Highly automated protein backbone resonance assignment within a few hours: the "BATCH" strategy and software package

Amino acid recognition for automatic resonance assignment of intrinsically disordered proteins

Resonance assignment is a prerequisite for almost any NMR-based study of proteins. It can be very challenging in some cases, however, due to the nature of the protein under investigation. This is the case with intrinsically disordered proteins, for example, whose NMR spectra suffer from low chemical shifts dispersion and generally low resolution. For these systems, sequence specific assignment is highly time-consuming, so the prospect of using automatic strategies for their assignment is very attractive. In this article we present a new version of the automatic assignment program TSAR dedicated to intrinsically disordered proteins. In particular, we demonstrate how the automatic procedure can be improved by incorporating methods for amino acid recognition and information on chemical shifts in selected amino acids. The approach was tested in silico on 16 disordered proteins and experimentally on α-synuclein, with remarkably good results.

Non-Uniform Sampling and J-UNIO Automation for Efficient Protein NMR Structure Determination

High-resolution structure determination of small proteins in solution is one of the big assets of NMR spectroscopy in structural biology. Improvements in the efficiency of NMR structure determination by advances in NMR experiments and automation of data handling therefore attracts continued interest. Here, non-uniform sampling (NUS) of 3D heteronuclear-resolved [(1)H,(1)H]-NOESY data yielded two- to three-fold savings of instrument time for structure determinations of soluble proteins. With the 152-residue protein NP_372339.1 from Staphylococcus aureus and the 71-residue protein NP_346341.1 from Streptococcus pneumonia we show that high-quality structures can be obtained with NUS NMR data, which are equally well amenable to robust automated analysis as the corresponding uniformly sampled data.

Reduced dimensionality (3,2)D NMR experiments and their automated analysis: implications to high-throughput structural studies on proteins

Protein NMR spectroscopy has expanded dramatically over the last decade into a powerful tool for the study of their structure, dynamics, and interactions. The primary requirement for all such investigations is sequence-specific resonance assignment. The demand now is to obtain this information as rapidly as possible and in all types of protein systems, stable/unstable, soluble/insoluble, small/big, structured/unstructured, and so on. In this context, we introduce here two reduced dimensionality experiments – (3,2)D-hNCOcanH and (3,2)D-hNcoCAnH – which enhance the previously described 2D NMR-based assignment methods quite significantly. Both the experiments can be recorded in just about 2-3 h each and hence would be of immense value for high-throughput structural proteomics and drug discovery research. The applicability of the method has been demonstrated using alpha-helical bovine apo calbindin-D9k P43M mutant (75 aa) protein. Automated assignment of this data using AUTOBA has been presented, which enhances the utility of these experiments. The backbone resonance assignments so derived are utilized to estimate secondary structures and the backbone fold using Web-based algorithms. Taken together, we believe that the method and the protocol proposed here can be used for routine high-throughput structural studies of proteins.

APSY-NMR for protein backbone assignment in high-throughput structural biology

A standard set of three APSY-NMR experiments has been used in daily practice to obtain polypeptide backbone NMR assignments in globular proteins with sizes up to about 150 residues, which had been identified as targets for structure determination by the Joint Center for Structural Genomics (JCSG) under the auspices of the Protein Structure Initiative (PSI). In a representative sample of 30 proteins, initial fully automated data analysis with the software UNIO-MATCH-2014 yielded complete or partial assignments for over 90 % of the residues. For most proteins the APSY data acquisition was completed in less than 30 h. The results of the automated procedure provided a basis for efficient interactive validation and extension to near-completion of the assignments by reference to the same 3D heteronuclear-resolved [(1)H,(1)H]-NOESY spectra that were subsequently used for the collection of conformational constraints. High-quality structures were obtained for all 30 proteins, using the J-UNIO protocol, which includes extensive automation of NMR structure determination.

A suite of amino acid residue type classification pulse sequences for 13C-detected NMR of proteins

A suite of (13)C-detected NMR pulse sequences to edit the correlation peaks of the CACO and CON spectra according to the amino acid residue type is presented. The pulse sequences exploit the topology of the C(β) carbon and led to the sorting of the CACO or CON signals into several classes depending on the nature of the generating residue. A set of four or eight correlation spectra is recorded where the sign of the cross peaks changes from one spectrum to another according to the amino acid type of the corresponding residue in the protein sequence. Linear combination of these spectra produces subspectra showing signals from residues having similar C(β) topology. The presence of weak breakthrough peaks does not prevent the proper classification, since this is obtained from the subspectrum in which the correlation peak is more intense. The experiments were tested on a globular protonated protein ((13)C, (15)N labeled Ubiquitin), on a globular deuterated protein ((2)H, (13)C, (15)N labeled Ubiquitin), and on an intrinsically disordered protein ((13)C, (15)N labeled Nupr1).

Parallel acquisition of 3D-HA(CA)NH and 3D-HACACO spectra

We present here an NMR pulse sequence with 5 independent incrementable time delays within the frame of a 3-dimensional experiment, by incorporating polarization sharing and dual receiver concepts. This has been applied to directly record 3D-HA(CA)NH and 3D-HACACO spectra of proteins simultaneously using parallel detection of (1)H and (13)C nuclei. While both the experiments display intra-residue backbone correlations, the 3D-HA(CA)NH provides also sequential 'i - 1 → i' correlation along the (1)Hα dimension. Both the spectra contain special peak patterns at glycine locations which serve as check points during the sequential assignment process. The 3D-HACACO spectrum contains, in addition, information on prolines and side chains of residues having H-C-CO network (i.e., (1)Hβ, (13)Cβ and (13)COγ of Asp and Asn, and (1)Hγ, (13)Cγ and (13)COδ of Glu and Gln), which are generally absent in most conventional proton detected experiments.

New amino acid residue type identification experiments valid for protonated and deuterated proteins

Two experiments are presented that yield amino acid type identification of individual residues in a protein by editing the (1)H-(15)N correlations into four different 2D subspectra, each corresponding to a different amino acid type class, and that can be applied to deuterated proteins. One experiment provides information on the amino acid type of the residue preceding the detected amide (1)H-(15)N correlation, while the other gives information on the type of its own residue. Versions for protonated proteins are also presented, and in this case it is possible to classify the residues into six different classes. Both sequential and intraresidue experiments provide highly complementary information, greatly facilitating the assignment of protein resonances. The experiments will also assist in transferring the assignment of a protein to the spectra obtained under different experimental conditions (e.g. temperature, pH, presence of ligands, cofactors, etc.).

The J-UNIO protocol for automated protein structure determination by NMR in solution

The J-UNIO (JCSG protocol using the software UNIO) procedure for automated protein structure determination by NMR in solution is introduced. In the present implementation, J-UNIO makes use of APSY-NMR spectroscopy, 3D heteronuclear-resolved [(1)H,(1)H]-NOESY experiments, and the software UNIO. Applications with proteins from the JCSG target list with sizes up to 150 residues showed that the procedure is highly robust and efficient. In all instances the correct polypeptide fold was obtained in the first round of automated data analysis and structure calculation. After interactive validation of the data obtained from the automated routine, the quality of the final structures was comparable to results from interactive structure determination. Special advantages are that the NMR data have been recorded with 6-10 days of instrument time per protein, that there is only a single step of chemical shift adjustments to relate the backbone signals in the APSY-NMR spectra with the corresponding backbone signals in the NOESY spectra, and that the NOE-based amino acid side chain chemical shift assignments are automatically focused on those residues that are heavily weighted in the structure calculation. The individual working steps of J-UNIO are illustrated with the structure determination of the protein YP_926445.1 from Shewanella amazonensis, and the results obtained with 17 JCSG targets are critically evaluated.

Facile backbone (1H, 15N, 13Ca, and 13C') assignment of 13C/15N-labeled proteins using orthogonal projection planes of HNN and HN(C)N experiments and its automation

Recently, we introduced an efficient high-throughput protocol for backbone assignment of small folded proteins based on two-dimensional (2D) projections of HN(C)N suite of experiments and its automation [Borkar et al., J. Biomol. NMR 2011, 50(3), 285-297]. This strategy provides complete sequence-specific assignment of backbone ((1)H, (15)N, (13)C(α), and (13)C') resonances in less than a day; thus, it has great implications for high-throughput structural proteomics. However, in cases when such small folded protein exhibits substantial amide (1)H shift degeneracy (typically seen in alpha-helical proteins), the strategy may fail or lead to ambiguities. Another limitation is with respect to the identification of checkpoints from the variants of 2D-hncNH spectrum. For example, a protein with many GG, GA, AA, SS, TS, TT, and TS types of dipeptide stretches along its sequence, thus the identification of NH cross-peak corresponding to second G, A, S, or T becomes difficult. In this backdrop, we present here two improvements to enhance the utility of the proposed high-throughput AUTOmatic Backbone Assignment protocol: (i) use of 2D-hNnH spectrum and its variants that display additional (1)H-(15)N correlations and thus help to resolve ambiguities arising because of amide (1)H shift degeneracy and (ii) optimization of the τ(CN) delay in the 2D-hncNH experiment that, when properly adjusted, is observed to help remove ambiguities in the identification of the checkpoints. These improvements have also been incorporated in the automation program AUTOmatic Backbone Assignment. Finally, the performance of the strategy and the automation has been demonstrated using the chicken SH3 domain protein.

Fast protein backbone NMR resonance assignment using the BATCH strategy

Probing protein structure, dynamics, and interaction surfaces by NMR requires initial backbone resonance assignment. The protocol for this step has been progressively developed in the last 15 years to provide robust assignments. However, even in the case of favorable conditions (high field magnets and cryogenically cooled probes, small globular proteins, high sample concentration), the assignment step generally takes several days of data collection and analysis, thus precluding studies of unstable proteins and limiting high-throughput applications. Recently, we have introduced the BATCH strategy for fast protein backbone resonance assignment. BATCH benefits from the combination of several tools (BEST/ASCOM/Targeted-Sampling/COBRA/HADAMAC) for time-optimized and highly automated NMR data acquisition, processing, and analysis. In this chapter, we discuss the individual steps of the BATCH method and describe its practical implementation to obtain the backbone resonance assignment of small globular proteins in a few hours of time.

iHADAMAC: a complementary tool for sequential resonance assignment of globular and highly disordered proteins

An experiment, iHADAMAC, is presented that yields information on the amino-acid type of individual residues in a protein by editing the (1)H-(15)N correlations into seven different 2D spectra, each corresponding to a different class of amino-acid types. Amino-acid type discrimination is realized via a Hadamard encoding scheme based on four different spin manipulations as recently introduced in the context of the sequential HADAMAC experiment. Both sequential and intra-residue HADAMAC experiments yield highly complementary information that greatly facilitate resonance assignment of proteins with high frequency degeneracy, as demonstrated here for a 188-residue intrinsically disordered protein fragment of the hepatitis C virus protein NS5A.

Rapid measurement of residual dipolar couplings for fast fold elucidation of proteins

It has been demonstrated that protein folds can be determined using appropriate computational protocols with NMR chemical shifts as the sole source of experimental restraints. While such approaches are very promising they still suffer from low convergence resulting in long computation times to achieve accurate results. Here we present a suite of time- and sensitivity optimized NMR experiments for rapid measurement of up to six RDCs per residue. Including such an RDC data set, measured in less than 24 h on a single aligned protein sample, greatly improves convergence of the Rosetta-NMR protocol, allowing for overnight fold calculation of small proteins. We demonstrate the performance of our fast fold calculation approach for ubiquitin as a test case, and for two RNA-binding domains of the plant protein HYL1. Structure calculations based on simulated RDC data highlight the importance of an accurate and precise set of several complementary RDCs as additional input restraints for high-quality de novo structure determination.

AUTOBA: automation of backbone assignment from HN(C)N suite of experiments

Development of efficient strategies and automation represent important milestones of progress in rapid structure determination efforts in proteomics research. In this context, we present here an efficient algorithm named as AUTOBA (Automatic Backbone Assignment) designed to automate the assignment protocol based on HN(C)N suite of experiments. Depending upon the spectral dispersion, the user can record 2D or 3D versions of the experiments for assignment. The algorithm uses as inputs: (i) protein primary sequence and (ii) peak-lists from user defined HN(C)N suite of experiments. In the end, one gets H(N), (15)N, C(α) and C' assignments (in common BMRB format) for the individual residues along the polypeptide chain. The success of the algorithm has been demonstrated, not only with experimental spectra recorded on two small globular proteins: ubiquitin (76 aa) and M-crystallin (85 aa), but also with simulated spectra of 27 other proteins using assignment data from the BMRB.

Overview on the use of NMR to examine protein structure

Any protein structure determination process contains several steps, starting from obtaining a suitable sample, then moving on to acquiring data and spectral assignment, and lastly to the final steps of structure determination and validation. This unit describes all of these steps, starting with the basic physical principles behind NMR and some of the most commonly measured and observed phenomena such as chemical shift, scalar and residual coupling, and the nuclear Overhauser effect. Then, in somewhat more detail, the process of spectral assignment and structure elucidation is explained. Furthermore, the use of NMR to study protein-ligand interaction, protein dynamics, or protein folding is described.

Structural and metal binding characterization of the C-terminal metallochaperone domain of membrane fusion protein SilB from Cupriavidus metallidurans CH34

Detoxification of heavy metal ions in Proteobacteria is tightly controlled by various systems regulating their sequestration and transport. In Cupriavidus metallidurans CH34, a model organism for heavy metal resistance studies, the sil determinant is potentially involved in the efflux of silver and copper ions. Proteins SilA, SilB, and SilC form a resistance nodulation cell division (RND)-based transport system in which SilB is the periplasmic adaptor protein belonging to the membrane fusion protein (MFP) family. In addition to the four domains typical of known MFPs, SilB has a fifth additional C-terminal domain, called SilB(440-521), which is characterized here. Structure and backbone dynamics of SilB(440-521) have been investigated using nuclear magnetic resonance, and the residues of the metal site were identified from (15)N- and (13)C-edited HSQC spectra. The solution structure and additional metal binding experiments demonstrated that this C-terminal domain folds independently of the rest of the protein and has a conformation and a Ag(+) and Cu(+) binding specificity similar to those determined for CusF from Escherichia coli. The small protein CusF plays a role in metal trafficking in the periplasm. The similarity with CusF suggests a potential metallochaperone role for SilB(440-521) that is discussed in the context of simultaneous expression of different determinants involved in copper resistance in C. metallidurans CH34.

Speeding up (13)C direct detection biomolecular NMR spectroscopy

After the exploitation of (1)H polarization as a starting source for (13)C direct detection experiments, pulse sequences are designed which exploit the accelerated (1)H longitudinal relaxation to expedite (13)C direct detection experiments. We show here that 2D experiments based on (13)C direct detection on a 0.5 mM water sample of ubiquitin can be recorded in a few minutes and 3D experiments in a few hours. We also show that fast methods like nonuniform sampling can be easily implemented. As overall experimental time has always been a counter indication for the use of (13)C direct detection experiments, this research opens new avenues for the application of (13)C NMR to biological molecules.

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.