The application of FAST-NMR for the identification of novel drug discovery targets

Early-stage structure-based drug discovery for small GTPases by NMR spectroscopy

Small GTPase or Ras superfamily, including Ras, Rho, Rab, Ran and Arf, are fundamental in regulating a wide range of cellular processes such as growth, differentiation, migration and apoptosis. They share structural and functional similarities for binding guanine nucleotides and hydrolyzing GTP. Dysregulations of Ras proteins are involved in the pathophysiology of multiple human diseases, however there is still a stringent need for effective treatments targeting these proteins. For decades, small GTPases were recognized as 'undruggable' targets due to their complex regulatory mechanisms and lack of deep pockets for ligand binding. NMR has been critical in deciphering the structural and dynamic properties of the switch regions that are underpinning molecular switch functions of small GTPases, which pave the way for developing new effective inhibitors. The recent progress of drug or lead molecule development made for small GTPases profoundly delineated how modern NMR techniques reshape the field of drug discovery. In this review, we will summarize the progress of structural and dynamic studies of small GTPases, the NMR techniques developed for structure-based drug screening and their applications in early-stage drug discovery for small GTPases.

A Practical Perspective on the Roles of Solution NMR Spectroscopy in Drug Discovery

Solution nuclear magnetic resonance (NMR) spectroscopy is a powerful tool to study structures and dynamics of biomolecules under physiological conditions. As there are numerous NMR-derived methods applicable to probe protein–ligand interactions, NMR has been widely utilized in drug discovery, especially in such steps as hit identification and lead optimization. NMR is frequently used to locate ligand-binding sites on a target protein and to determine ligand binding modes. NMR spectroscopy is also a unique tool in fragment-based drug design (FBDD), as it is able to investigate target-ligand interactions with diverse binding affinities. NMR spectroscopy is able to identify fragments that bind weakly to a target, making it valuable for identifying hits targeting undruggable sites. In this review, we summarize the roles of solution NMR spectroscopy in drug discovery. We describe some methods that are used in identifying fragments, understanding the mechanism of action for a ligand, and monitoring the conformational changes of a target induced by ligand binding. A number of studies have proven that ¹⁹F-NMR is very powerful in screening fragments and detecting protein conformational changes. In-cell NMR will also play important roles in drug discovery by elucidating protein-ligand interactions in living cells.

NMR Metabolomics Protocols for Drug Discovery

Drug discovery is an extremely difficult and challenging endeavor with a very high failure rate. The task of identifying a drug that is safe, selective, and effective is a daunting proposition because disease biology is complex and highly variable across patients. Metabolomics enables the discovery of disease biomarkers, which provides insights into the molecular and metabolic basis of disease and may be used to assess treatment prognosis and outcome. In this regard, metabolomics has evolved to become an important component of the drug discovery process to resolve efficacy and toxicity issues and as a tool for precision medicine. A detailed description of an experimental protocol is presented that outlines the application of NMR metabolomics to the drug discovery pipeline. This includes (1) target identification by understanding the metabolic dysregulation in diseases, (2) predicting the mechanism of action of newly discovered or existing drug therapies, (3) and using metabolomics to screen a chemical lead to assess biological activity. Unlike other OMICS approaches, the metabolome is "fragile" and may be negatively impacted by improper sample collection, storage, and extraction procedures. Similarly, biologically irrelevant conclusions may result from incorrect data collection, preprocessing or processing procedures, or the erroneous use of univariate and multivariate statistical methods. These critical concerns are also addressed in the protocol.

Multi-omic data integration and analysis using systems genomics approaches: methods and applications in animal production, health and welfare

In the past years, there has been a remarkable development of high-throughput omics (HTO) technologies such as genomics, epigenomics, transcriptomics, proteomics and metabolomics across all facets of biology. This has spearheaded the progress of the systems biology era, including applications on animal production and health traits. However, notwithstanding these new HTO technologies, there remains an emerging challenge in data analysis. On the one hand, different HTO technologies judged on their own merit are appropriate for the identification of disease-causing genes, biomarkers for prevention and drug targets for the treatment of diseases and for individualized genomic predictions of performance or disease risks. On the other hand, integration of multi-omic data and joint modelling and analyses are very powerful and accurate to understand the systems biology of healthy and sustainable production of animals. We present an overview of current and emerging HTO technologies each with a focus on their applications in animal and veterinary sciences before introducing an integrative systems genomics framework for analysing and integrating multi-omic data towards improved animal production, health and welfare. We conclude that there are big challenges in multi-omic data integration, modelling and systems-level analyses, particularly with the fast emerging HTO technologies. We highlight existing and emerging systems genomics approaches and discuss how they contribute to our understanding of the biology of complex traits or diseases and holistic improvement of production performance, disease resistance and welfare.

NMRmix: A Tool for the Optimization of Compound Mixtures in 1D (1)H NMR Ligand Affinity Screens

NMR ligand affinity screening is a powerful technique that is routinely used in drug discovery or functional genomics to directly detect protein–ligand binding events. Binding events can be identified by monitoring differences in the 1D ¹H NMR spectrum of a compound with and without protein. Although a single NMR spectrum can be collected within a short period (2—10 min per sample), one-by-one screening of a protein against a library of hundreds or thousands of compounds requires a large amount of spectrometer time and a large quantity of protein. Therefore, compounds are usually evaluated in mixtures ranging in size from 3 to 20 compounds to improve the efficiency of these screens in both time and material. Ideally, the NMR signals from individual compounds in the mixture should not overlap so that spectral changes can be associated with a particular compound. We have developed a software tool, NMRmix, to assist in creating ideal mixtures from a large panel of compounds with known chemical shifts. Input to NMRmix consists of an ¹H NMR peak list for each compound, a user-defined overlap threshold, and additional user-defined parameters if default settings are not used. NMRmix utilizes a simulated annealing algorithm to optimize the composition of the mixtures to minimize spectral peak overlaps so that each compound in the mixture is represented by a maximum number of nonoverlapping chemical shifts. A built-in graphical user interface simplifies data import and visual evaluation of the results.

Statistical removal of background signals from high-throughput (1)H NMR line-broadening ligand-affinity screens

NMR ligand-affinity screens are vital to drug discovery, are routinely used to screen fragment-based libraries, and used to verify chemical leads from high-throughput assays and virtual screens. NMR ligand-affinity screens are also a highly informative first step towards identifying functional epitopes of unknown proteins, as well as elucidating the biochemical functions of protein-ligand interaction at their binding interfaces. While simple one-dimensional (1)H NMR experiments are capable of indicating binding through a change in ligand line shape, they are plagued by broad, ill-defined background signals from protein (1)H resonances. We present an uncomplicated method for subtraction of protein background in high-throughput ligand-based affinity screens, and show that its performance is maximized when phase-scatter correction is applied prior to subtraction.

The applicability of molecular descriptors for designing an electrospray ionization mass spectrometry compatible library for drug discovery

Detecting a small molecular-weight compound by electrospray ionization mass spectrometry (ESI-MS) requires the compound to obtain a charge. Factors such as gas-phase proton affinities and analyte surface activity are correlated with a positive ESI-MS response, but unfortunately it is extremely challenging to predict from a chemical structure alone if a compound is likely to yield an observable molecular-ion peak in an ESI-MS spectrum. Thus, the design of a chemical library for an ESI-MS ligand-affinity screen is particularly daunting. Only 56.9% of the compounds from our FAST-NMR functional library [1] were detectable by ESI-MS. An analysis of ~1,600 molecular descriptors did not identify any correlation with a positive ESI-MS response that cannot be attributed to a skewed population distribution. Unfortunately, our results suggest that molecular descriptors are not a valuable approach for designing a chemical library for an MS-based ligand affinity screen.

Structure and function of human DnaJ homologue subfamily a member 1 (DNAJA1) and its relationship to pancreatic cancer

Pancreatic cancer has a dismal 5 year survival rate of 5.5% that has not been improved over the past 25 years despite an enormous amount of effort. Thus, there is an urgent need to identify truly novel yet druggable protein targets for drug discovery. The human protein DnaJ homologue subfamily A member 1 (DNAJA1) was previously shown to be downregulated 5-fold in pancreatic cancer cells and has been targeted as a biomarker for pancreatic cancer, but little is known about the specific biological function for DNAJA1 or the other members of the DnaJ family encoded in the human genome. Our results suggest the overexpression of DNAJA1 suppresses the stress response capabilities of the oncogenic transcription factor, c-Jun, and results in the diminution of cell survival. DNAJA1 likely activates a DnaK protein by forming a complex that suppresses the JNK pathway, the hyperphosphorylation of c-Jun, and the anti-apoptosis state found in pancreatic cancer cells. A high-quality nuclear magnetic resonance solution structure of the J-domain of DNAJA1 combined with a bioinformatics analysis and a ligand affinity screen identifies a potential DnaK binding site, which is also predicted to overlap with an inhibitory binding site, suggesting DNAJA1 activity is highly regulated.

Towards fully automated structure-based NMR resonance assignment of ¹⁵N-labeled proteins from automatically picked peaks

In NMR resonance assignment, an indispensable step in NMR protein studies, manually processed peaks from both N-labeled and C-labeled spectra are typically used as inputs. However, the use of homologous structures can allow one to use only N-labeled NMR data and avoid the added expense of using C-labeled data. We propose a novel integer programming framework for structure-based backbone resonance assignment using N-labeled data. The core consists of a pair of integer programming models: one for spin system forming and amino acid typing, and the other for backbone resonance assignment. The goal is to perform the assignment directly from spectra without any manual intervention via automatically picked peaks, which are much noisier than manually picked peaks, so methods must be error-tolerant. In the case of semi-automated/manually processed peak data, we compare our system with the Xiong-Pandurangan-Bailey-Kellogg's contact replacement (CR) method, which is the most error-tolerant method for structure-based resonance assignment. Our system, on average, reduces the error rate of the CR method by five folds on their data set. In addition, by using an iterative algorithm, our system has the added capability of using the NOESY data to correct assignment errors due to errors in predicting the amino acid and secondary structure type of each spin system. On a publicly available data set for human ubiquitin, where the typing accuracy is 83%, we achieve 91% accuracy, compared to the 59% accuracy obtained without correcting for such errors. In the case of automatically picked peaks, using assignment information from yeast ubiquitin, we achieve a fully automatic assignment with 97% accuracy. To our knowledge, this is the first system that can achieve fully automatic structure-based assignment directly from spectra. This has implications in NMR protein mutant studies, where the assignment step is repeated for each mutant.

Research Spotlight: Research in bioanalysis and separations at the University of Nebraska – Lincoln

The Chemistry Department at the University of Nebraska – Lincoln (UNL) is located in Hamilton Hall on the main campus of UNL in Lincoln, NE, USA. This department houses the primary graduate and research program in chemistry in the state of Nebraska. This program includes the traditional fields of analytical chemistry, biochemistry, inorganic chemistry, organic chemistry and physical chemistry. However, this program also contains a great deal of multidisciplinary research in fields that range from bioanalytical and biophysical chemistry to nanomaterials, energy research, catalysis and computational chemistry. Current research in bioanalytical and biophysical chemistry at UNL includes work with separation methods such as HPLC and CE, as well as with techniques such as MS and LC–MS, NMR spectroscopy, electrochemical biosensors, scanning probe microscopy and laser spectroscopy. This article will discuss several of these areas, with an emphasis being placed on research in bioanalytical separations, binding assays and related fields.

Correlation between protein function and ligand binding profiles

We report that proteins with the same function bind the same set of small molecules from a standardized chemical library. This observation led to a quantifiable and rapidly adaptable method for protein functional analysis using experimentally derived ligand binding profiles. Ligand binding is measured using a high-throughput NMR ligand affinity screen with a structurally diverse chemical library. The method was demonstrated using a set of 19 proteins with a range of functions. A statistically significant similarity in ligand binding profiles was only observed between the two functionally identical albumins and between the five functionally similar amylases. This new approach is independent of sequence, structure, or evolutionary information and, therefore, extends our ability to analyze and functionally annotate novel genes.

Solution structure and function of YndB, an AHSA1 protein from Bacillus subtilis

The solution structure of the Bacillus subtilis protein YndB has been solved using NMR to investigate proposed biological functions. The YndB structure exhibits the helix-grip fold, which consists of a β-sheet with two small and one long α-helix, forming a hydrophobic cavity that preferentially binds lipid-like molecules. Sequence and structure comparisons with proteins from eukaryotes, prokaryotes, and archaea suggest that YndB is very similar to the eukaryote protein Aha1, which binds to the middle domain of Hsp90 and induces ATPase activity. On the basis of these similarities, YndB has been classified as a member of the activator of Hsp90 ATPase homolog 1-like protein (AHSA1) family with a function that appears to be related to stress response. An in silico screen of a compound library of ∼ 18,500 lipids was used to identify classes of lipids that preferentially bind YndB. The in silico screen identified, in order of affinity, the chalcone/hydroxychalcone, flavanone, and flavone/flavonol classes of lipids, which was further verified by 2D (1) H-(15) N HSQC NMR titration experiments with trans-chalcone, flavanone, flavone, and flavonol. All of these compounds are typically found in plants as precursors to various flavonoid antibiotics and signaling molecules. The sum of the data suggests an involvement of YndB with the stress response of B. subtilis to chalcone-like flavonoids released by plants due to a pathogen infection. The observed binding of chalcone-like molecules by YndB is likely related to the symbiotic relationship between B. subtilis and plants.

Searching the protein structure database for ligand-binding site similarities using CPASS v.2

Background

A recent analysis of protein sequences deposited in the NCBI RefSeq database indicates that ~8.5 million protein sequences are encoded in prokaryotic and eukaryotic genomes, where ~30% are explicitly annotated as "hypothetical" or "uncharacterized" protein. Our Comparison of Protein Active-Site Structures (CPASS v.2) database and software compares the sequence and structural characteristics of experimentally determined ligand binding sites to infer a functional relationship in the absence of global sequence or structure similarity. CPASS is an important component of our Functional Annotation Screening Technology by NMR (FAST-NMR) protocol and has been successfully applied to aid the annotation of a number of proteins of unknown function.

Findings

We report a major upgrade to our CPASS software and database that significantly improves its broad utility. CPASS v.2 is designed with a layered architecture to increase flexibility and portability that also enables job distribution over the Open Science Grid (OSG) to increase speed. Similarly, the CPASS interface was enhanced to provide more user flexibility in submitting a CPASS query. CPASS v.2 now allows for both automatic and manual definition of ligand-binding sites and permits pair-wise, one versus all, one versus list, or list versus list comparisons. Solvent accessible surface area, ligand root-mean square difference, and Cβ distances have been incorporated into the CPASS similarity function to improve the quality of the results. The CPASS database has also been updated.

Conclusions

CPASS v.2 is more than an order of magnitude faster than the original implementation, and allows for multiple simultaneous job submissions. Similarly, the CPASS database of ligand-defined binding sites has increased in size by ~ 38%, dramatically increasing the likelihood of a positive search result. The modification to the CPASS similarity function is effective in reducing CPASS similarity scores for false positives by ~30%, while leaving true positives unaffected. Importantly, receiver operating characteristics (ROC) curves demonstrate the high correlation between CPASS similarity scores and an accurate functional assignment. As indicated by distribution curves, scores ≥ 30% infer a functional similarity. Software URL: http://cpass.unl.edu.

Application of NMR and molecular docking in structure-based drug discovery

Drug discovery is a complex and costly endeavor, where few drugs that reach the clinical testing phase make it to market. High-throughput screening (HTS) is the primary method used by the pharmaceutical industry to identify initial lead compounds. Unfortunately, HTS has a high failure rate and is not particularly efficient at identifying viable drug leads. These shortcomings have encouraged the development of alternative methods to drive the drug discovery process. Specifically, nuclear magnetic resonance (NMR) spectroscopy and molecular docking are routinely being employed as important components of drug discovery research. Molecular docking provides an extremely rapid way to evaluate likely binders from a large chemical library with minimal cost. NMR ligand-affinity screens can directly detect a protein-ligand interaction, can measure a corresponding dissociation constant, and can reliably identify the ligand binding site and generate a co-structure. Furthermore, NMR ligand affinity screens and molecular docking are perfectly complementary techniques, where the combination of the two has the potential to improve the efficiency and success rate of drug discovery. This review will highlight the use of NMR ligand affinity screens and molecular docking in drug discovery and describe recent examples where the two techniques were combined to identify new and effective therapeutic drugs.

PROFESS: a PROtein function, evolution, structure and sequence database

The proliferation of biological databases and the easy access enabled by the Internet is having a beneficial impact on biological sciences and transforming the way research is conducted. There are approximately 1100 molecular biology databases dispersed throughout the Internet. To assist in the functional, structural and evolutionary analysis of the abundant number of novel proteins continually identified from whole-genome sequencing, we introduce the PROFESS (PROtein Function, Evolution, Structure and Sequence) database. Our database is designed to be versatile and expandable and will not confine analysis to a pre-existing set of data relationships. A fundamental component of this approach is the development of an intuitive query system that incorporates a variety of similarity functions capable of generating data relationships not conceived during the creation of the database. The utility of PROFESS is demonstrated by the analysis of the structural drift of homologous proteins and the identification of potential pancreatic cancer therapeutic targets based on the observation of protein-protein interaction networks. Database URL: http://cse.unl.edu/~profess/

Structural and functional similarity between the bacterial type III secretion system needle protein PrgI and the eukaryotic apoptosis Bcl-2 proteins

Background

Functional similarity is challenging to identify when global sequence and structure similarity is low. Active-sites or functionally relevant regions are evolutionarily more stable relative to the remainder of a protein structure and provide an alternative means to identify potential functional similarity between proteins. We recently developed the FAST-NMR methodology to discover biochemical functions or functional hypotheses of proteins of unknown function by experimentally identifying ligand binding sites. FAST-NMR utilizes our CPASS software and database to assign a function based on a similarity in the structure and sequence of ligand binding sites between proteins of known and unknown function.

Methodology/Principal Findings

The PrgI protein from Salmonella typhimurium forms the needle complex in the type III secretion system (T3SS). A FAST-NMR screen identified a similarity between the ligand binding sites of PrgI and the Bcl-2 apoptosis protein Bcl-xL. These ligand binding sites correlate with known protein-protein binding interfaces required for oligomerization. Both proteins form membrane pores through this oligomerization to release effector proteins to stimulate cell death. Structural analysis indicates an overlap between the PrgI structure and the pore forming motif of Bcl-xL. A sequence alignment indicates conservation between the PrgI and Bcl-xL ligand binding sites and pore formation regions. This active-site similarity was then used to verify that chelerythrine, a known Bcl-xL inhibitor, also binds PrgI.

Conclusions/Significance

A structural and functional relationship between the bacterial T3SS and eukaryotic apoptosis was identified using our FAST-NMR ligand affinity screen in combination with a bioinformatic analysis based on our CPASS program. A similarity between PrgI and Bcl-xL is not readily apparent using traditional global sequence and structure analysis, but was only identified because of conservation in ligand binding sites. These results demonstrate the unique opportunity that ligand-binding sites provide for the identification of functional relationships when global sequence and structural information is limited.

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.

Structure and function of Pseudomonas aeruginosa protein PA1324 (21-170)

Pseudomonas aeruginosa is the prototypical biofilm-forming gram-negative opportunistic human pathogen. P. aeruginosa is causatively associated with nosocomial infections and with cystic fibrosis. Antibiotic resistance in some strains adds to the inherent difficulties that result from biofilm formation when treating P. aeruginosa infections. Transcriptional profiling studies suggest widespread changes in the proteome during quorum sensing and biofilm development. Many of the proteins found to be upregulated during these processes are poorly characterized from a functional standpoint. Here, we report the solution NMR structure of PA1324, a protein of unknown function identified in these studies, and provide a putative biological functional assignment based on the observed prealbumin-like fold and FAST-NMR ligand screening studies. PA1324 is postulated to be involved in the binding and transport of sugars or polysaccharides associated with the peptidoglycan matrix during biofilm formation.

Targeting protein–protein interactions for therapeutic intervention: a challenge for the future

Background: Over the last two decades, an increasing research effort in academia and industry has focused on the modulation (both inhibition and stabilization) of protein–protein interactions (PPIs) in order to develop novel therapeutic approaches and target-selective agents in drug discovery. Discussion: The diversity and complexity of highly dynamic systems such as PPIs present many challenges for the identification of drug-like molecules with the ability to modulate the PPI with the necessary selectivity and potency. In this review, a number of these strategies will be presented along with a critical overview of the challenges and potential solutions relating to the exploitation of PPIs as molecular targets. Conclusions: Both traditional drug discovery approaches and some more recently developed innovative strategies have already provided valuable tools for the discovery of PPI modulators, and a number of successful examples have highlighted the potential of targeting PPIs for therapeutic intervention, especially in the oncology area.

Enzyme controlled glucose auto-delivery for high cell density cultivations in microplates and shake flasks

Background

Here we describe a novel cultivation method, called EnBase™, or enzyme-based-substrate-delivery, for the growth of microorganisms in millilitre and sub-millilitre scale which yields 5 to 20 times higher cell densities compared to standard methods. The novel method can be directly applied in microwell plates and shake flasks without any requirements for additional sensors or liquid supply systems. EnBase is therefore readily applicable for many high throughput applications, such as DNA production for genome sequencing, optimisation of protein expression, production of proteins for structural genomics, bioprocess development, and screening of enzyme and metagenomic libraries.

Results

High cell densities with EnBase are obtained by applying the concept of glucose-limited fed-batch cultivation which is commonly used in industrial processes. The major difference of the novel method is that no external glucose feed is required, but glucose is released into the growth medium by enzymatic degradation of starch. To cope with the high levels of starch necessary for high cell density cultivation, starch is supplied to the growing culture suspension by continuous diffusion from a storage gel.

Our results show that the controlled enzyme-based supply of glucose allows a glucose-limited growth to high cell densities of OD₆₀₀ = 20 to 30 (corresponding to 6 to 9 g l^-1 cell dry weight) without the external feed of additional compounds in shake flasks and 96-well plates. The final cell density can be further increased by addition of extra nitrogen during the cultivation. Production of a heterologous triosphosphate isomerase in E. coli BL21(DE3) resulted in 10 times higher volumetric product yield and a higher ratio of soluble to insoluble product when compared to the conventional production method.

Conclusion

The novel EnBase method is robust and simple-to-apply for high cell density cultivation in shake flasks and microwell plates. The potential of the system is that the microbial growth rate and oxygen consumption can be simply controlled by the amount (and principally also by the activity) of the starch-degrading enzyme. This solves the problems of uncontrolled growth, oxygen limitation, and severe pH drop in shaken cultures. In parallel the method provides the basis for enhanced cell densities. The feasibility of the new method has been shown for 96-well plates and shake flasks and we believe that it can easily be adapted to different microwell and deepwell plate formats and shake flasks. Therefore EnBase will be a helpful tool especially in high throughput applications.