SideLink: automated side-chain assignment of biopolymers from NMR data by relative-hypothesis-prioritization-based simulated logic

Microfluidics delivery of DARPP-32 into HeLa cells maintains viability for in-cell NMR spectroscopy

High-resolution structural studies of proteins and protein complexes in a native eukaryotic environment present a challenge to structural biology. In-cell NMR can characterize atomic resolution structures but requires high concentrations of labeled proteins in intact cells. Most exogenous delivery techniques are limited to specific cell types or are too destructive to preserve cellular physiology. The feasibility of microfluidics transfection or volume exchange for convective transfer, VECT, as a means to deliver labeled target proteins to HeLa cells for in-cell NMR experiments is demonstrated. VECT delivery does not require optimization or impede cell viability; cells are immediately available for long-term eukaryotic in-cell NMR experiments. In-cell NMR-based drug screening using VECT was demonstrated by collecting spectra of the sensor molecule DARPP32, in response to exogenous administration of Forskolin.

Potent Inhibitors of Mycobacterium tuberculosis Growth Identified by Using in-Cell NMR-based Screening

In-cell NMR spectroscopy was used to screen for drugs that disrupt the interaction between prokaryotic ubiquitin like protein, Pup, and mycobacterial proteasome ATPase, Mpa. This interaction is critical for Mycobacterium tuberculosis resistance against nitric oxide (NO) stress; interruption of this process was proposed as a mechanism to control latent infection. Three compounds isolated from the NCI Diversity set III library rescued the physiological proteasome substrate from degradation suggesting that the proteasome degradation pathway was selectively targeted. Two of the compounds bind to Mpa with sub-micromolar to nanomolar affinity, and all three exhibit potency toward mycobacteria comparable to antibiotics currently available on the market, inhibiting growth in the low micromolar range.

Caught in action: selecting peptide aptamers against intrinsically disordered proteins in live cells

Intrinsically disordered proteins (IDPs) or unstructured segments within proteins play an important role in cellular physiology and pathology. Low cellular concentration, multiple binding partners, frequent post-translational modifications and the presence of multiple conformations make it difficult to characterize IDP interactions in intact cells. We used peptide aptamers selected by using the yeast-two-hybrid scheme and in-cell NMR to identify high affinity binders to transiently structured IDP and unstructured segments at atomic resolution. Since both the selection and characterization of peptide aptamers take place inside the cell, only physiologically relevant conformations of IDPs are targeted. The method is validated by using peptide aptamers selected against the prokaryotic ubiquitin-like protein, Pup, of the mycobacterium proteasome. The selected aptamers bind to distinct sites on Pup and have vastly different effects on rescuing mycobacterial proteasome substrate and on the survival of the Bacille-Calmette-Guèrin, BCG, strain of M. bovis. This technology can be applied to study the elusive action of IDPs under near physiological conditions.

Disulfide bridges remain intact while native insulin converts into amyloid fibrils

Amyloid fibrils are β-sheet-rich protein aggregates commonly found in the organs and tissues of patients with various amyloid-associated diseases. Understanding the structural organization of amyloid fibrils can be beneficial for the search of drugs to successfully treat diseases associated with protein misfolding. The structure of insulin fibrils was characterized by deep ultraviolet resonance Raman (DUVRR) and Nuclear Magnetic Resonance (NMR) spectroscopy combined with hydrogen-deuterium exchange. The compositions of the fibril core and unordered parts were determined at single amino acid residue resolution. All three disulfide bonds of native insulin remained intact during the aggregation process, withstanding scrambling. Three out of four tyrosine residues were packed into the fibril core, and another aromatic amino acid, phenylalanine, was located in the unordered parts of insulin fibrils. In addition, using all-atom MD simulations, the disulfide bonds were confirmed to remain intact in the insulin dimer, which mimics the fibrillar form of insulin.

Comprehensive automation for NMR structure determination of proteins

This chapter gives an overview of automated protein structure determination by nuclear magnetic resonance (NMR) with the UNIO protocol that enables high to full automation of all NMR data analysis steps involved. Four established algorithms, namely, the MATCH algorithm for sequence-specific resonance assignment, the ASCAN algorithm for side-chain resonance assignment, the CANDID algorithm for NOE assignment, and the ATNOS algorithm for signal identification in NMR spectra, are assembled into three principal UNIO NMR data analysis components (MATCH, ATNOS/ASCAN, and ATNOS/CANDID) that are accessed thanks to a particularly intuitive and flexible, yet powerful graphical user interface (GUI). UNIO is designed to work independently or in association with other NMR software. The principal data analysis components for sequence-specific backbone, side-chain and NOE assignment may be run separately or out of sequence. User-intervention at individual stages is encouraged and facilitated by graphical tools included for the preparation, analysis, validation, and subsequent presentation of the NMR structure.

Protein side-chain resonance assignment and NOE assignment using RDC-defined backbones without TOCSY data

One bottleneck in NMR structure determination lies in the laborious and time-consuming process of side-chain resonance and NOE assignments. Compared to the well-studied backbone resonance assignment problem, automated side-chain resonance and NOE assignments are relatively less explored. Most NOE assignment algorithms require nearly complete side-chain resonance assignments from a series of through-bond experiments such as HCCH-TOCSY or HCCCONH. Unfortunately, these TOCSY experiments perform poorly on large proteins. To overcome this deficiency, we present a novel algorithm, called NASCA: (NOE Assignment and Side-Chain Assignment), to automate both side-chain resonance and NOE assignments and to perform high-resolution protein structure determination in the absence of any explicit through-bond experiment to facilitate side-chain resonance assignment, such as HCCH-TOCSY. After casting the assignment problem into a Markov Random Field (MRF), NASCA: extends and applies combinatorial protein design algorithms to compute optimal assignments that best interpret the NMR data. The MRF captures the contact map information of the protein derived from NOESY spectra, exploits the backbone structural information determined by RDCs, and considers all possible side-chain rotamers. The complexity of the combinatorial search is reduced by using a dead-end elimination (DEE) algorithm, which prunes side-chain resonance assignments that are provably not part of the optimal solution. Then an A* search algorithm is employed to find a set of optimal side-chain resonance assignments that best fit the NMR data. These side-chain resonance assignments are then used to resolve the NOE assignment ambiguity and compute high-resolution protein structures. Tests on five proteins show that NASCA: assigns resonances for more than 90% of side-chain protons, and achieves about 80% correct assignments. The final structures computed using the NOE distance restraints assigned by NASCA: have backbone RMSD 0.8-1.5 Å from the reference structures determined by traditional NMR approaches.

Increased hydrophobicity and decreased backbone flexibility explain the lower solubility of a cataract-linked mutant of γD-crystallin

A number of point mutations in γD-crystallin are associated with human cataract. The Pro23-to-Thr (P23T) mutation is perhaps the most common, is geographically widespread, and presents itself in a variety of phenotypes. It is therefore important to understand the molecular basis of lens opacity due to this mutation. In our earlier studies, we noted that P23T shows retrograde and sharply lowered solubility, most likely due to the emergence of hydrophobic patches involved in protein aggregation. Binding of 4,4'-dianilino-1,1'-binaphthyl-5,5'-disulfonate (Bis-ANS) dye (a probe commonly used for detecting surface hydrophobicity) competed with aggregation, suggesting that the residues involved in Bis-ANS binding are also involved in protein aggregation. Here, using NMR spectroscopy in conjunction with Bis-ANS binding, we identify three residues (Y16, D21, and Y50) in P23T that are involved in binding the dye. Furthermore, using (15)N NMR relaxation experiments, we show that, in the mutant protein, backbone fluctuations are restricted to the picosecond-to-nanosecond and microsecond timescales relative to the wild type. Our present studies specify the residues involved in these two pivotal characteristics of the mutant protein, namely increased surface hydrophobicity and restricted mobility of the protein backbone, which can explain the nucleation and further propagation of protein aggregates. Thus, we have now identified the residues in the P23T mutant that give rise to novel hydrophobic surfaces, as well as those regions of the protein backbone where fluctuations in different timescales are restricted, providing a comprehensive understanding of how lens opacity could result from this mutation.

Automatic assignment of protein backbone resonances by direct spectrum inspection in targeted acquisition of NMR data

The necessity to acquire large multidimensional datasets, a basis for assignment of NMR resonances, results in long data acquisition times during which substantial degradation of a protein sample might occur. Here we propose a method applicable for such a protein for automatic assignment of backbone resonances by direct inspection of multidimensional NMR spectra. In order to establish an optimal balance between completeness of resonance assignment and losses of cross-peaks due to dynamic processes/degradation of protein, assignment of backbone resonances is set as a stirring criterion for dynamically controlled targeted nonlinear NMR data acquisition. The result is demonstrated with the 12 kDa (13)C,(15) N-labeled apo-form of heme chaperone protein CcmE, where hydrolytic cleavage of 29 C-terminal amino acids is detected. For this protein, 90 and 98% of manually assignable resonances are automatically assigned within 10 and 40 h of nonlinear sampling of five 3D NMR spectra, respectively, instead of 600 h needed to complete the full time domain grid. In addition, resonances stemming from degradation products are identified. This study indicates that automatic resonance assignment might serve as a guiding criterion for optimal run-time allocation of NMR resources in applications to proteins prone to degradation.

Automated structure determination from NMR spectra

Automated methods for protein structure determination by NMR have increasingly gained acceptance and are now widely used for the automated assignment of distance restraints and the calculation of three-dimensional structures. This review gives an overview of the techniques for automated protein structure analysis by NMR, including both NOE-based approaches and methods relying on other experimental data such as residual dipolar couplings and chemical shifts, and presents the FLYA algorithm for the fully automated NMR structure determination of proteins that is suitable to substitute all manual spectra analysis and thus overcomes a major efficiency limitation of the NMR method for protein structure determination.

Graphical interpretation of Boolean operators for protein NMR assignments

We have developed a graphics based algorithm for semi-automated protein NMR assignments. Using the basic sequential triple resonance assignment strategy, the method is inspired by the Boolean operators as it applies "AND"-, "OR"- and "NOT"-like operations on planes pulled out of the classical three-dimensional spectra to obtain its functionality. The method's strength lies in the continuous graphical presentation of the spectra, allowing both a semi-automatic peaklist construction and sequential assignment. We demonstrate here its general use for the case of a folded protein with a well-dispersed spectrum, but equally for a natively unfolded protein where spectral resolution is minimal.

Targeted acquisition for real-time NMR spectroscopy

A target-oriented approach for the acquisition of information in biomolecular NMR spectroscopy is being developed. This approach combines concurrent data accumulation, processing, and monitoring of spectral quality. Real-time estimation of parameters allows acquisition to be stopped when results are complete and have a specified precision. The technique is based on multidimensional decomposition, which can process incomplete data. An incremental nonuniform sampling scheme ensures the optimization of resolution sensitivity. To validate this method, 3D HNCO spectra of three biomolecular systems (8 kDa ubiquitin, 22 kDa barstar-barnase complex, and 82 kDa malate synthase G) are processed incrementally at small acquisition time steps. The range of molecular sizes illustrates applicability in both sample- and sensitivity-limited regimes. In each case, the target was to acquire all backbone resonances in the spectra. For the three systems, the targets are achieved after 4.5 min, 1.6 h, and 22 h of acquisition time, respectively. A number of other targets that can be similarly monitored as a function of time are discussed.