In structural biology, nuclear magnetic resonance (NMR) is an important method when studying biological complexes with high resolution. Compared with solution NMR, solid-state NMR (ssNMR) has increased the possibility of studying large macromolecular assemblies with high structural complexity mainly related to low solubility. However, computational tools for the analysis of complex multidimensional ssNMR data have lagged behind those for solution NMR. Before a structure can be determined, thousands of signals from individual types of multidimensional ssNMR spectra of samples must be recognized, correlated, categorized, and eventually assigned to atoms in the chemical structure. To address these tedious steps, we have developed an automated algorithm for ssNMR spectra called “ssPINE”. The ssPINE software accepts the sequence of the protein plus peak lists from a variety of ssNMR experiments as inputs and offers automated backbone and side-chain assignments. To lower the bar of using ssPINE, we have developed a graphical user interface called ssPINE-POKY as a plugin to POKY that provides seamless communication between POKY and ssPINE webserver. The user only needs to select experiments in POKY to run a job and import results with just a few mouse clicks. Supported by NSF DBI-2051595, DBI-1902076 and University of Colorado Denver.

Background: Macrophage activation and vascular inflammation play important roles in atherosclerosis. Non-editing functions of adenosine deaminase acting on RNA (ADAR1) in macrophage activation and atherosclerosis remain elusive. Methods: Nonvascular ADAR1 in atherosclerosis progression was investigated via aortic transplantation and bone marrow transplantation. ApoE-/- mice combined with macrophage-specific ADAR1 deficiency were used to determine macrophage-specific roles of ADAR1 in atherosclerosis. Human coronary atherosclerotic specimens were utilized to establish the relevance to human atherosclerosis. Moreover, a humanized atherosclerosis model was created to examine the influence of human macrophages in human arteries. Results: ADAR1+/– attenuates atherosclerosis. Allograft transplantation of wild-type abdominal aorta into ADAR1+/– recipient mice promoted atherosclerosis. Likewise, bone marrow transplantation from wild-type mice to ADAR1+/– recipient mice negated the protective effects of ADAR1+/–, suggesting that nonvascular ADAR1 is instrumental for atherosclerosis progression. ADAR1 deficiency in hematopoietic cells lessened the prevalence and severity of atherosclerosis, and impeded macrophage infiltration, foam cell formation, and aortic wall inflammation. Mechanistically, ADAR1 deletion deterred classical macrophage activation and foam cell formation via downregulation of PPAR-γ, which was mediated by enhancing ubiquitination and further degradation of PPAR-γ. Importantly, ADAR1 was upregulated in macrophages in human atherosclerotic lesions. Transplantation of ADAR1-deficient human monocytes, rather than their wild-type counterparts, into hyperlipidemic immunodeficient mice suppressed the formation of atherosclerosis in transplanted arteries from patients undergoing coronary artery bypass grafting surgery due to coronary artery blockade by atherosclerotic plagues. Interestingly, ADAR1 suppression in macrophages noticeably augmented the anti-atherosclerotic effect of the PPAR-γ agonist rosiglitazone. Conclusions: These results demonstrate that noncanonical ADAR1 plays an essential role in the regulation of macrophage activation and atherosclerosis development.

Background: Niacin-derived nicotinamide adenine dinucleotide is an essential cofactor for many dehydrogenase enzymes involved in vitamin A (VA) metabolism. Several countries with high prevalence of VA deficiency rely on maize, a poor source of available niacin, as a dietary staple. Objectives: This study evaluated the interaction of dietary niacin on VA homeostasis using male Sprague-Dawley rats, aged 21 d (baseline body weight 88.3 +/- 6.6 g). Methods: After 1 wk of acclimation, baseline samples were collected (n = 4). Remaining rats (n = 54) were split into 9 groups to receive low tryptophan, VA-deficient feed with 3 different amounts of niacin (0, 15, or 30 mg/kg) and 3 different oral VA doses (50, 350, or 3500 nmol/d) in a 3 x 3 design. After 4 wk, the study was terminated. Serum, livers, and small intestine were analyzed for retinoids using high-performance liquid chromatography. Niacin and metabolites were evaluated with nuclear magnetic resonance. Plasma pyridoxal-P (PLP) was measured with high-performance liquid chromatography. Results: Niacin intake correlated with serum retinol concentrations (r = 0.853, P < 0.001). For rats receiving the highest VA dose, liver retinol concentrations were lower in the 30-mg/kg niacin group (5.39 +/- 0.27 mu mol/g) than those in the 0-mg/kg and 15-mg/kg groups (9.18 +/- 0.62 and 8.75 +/- 0.07 mu mol/g, respectively; P <= 0.05 for both). This phenomenon also occurred in the lower VA doses (P <= 0.05 for all). Growth and tissue weight at endline were associated with niacin intake (P <= 0.001 for all). Plasma PLP correlated with estimated niacin intake (r = 0.814, P < 0.001). Conclusions: Optimal niacin intake is associated with lower liver VA and higher serum retinol and plasma PLP concentrations. The extent to which vitamin B intake affects VA homeostasis requires further investigation to determine if the effects are maintained in humans.

NMR spectroscopy provides structural and functional information about biomolecules and their complexes. The complexity of these systems can make the NMR data difficult to interpret, particularly for newer users of NMR technology, who may have limited understanding of the tools available and how they are used. To alleviate this problem, we have created software based on standardized workflows for both solution and solid-state NMR spectroscopy of proteins. These tools assist with manual and automated peak picking and with chemical shift assignment and validation. They provide users with an optimized path through spectral analysis that can help them perform the necessary tasks more efficiently.

The heightened dipolar interactions in solids render solid-state NMR (ssNMR) spectra more difficult to interpret than solution NMR spectra. On the other hand, ssNMR does not suffer from severe molecular weight limitations like solution NMR. In recent years, ssNMR has undergone rapid technological developments that have enabled structure–function studies of increasingly larger biomolecules, including membrane proteins. Current methodology includes stable isotope labeling schemes, non-uniform sampling with spectral reconstruction, faster magic angle spinning, and innovative pulse sequences that capture different types of interactions among spins. However, computational tools for the analysis of complex ssNMR data from membrane proteins and other challenging protein systems have lagged behind those for solution NMR. Before a structure can be determined, thousands of signals from individual types of multidimensional ssNMR spectra of samples, which may have differing isotopic composition, must be recognized, correlated, categorized, and eventually assigned to atoms in the chemical structure. To address these tedious steps, we have developed an automated algorithm for ssNMR spectra called “ssPINE”. The ssPINE software accepts the sequence of the protein plus peak lists from a variety of ssNMR experiments as inputs and offers automated backbone and side-chain assignments. The alpha version of ssPINE, which we describe here, is freely available through a web submission form.

The Biological Magnetic Resonance Data Bank (BioMagResBank or BMRB https://bmrb.io), founded in 1988, is the international, open archive for data generated by Nuclear Magnetic Resonance (NMR) spectroscopy of biological systems. NMR spectroscopy is unique among biophysical approaches in its ability to provide a broad range of atomic and higher-level information relevant to the structural, dynamic, and chemical properties of biological macromolecules, as well as report on metabolite and natural product concentrations in complex mixtures and their chemical structures. NMR-STAR is the official data format of BMRB and BMRB provides python parser (PyNMRSTAR https://github.com/uwbmrb/PyNMRSTAR), a data visualization tool (PyBMRB https://github.com/uwbmrb/PyBMRB) and an Application Program Interface (API)(BMRB-API https://github.com/uwbmrb/BMRB-API) to access the BMRB archive. PyBMRB displays the chemical shifts data in each entry as a simulated NMR spectrum and to generates database-wide chemical shift histograms of different atom types in proteins and nucleic acids. PyBMRB provides access to BMRB data through the API and generates portable and interactive visualizations as a single html file. It also supports data visualization workflows using Jupyter Notebooks, which can be both easily created and shared.

The ATPase Family, AAA domain-containing protein 2 (ATAD2) bromodomain (BRD) has a canonical bromodomain structure consisting of four α-helices. ATAD2 functions as a co-activator of the androgen and estrogen receptors as well as the MYC and E2F transcription factors. ATAD2 also functions during DNA replication, recognizing newly synthesized histones. In addition, ATAD2 is shown to be up regulated in multiple forms of cancer including breast, lung, gastric, endometrial, renal, and prostate. Furthermore, up-regulation of ATAD2 is strongly correlated with poor prognosis in many types of cancer, making the ATAD2 bromodomain an innovative target for cancer therapeutics. In this study, we describe the recognition of histone acetyllysine modifications by the ATAD2 bromodomain. Residue-specific information on the complex formed between the histone tail and the ATAD2 bromodomain, obtained through nuclear magnetic resonance spectroscopy (NMR) and X-ray crystallography, illustrates key residues lining the binding pocket, which are involved in coordination of di-acetylated histone tails. Analytical ultracentrifugation, NMR relaxation data, and isothermal titration calorimetry further confirm the monomeric state of the functionally active ATAD2 bromodomain in complex with di-acetylated histone ligands. Overall, we describe histone tail recognition by ATAD2 BRD and illustrate that one acetyllysine group is primarily engaged by the conserved asparagine (N1064), the “RVF” shelf residues, and the flexible ZA loop. Coordination of a second acetyllysine group also occurs within the same binding pocket, but is essentially governed by unique hydrophobic and electrostatic interactions making the di-acetyllysine histone coordination more specific than previously presumed.

Protein Data Bank is the single worldwide archive of experimentally determined macromolecular structure data. Established in 1971 as the first open access data resource in biology, the PDB archive is managed by the worldwide Protein Data Bank (wwPDB) consortium which has four partners-the RCSB Protein Data Bank (RCSB PDB; rcsb.org), the Protein Data Bank Japan (PDBj; pdbj.org), the Protein Data Bank in Europe (PDBe; pdbe.org), and BioMagResBank (BMRB; www.bmrb.wisc.edu). The PDB archive currently includes similar to 175,000 entries. The wwPDB has established a number of task forces and working groups that bring together experts form the community who provide recommendations on improving data standards and data validation for improving data quality and integrity. The wwPDB members continue to develop the joint deposition, biocuration, and validation system (OneDep) to improve data quality and accommodate new data from emerging techniques such as 3DEM. Each PDB entry contains coordinate model and associated metadata for all experimentally determined atomic structures, experimental data for the traditional structure determination techniques (X-ray crystallography and nuclear magnetic resonance (NMR) spectroscopy), validation reports, and additional information on quaternary structures. The wwPDB partners are committed to following the FAIR (Findability, Accessibility, Interoperability, and Reproducibility) principles and have implemented a DOI resolution mechanism that provides access to all the relevant files for a given PDB entry. On average, >250 new entries are added to the archive every week and made available by each wwPDB partner via FTP area. The wwPDB partner sites also develop data access and analysis tools and make these available via their websites. wwPDB continues to work with experts in the community to establish a federation of archives for archiving structures determined using integrative/hybrid method where multiple experimental techniques are used.

Peak picking is a critical step in biomolecular NMR spectroscopy. The program, iPick, presented here provides a scripting tool and a graphical user interface (GUI), which allow the user to perform interactive and intuitive peak picking and validation. The click-and-run GUI requires no computer programming skills, while the scripting tool can be used by more advanced users to customize the application. If used with a multi-core CPU, the multiprocessing feature of iPick reduces the processing time significantly by invoking parallel computing. The GUI is a plugin, compatible with the popular NMRFAM-SPARKY software package and its newly released successor, the POKY software. Features implemented in iPick include automated noise level detection and threshold setting, cross-validation against multiple spectra, and a method for quantifying peak reliability. The iPick software is cross-platform, open-source, and freely available from https://github.com/pokynmr/ipick.

The Ebola Virus is a causative agent of viral hemorrhagic fever outbreaks and a potential global health risk. The outbreak in West Africa (2013–2016) led to 11,000+ deaths and 30,000+ Ebola infected individuals. The current outbreak in the Democratic Republic of Congo (DRC) with 3000+ confirmed cases and 2000+ deaths attributed to Ebola virus infections provides a reminder that innovative countermeasures are still needed. Ebola virus encodes 7 open reading frames (ORFs). Of these, the nucleocapsid protein (eNP) encoded by the first ORF plays many significant roles, including a role in viral RNA synthesis. Here we describe efforts to target the C-terminal domain of eNP (eNP-CTD) that contains highly conserved residues 641–739 as a pan-Ebola antiviral target. Interactions of eNP-CTD with Ebola Viral Protein 30 (eVP30) and Viral Protein 40 (eVP40) have been shown to be crucial for viral RNA synthesis, virion formation, and virion transport. We used nuclear magnetic response (NMR)-based methods to screened the eNP-CTD against a fragment library. Perturbations of 1D 1H NMR spectra identified of 48 of the 439 compounds screened as potential eNP CTD interactors. Subsequent analysis of these compounds to measure chemical shift perturbations in 2D 1H,15N NMR spectra of 15N-labeled protein identified six with low millimolar affinities. All six perturbed an area consisting mainly of residues at or near the extreme C-terminus that we named “Site 1” while three other sites were perturbed by other compounds. Our findings here demonstrate the potential utility of eNP as a target, several fragment hits, and provide an experimental pipeline to validate viral-viral interactions as potential panfiloviral inhibitor targets.

Arabidopsis thaliana contains 36 known members of a class of small proteins known as rapid alkalinization factors (RALF). We succeeded in overexpressing one of these proteins, RALF8, which we found to inhibit plant root growth, and labeled it uniformly with 13C and 15N for NMR analysis. RALF8, which contains four cysteine residues, proved to be a challenging target for structure determination because much of the protein is discorded. We used non-uniform sampling (NUS) for 3D NMR collection followed by spectral reconstruction. In determining the solution structure of RALF8, we used the latest version of the Integrative NMR platform, which includes the software tools described below. Backbone and sidechain signals were automatically detected and assigned by tools in NMRFAM-SPARKY. Tools in the I-PINE web server yielded structural information including the presence of two disulfide bridges. The disulfide pairing was determined by hetNOE analysis and confirmed by data from an optimized 1H,13C-HSQC-NOESY-1H,13C-HSQC pulse program. The 3D structure was determined automatically by AUDANA algorithm in the PONDEROSA-C/S suite, which automatically assigns NOE cross peaks and generates distance and angle restraints. After refining the restraints by the visual validation module in PONDEROSA-Analyzer, the Final Step with Explicit Water Refinement option was used in calculating 100 conformers and selecting the 20 conformers with lowest energy, which were used to represent the solution structure. The root mean square deviation (RMSD) between the backbone heavy atoms of all residues in the superimposed structures was 12.8 Å, consistent with overall dynamic disorder. Two loops between the disulfides (C21–29 and C41–47) were well-ordered with 0.6 and 0.7 Å RMSDs respectively. All assigned chemical shifts and atomic coordinates are available under PDB 6NU4 and BMRB 30565.

The Biological Magnetic Resonance Data Bank (BioMagResBank or BMRB), founded in 1988, serves as the archive for data generated by nuclear magnetic resonance (NMR) spectroscopy of biological systems. NMR spectroscopy is unique among biophysical approaches in its ability to provide a broad range of atomic and higher-level information relevant to the structural, dynamic, and chemical properties of biological macromolecules, as well as report on metabolite and natural product concentrations in complex mixtures and their chemical structures. BMRB became a core member of the Worldwide Protein Data Bank (wwPDB) in 2007, and the BMRB archive is now a core archive of the wwPDB. Currently, about 10% of the structures deposited into the PDB archive are based on NMR spectroscopy. BMRB stores experimental and derived data from biomolecular NMR studies. Newer BMRB biopolymer depositions are divided about evenly between those associated with structure determinations (atomic coordinates and supporting information archived in the PDB) and those reporting experimental information on molecular dynamics, conformational transitions, ligand binding, assigned chemical shifts, or other results from NMR spectroscopy. BMRB also provides resources for NMR studies of metabolites and other small molecules that are often macromolecular ligands and/or nonstandard residues. This chapter is directed to the structural biology community rather than the metabolomics and natural products community. Our goal is to describe various BMRB services offered to structural biology researchers and how they can be accessed and utilized. These services can be classified into four main groups: (1) data deposition, (2) data retrieval, (3) data analysis, and (4) services for NMR spectroscopists and software developers. The chapter also describes the NMR-STAR data format used by BMRB and the tools provided to facilitate its use. For programmers, BMRB offers an application programming interface (API) and libraries in the Python and R languages that enable users to develop their own BMRB-based tools for data analysis, visualization, and manipulation of NMR-STAR formatted files. BMRB also provides users with direct access tools through the NMRbox platform.

Bromodomain-containing proteins are often part of chromatin-modifying complexes, and their activity can lead to altered expression of genes that drive cancer, inflammation and neurological disorders in humans. Bromodomain-PHD finger protein 1 (BRPF1) is part of the MOZ (monocytic leukemic zinc-finger protein) HAT (histone acetyltransferase) complex, which is associated with chromosomal translocations known to contribute to the development of acute myeloid leukemia (AML). BRPF1 contains a unique combination of chromatin reader domains including two plant homeodomain (PHD) fingers separated by a zinc knuckle (PZP domain), a bromodomain, and a proline-tryptophan-tryptophan-proline (PWWP) domain. BRPF1 is known to recruit the MOZ HAT complex to chromatin by recognizing acetylated lysine residues on the N-terminal histone tail region through its bromodomain. However, histone proteins can contain several acetylation modifications on their N-terminus, and it is unknown how additional marks influence bromodomain recruitment to chromatin. Here, we identify the BRPF1 bromodomain as a selective reader of di-acetyllysine modifications on histone H4. We used ITC assays to characterize the binding of di-acetylated histone ligands to the BRPF1 bromodomain and found that the domain binds preferentially to histone peptides H4K5acK8ac and H4K5acK12ac. Analytical ultracentrifugation (AUC) experiments revealed that the monomeric state of the BRPF1 bromodomain coordinates di-acetylated histone ligands. NMR chemical shift perturbation studies, along with binding and mutational analyses, revealed non-canonical regions of the bromodomain-binding pocket that are important for histone tail recognition. Together, our findings provide critical information on how the combinatorial action of post-translational modifications can modulate BRPF1 bromodomain binding and specificity.

Bromodomains exhibit preferences for specific patterns of post-translational modifications on core and variant histone proteins. We examined the ligand specificity of the ATAD2B bromodomain and compared it to its closely related paralogue in ATAD2. We show that the ATAD2B bromodomain recognizes mono- and diacetyllysine modifications on histones H4 and H2A. A structure-function approach was used to identify key residues in the acetyllysine-binding pocket that dictate the molecular recognition process, and we examined the binding of an ATAD2 bromodomain inhibitor by ATAD2B. Our analysis demonstrated that critical contacts required for bromodomain inhibitor coordination are conserved between the ATAD2/B bromodomains, with many residues playing a dual role in acetyllysine recognition. We further characterized an alternative splice variant of ATAD2B that results in a loss of function. Our results outline the structural and functional features of the ATAD2B bromodomain and identify a novel mechanism regulating the interaction of the ATAD2B protein with chromatin.

MOTIVATION:Two-dimensional [15N-1H] separated local field solid-state nuclear magnetic resonance (NMR) experiments of membrane proteins aligned in lipid bilayers provide tilt and rotation angles for α-helical segments using Polar Index Slant Angle (PISA)-wheel models. No integrated software has been made available for data analysis and visualization.RESULTS:We have developed the PISA-SPARKY plugin to seamlessly integrate PISA-wheel modeling into the NMRFAM-SPARKY platform. The plugin performs basic simulations, exhaustive fitting against experimental spectra, error analysis and dipolar and chemical shift wave plotting. The plugin also supports PyMOL integration and handling of parameters that describe variable alignment and dynamic scaling encountered with magnetically aligned media, ensuring optimal fitting and generation of restraints for structure calculation.AVAILABILITY AND IMPLEMENTATION:PISA-SPARKY is freely available in the latest version of NMRFAM-SPARKY from the National Magnetic Resonance Facility at Madison (http://pine.nmrfam.wisc.edu/download_packages.html), the NMRbox Project (https://nmrbox.org) and to subscribers of the SBGrid (https://sbgrid.org). The pisa.py script is available and documented on GitHub (https://github.com/weberdak/pisa.py) along with a tutorial video and sample data.SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.

MOTIVATION:Correlated Nuclear Magnetic Resonance (NMR) chemical shift changes identified through the CHEmical Shift Projection Analysis (CHESPA) and CHEmical Shift Covariance Analysis (CHESCA) reveal pathways of allosteric transitions in biological macromolecules. To address the need for an automated platform that implements CHESPA and CHESCA and integrates them with other NMR analysis software packages, we introduce here integrated plugins for NMRFAM-SPARKY that implement the seamless detection and visualization of allosteric networks.AVAILABILITY AND IMPLEMENTATION:CHESCA-SPARKY and CHESPA-SPARKY are available in the latest version of NMRFAM-SPARKY from the National Magnetic Resonance Facility at Madison (http://pine.nmrfam.wisc.edu/download_packages.html), the NMRbox Project (https://nmrbox.org) and to subscribers to the SBGrid (https://sbgrid.org). The assigned spectra involved in this study and tutorial videos using this dataset are available at https://sites.google.com/view/chescachespa-sparky.SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics Online.

The chemical composition of saccharide complexes underlies their biomedical activities as biomarkers for cardiometabolic disease, various types of cancer, and other conditions. However, because these molecules may undergo major structural modifications, distinguishing between compounds of saccharide and non-saccharide origin becomes a challenging computational problem that hinders the aggregation of information about their bioactive moieties. We have developed an algorithm and software package called “Cheminformatics Tool for Probabilistic Identification of Carbohydrates” (CTPIC) that analyzes the covalent structure of a compound to yield a probabilistic measure for distinguishing saccharides and saccharide-derivatives from non-saccharides. CTPIC analysis of the RCSB Ligand Expo (database of small molecules found to bind proteins in the Protein Data Bank) led to a substantial increase in the number of ligands characterized as saccharides. CTPIC analysis of Protein Data Bank identified 7.7% of the proteins as saccharide-binding. CTPIC is freely available as a webservice at ( http://ctpic.nmrfam.wisc.edu ).

The self-assembly of collagen-mimetic peptides (CMPs) that form sticky-ended triple helices has allowed the production of surprisingly stable artificial collagen fibers and hydrogels. Assembly through sticky ends requires the recognition of a single strand by a templated strand dimer. Although CMPs and their triple helices have been studied extensively, the structure of a strand dimer is unknown. Here, we evaluate the physical characteristics of such dimers, using disulfide-templated (PPG)10 dimers as a model. Such "linked-dimers" retain their collagen-like structure even in the absence of a third strand, but only when their strands are capable of adopting a triple-helical fold. The intrinsic collagen-like structure of templated CMP pairs helps to explain the success of sticky-ended CMP association and changes the conception of new synthetic collagen designs.