC) experiment on high magnetic field strength NMR spectrometers. Theoretical and experimental examinations of the quantitative, offset-compensated, CPMG-adjusted HSQC (Q-OCCAHSQC) experiment are presented. The proposed experiment offers a formidable improvement to the offset performance; (13)C offset-dependent standard deviation of the peak intensity was below 6% in range of+/-20 kHz. This covers the carbon chemical shift range of 150 ppm, which contains the protonated carbons excluding the aldehydes, for 22.3 T NMR magnets. A demonstration of the quantitative analysis of a fasting blood plasma sample obtained from a healthy volunteer is given.

Advances in Nuclear Magnetic Resonance for Drug Discovery

BACKGROUND: Drug discovery is a complex and unpredictable endeavor with a high failure rate. Current trends in the pharmaceutical industry have exasperated these challenges and are contributing to the dramatic decline in productivity observed over the last decade. The industrialization of science by forcing the drug discovery process to adhere to assembly-line protocols is imposing unnecessary restrictions, such as short project time-lines. Recent advances in nuclear magnetic resonance are responding to these self-imposed limitations and are providing opportunities to increase the success rate of drug discovery. OBJECTIVE/METHOD: A review of recent advancements in NMR technology that have the potential of significantly impacting and benefiting the drug discovery process will be presented. These include fast NMR data collection protocols and high-throughput protein structure determination, rapid protein-ligand co-structure determination, lead discovery using fragment-based NMR affinity screens, NMR metabolomics to monitor in vivo efficacy and toxicity for lead compounds, and the identification of new therapeutic targets through the functional annotation of proteins by FAST-NMR. CONCLUSION: NMR is a critical component of the drug discovery process, where the versatility of the technique enables it to continually expand and evolve its role. NMR is expected to maintain this growth over the next decade with advancements in automation, speed of structure calculation, in-cell imaging techniques, and the expansion of NMR amenable targets.

Enhanced spectral resolution by high-dimensional NMR using the filter diagonalization method and "hidden" dimensions

High-dimensional (HD) NMR spectra have poorer digital resolution than low-dimensional (LD) spectra, for a fixed amount of experiment time. This has led to "reduced-dimensionality" strategies, in which several LD projections of the HD NMR spectrum are acquired, each with higher digital resolution; an approximate HD spectrum is then inferred by some means. We propose a strategy that moves in the opposite direction, by adding more time dimensions to increase the information content of the data set, even if only a very sparse time grid is used in each dimension. The full HD time-domain data can be analyzed by the filter diagonalization method (FDM), yielding very narrow resonances along all of the frequency axes, even those with sparse sampling. Integrating over the added dimensions of HD FDM NMR spectra reconstitutes LD spectra with enhanced resolution, often more quickly than direct acquisition of the LD spectrum with a larger number of grid points in each of the fewer dimensions. If the extra-dimensions do not appear in the final spectrum, and are used solely to boost information content, we propose the moniker hidden-dimension NMR. This work shows that HD peaks have unmistakable frequency signatures that can be detected as single HD objects by an appropriate algorithm, even though their patterns would be tricky for a human operator to visualize or recognize, and even if digital resolution in an HD FT spectrum is very coarse compared with natural line widths.

Doubly compensated multiplicity-edited HSQC experiments utilizing broadband inversion pulses

We propose a family of doubly compensated multiplicity-edited heteronuclear single quantum coherence (HSQC) pulse sequences. The key difference between our proposed sequences and the compensation of refocusing inefficiency with synchronized inversion sweeps (CRISIS)-HSQC experiments they are based on is that the conventional rectangular 180 degrees pulses on the proton channel in the latter have been replaced by the computer-optimized broadband inversion pulses (BIPs) with superior inversion performance as well as much improved tolerance to B(1) field inhomogeneity. Moreover, all adiabatic carbon 180 degrees pulses during the INEPT and reverse-INEPT periods in the CRISIS-HSQC sequences have also been replaced with the much shorter BIPs, while the adiabatic sweeps during the heteronuclear spin echo for multiplicity editing are kept in place in order to maintain the advantage of the CRISIS feature of the original sequences, namely J-independent refocusing of the one-bond (1)H--(13)C coupling constants. These modifications have also been implemented to the preservation of equivalent pathways (PEP)-HSQC experiments. We demonstrate through a detailed comparison that replacing the proton 180 degrees pulses with the BIPs provide additional sensitivity gain that can be mainly attributed to the improved tolerance to B(1) field inhomogeneity of the BIPs. The proposed sequences can be easily adapted for (19)F--(13)C correlations.

Cell-free protein synthesis for analysis by NMR spectroscopy

Cell-free protein synthesis offers fast and inexpensive access to selectively isotope labeled proteins that can be measured by NMR spectroscopy in the presence of all the unlabeled proteins in the reaction mixture. No chromatographic purification is required. Using an extract from Escherichia coli in a simple dialysis system, the target protein can be prepared at a typical concentration of about 1 mg/ml, which is sufficient for subsequent analysis by NMR. This chapter describes in detail the protocol used in the authors' laboratory.

Minimizing the overlap problem in protein NMR: a computational framework for precision amino acid labeling

MOTIVATION

Recent advances in cell-free protein expression systems allow specific labeling of proteins with amino acids containing stable isotopes ((15)N, (13) C and (2)H), an important feature for protein structure determination by nuclear magnetic resonance (NMR) spectroscopy. Given this labeling ability, we present a mathematical optimization framework for designing a set of protein isotopomers, or labeling schedules, to reduce the congestion in the NMR spectra. The labeling schedules, which are derived by the optimization of a cost function, are tailored to a specific protein and NMR experiment.

RESULTS

For 2D (15)N-(1)H HSQC experiments, we can produce an exact solution using a dynamic programming algorithm in under 2 h on a standard desktop machine. Applying the method to a standard benchmark protein, calmodulin, we are able to reduce the number of overlaps in the 500 MHz HSQC spectrum from 10 to 1 using four samples with a true cost function, and 10 to 4 if the cost function is derived from statistical estimates. On a set of 448 curated proteins from the BMRB database, we are able to reduce the relative percent congestion by 84.9% in their HSQC spectra using only four samples. Our method can be applied in a high-throughput manner on a proteomic scale using the server we developed. On a 100-node cluster, optimal schedules can be computed for every protein coded for in the human genome in less than a month.

AVAILABILITY

A server for creating labeling schedules for (15)N-(1)H HSQC experiments as well as results for each of the individual 448 proteins used in the test set is available at http://nmr.proteomics.ics.uci.edu.

Simultaneous Characterization of a Mixture of Fluorochemicals Using Three-Dimensional 19F−1H Heteronuclear TOCSY Filtered/Edited NMR Experiments

Heteronuclear 19F-1H cross-polarization can be used effectively as a tool for both spectral filtering and editing in the NMR analysis of the increasing number of fluorine-containing compounds encountered in drug discovery. Combined with LC-MS, three-dimensional 19F-1H heteronuclear TOCSY filtered experiments based on this approach have enabled the simultaneous identification of a mixture of closely related dexamethasone derivatives without the need for isolation.

Enhanced cell-free protein expression by fusion with immunoglobulin Ckappa domain

While cell-free systems are increasingly used for protein expression in structural and functional studies, several proteins are difficult to express or expressed only at low levels in cell-free lysates. Here, we report that fusion of the human immunoglobulin kappa light chain constant domain (Ckappa) at the C terminus of four representative proteins dramatically improved their production in the Escherichia coli S30 system, suggesting that enhancement of cell-free protein expression by Ckappa fusion will be widely applicable.

15N-Labelled proteins by cell-free protein synthesis

[(15)N]-heteronuclear single quantum coherence (HSQC) spectra provide a readily accessible fingerprint of [(15)N]-labelled proteins, where the backbone amide group of each nonproline amino acid residue contributes a single cross-peak. Cell-free protein synthesis offers a fast and economical route to enhance the information content of [(15)N]-HSQC spectra by amino acid type selective [(15)N]-labelling. The samples can be measured without chromatographic protein purification, dilution of isotopes by transaminase activities are suppressed, and a combinatorial isotope labelling scheme can be adopted that combines reduced spectral overlap with a minimum number of samples for the identification of all [(15)N]-HSQC cross-peaks by amino acid residue type. These techniques are particularly powerful for tracking [(15)N]-HSQC cross-peaks after titration with unlabelled ligand molecules or macromolecular binding partners. In particular, combinatorial isotope labelling can provide complete cross-peak identification by amino acid type in 24 h, including protein production and NMR measurement.