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Gaetano T Montelione

Publications and source records attributed to Gaetano T Montelione.

At least 19 recordsLinked to original sources
PubMed2026

Assessing Metal Ion Assignment Accuracy in Protein Data Bank Models via Elemental Spectroscopy.

Accurate representation of metal ions in macromolecular structures is critical for chemical interpretation, computational modeling, and machine-learning methods that rely on Protein Data Bank (PDB) entries. However, the elemental identity of metals modeled in crystallographic structures is often inferred indirectly and rarely validated experimentally. Here, we combine Particle Induced X-ray Emission (PIXE) and X-ray Fluorescence Spectroscopy (XRFS) to determine the elemental composition of protein samples used to generate 70 deposited metalloprotein crystal structures. By analyzing the original protein material employed for crystallization, but before the addition of crystallization buffer solutions, we assess whether the modeled metal ions in deposited structures are consistent with experimentally detectable elemental content. We find that in a majority of cases, the metals modeled in the corresponding PDB entries are inconsistent with the metals present in the protein samples before crystallization, or that additional metals are present but not represented in the structural models. Spectroscopic results were integrated with automated crystallographic validation metrics, including real-space Z-difference (RSZD) analysis and systematic rerefinement, to evaluate atomic-number mismatch at metal sites. PIXE and XRFS show strong agreement for dominant elemental signals and provide complementary, scalable approaches for identifying suspect metal assignments. This work does not address physiological or functional metalation but instead highlights a widespread data integrity issue in deposited macromolecular structures, PDB-wide. These results establish an experimentally corroborated link between elemental identity and crystallographic validation metrics, enabling the large-scale detection of chemically inconsistent annotations in structural databases used for computational modeling and machine learning.

Databases, Protein↗
PubMed2025

Modeling Alternative Conformational States in CASP16.

The CASP16 Ensemble Prediction experiment assessed advances in methods for modeling proteins, nucleic acids, and their complexes in multiple conformational states. Targets included systems with experimental structures determined in two or three states, evaluated by direct comparison to experimental coordinates, as well as domain-linker-domain (D-L-D) targets assessed against statistical models from NMR and SAXS data. This paper focuses on the former class of multi-state targets. Ten ensembles were released as community challenges, including ligand-induced conformational changes, protein-DNA complexes, a trimeric protein, a stem-loop RNA, and multiple oligomeric states of a single RNA. For five targets, some groups produced reasonably accurate models of both reference states (best TM-score >0.75). However, with the exception of one protein-ligand complex (T1214), where an apo structure was available as a template, predictors generally failed to capture key structural details distinguishing the states. Overall, accuracy was significantly lower than for single-state targets in other CASP experiments. The most successful approaches generated multiple AlphaFold2 models using enhanced multiple sequence alignments and sampling protocols, followed by model quality based selection. While the AlphaFold3 server performed well on several targets, individual groups outperformed it in specific cases. By contrast, predictions for one protein-DNA complex, three RNA targets, and multiple oligomeric RNA states consistently fell short (TM-score <0.75). These results highlight both progress and persistent challenges in multi-state prediction. Despite recent advances, accurate modeling of conformational ensembles, particularly RNA and large multimeric assemblies, remains a critical frontier for structural biology.

AlphaFold2↗
PubMed2007

Evaluating protein structures determined by structural genomics consortia.

Structural genomics projects are providing large quantities of new 3D structural data for proteins. To monitor the quality of these data, we have developed the protein structure validation software suite (PSVS), for assessment of protein structures generated by NMR or X-ray crystallographic methods. PSVS is broadly applicable for structure quality assessment in structural biology projects. The software integrates under a single interface analyses from several widely-used structure quality evaluation tools, including PROCHECK (Laskowski et al., J Appl Crystallog 1993;26:283-291), MolProbity (Lovell et al., Proteins 2003;50:437-450), Verify3D (Luthy et al., Nature 1992;356:83-85), ProsaII (Sippl, Proteins 1993;17: 355-362), the PDB validation software, and various structure-validation tools developed in our own laboratory. PSVS provides standard constraint analyses, statistics on goodness-of-fit between structures and experimental data, and knowledge-based structure quality scores in standardized format suitable for database integration. The analysis provides both global and site-specific measures of protein structure quality. Global quality measures are reported as Z scores, based on calibration with a set of high-resolution X-ray crystal structures. PSVS is particularly useful in assessing protein structures determined by NMR methods, but is also valuable for assessing X-ray crystal structures or homology models. Using these tools, we assessed protein structures generated by the Northeast Structural Genomics Consortium and other international structural genomics projects, over a 5-year period. Protein structures produced from structural genomics projects exhibit quality score distributions similar to those of structures produced in traditional structural biology projects during the same time period. However, while some NMR structures have structure quality scores similar to those seen in higher-resolution X-ray crystal structures, the majority of NMR structures have lower scores. Potential reasons for this "structure quality score gap" between NMR and X-ray crystal structures are discussed.

Computational Biology↗
PubMed2006

Molecular insights into substrate recognition and catalysis by tryptophan 2,3-dioxygenase.

Tryptophan 2,3-dioxygenase (TDO) and indoleamine 2,3-dioxygenase (IDO) constitute an important, yet relatively poorly understood, family of heme-containing enzymes. Here, we report extensive structural and biochemical studies of the Xanthomonas campestris TDO and a related protein SO4414 from Shewanella oneidensis, including the structure at 1.6-A resolution of the catalytically active, ferrous form of TDO in a binary complex with the substrate L-Trp. The carboxylate and ammonium moieties of tryptophan are recognized by electrostatic and hydrogen-bonding interactions with the enzyme and a propionate group of the heme, thus defining the L-stereospecificity. A second, possibly allosteric, L-Trp-binding site is present at the tetramer interface. The sixth coordination site of the heme-iron is vacant, providing a dioxygen-binding site that would also involve interactions with the ammonium moiety of L-Trp and the amide nitrogen of a glycine residue. The indole ring is positioned correctly for oxygenation at the C2 and C3 atoms. The active site is fully formed only in the binary complex, and biochemical experiments confirm this induced-fit behavior of the enzyme. The active site is completely devoid of water during catalysis, which is supported by our electrochemical studies showing significant stabilization of the enzyme upon substrate binding.

Allosteric Site↗
PubMed2006

FAST-NMR: functional annotation screening technology using NMR spectroscopy.

An abundance of protein structures emerging from structural genomics and the Protein Structure Initiative (PSI) are not amenable to ready functional assignment because of a lack of sequence and structural homology to proteins of known function. We describe a high-throughput NMR methodology (FAST-NMR) to annotate the biological function of novel proteins through the structural and sequence analysis of protein-ligand interactions. This is based on basic tenets of biochemistry where proteins with similar functions will have similar active sites and exhibit similar ligand binding interactions, despite global differences in sequence and structure. Protein-ligand interactions are determined through a tiered NMR screen using a library composed of compounds with known biological activity. A rapid co-structure is determined by combining the experimental identification of the ligand binding site from NMR chemical shift perturbations with the protein-ligand docking program AutoDock. Our CPASS (Comparison of Protein Active Site Structures) software and database are then used to compare this active site with proteins of known function. The methodology is demonstrated using unannotated protein SAV1430 from Staphylococcus aureus.

Amino Acid Sequence↗
PubMed2006

Solution NMR structure of the junction between tropomyosin molecules: implications for actin binding and regulation.

Tropomyosin is a coiled-coil protein that binds head-to-tail along the length of actin filaments in eukaryotic cells, stabilizing them and providing protection from severing proteins. Tropomyosin cooperatively regulates actin's interaction with myosin and mediates the Ca2+ -dependent regulation of contraction by troponin in striated muscles. The N-terminal and C-terminal ends are critical functional determinants that form an "overlap complex". Here we report the solution NMR structure of an overlap complex formed of model peptides. In the complex, the chains of the C-terminal coiled coil spread apart to allow insertion of 11 residues of the N-terminal coiled coil into the resulting cleft. The plane of the N-terminal coiled coil is rotated 90 degrees relative to the plane of the C terminus. A consequence of the geometry is that the orientation of postulated periodic actin binding sites on the coiled-coil surface is retained from one molecule to the next along the actin filament when the overlap complex is modeled into the X-ray structure of tropomyosin determined at 7 Angstroms. Nuclear relaxation NMR data reveal flexibility of the junction, which may function to optimize binding along the helical actin filament and to allow mobility of tropomyosin on the filament surface as it switches between regulatory states.

Actins↗
PubMed2006

A topology-constrained distance network algorithm for protein structure determination from NOESY data.

This article formulates the multidimensional nuclear Overhauser effect spectroscopy (NOESY) interpretation problem using graph theory and presents a novel, bottom-up, topology-constrained distance network analysis algorithm for NOESY cross peak interpretation using assigned resonances. AutoStructure is a software suite that implements this topology-constrained distance network analysis algorithm and iteratively generates structures using the three-dimensional (3D) protein structure calculation programs XPLOR/CNS or DYANA. The minimum input for AutoStructure includes the amino acid sequence, a list of resonance assignments, and lists of 2D, 3D, and/or 4D-NOESY cross peaks. AutoStructure can also analyze homodimeric proteins when X-filtered NOESY experiments are available. The quality of input data and final 3D structures is evaluated using recall, precision, and F-measure (RPF) scores, a statistical measure of goodness of fit with the input data. AutoStructure has been tested on three protein NMR data sets for which high-quality structures have previously been solved by an expert, and yields comparable high-quality distance constraint lists and 3D protein structures in hours. We also compare several protein structures determined using AutoStructure with corresponding homologous proteins determined with other independent methods. The program has been used in more than two dozen protein structure determinations, several of which have already been published.

Algorithms↗
PubMed2006

SPINS: a laboratory information management system for organizing and archiving intermediate and final results from NMR protein structure determinations.

Recent technological advances and experimental techniques have contributed to an increasing number and size of NMR datasets. In order to scale up productivity, laboratory information management systems for handling these extensive data need to be designed and implemented. The SPINS (Standardized ProteIn Nmr Storage) Laboratory Information Management System (LIMS) addresses these needs by providing an interface for archival of complete protein NMR structure determinations, together with functionality for depositing these data to the public BioMagResBank (BMRB). The software tracks intermediate files during each step of an NMR structure-determination process, including: data collection, data processing, resonance assignments, resonance assignment validation, structure calculation, and structure validation. The underlying SPINS data dictionary allows for the integration of various third party NMR data processing and analysis software, enabling users to launch programs they are accustomed to using for each step of the structure determination process directly out of the SPINS user interface.

Computer Graphics↗
PubMed2006

Identification of zinc-ligated cysteine residues based on 13Calpha and 13Cbeta chemical shift data.

Although a significant number of proteins include bound metals as part of their structure, the identification of amino acid residues coordinated to non-paramagnetic metals by NMR remains a challenge. Metal ligands can stabilize the native structure and/or play critical catalytic roles in the underlying biochemistry. An atom's chemical shift is exquisitely sensitive to its electronic environment. Chemical shift data can provide valuable insights into structural features, including metal ligation. In this study, we demonstrate that overlapped 13Cbeta chemical shift distributions of Zn-ligated and non-metal-ligated cysteine residues are largely resolved by the inclusion of the corresponding 13Calpha chemical shift information, together with secondary structural information. We demonstrate this with a bivariate distribution plot, and statistically with a multivariate analysis of variance (MANOVA) and hierarchical logistic regression analysis. Using 287 13Calpha/13Cbeta shift pairs from 79 proteins with known three-dimensional structures, including 86 13Calpha and 13Cbeta shifts for 43 Zn-ligated cysteine residues, along with corresponding oxidation state and secondary structure information, we have built a logistic regression model that distinguishes between oxidized cystines, reduced (non-metal ligated) cysteines, and Zn-ligated cysteines. Classifying cysteines/cystines with a statistical model incorporating all three phenomena resulted in a predictor of Zn ligation with a recall, precision and F-measure of 83.7%, and an accuracy of 95.1%. This model was applied in the analysis of Bacillus subtilis IscU, a protein involved in iron-sulfur cluster assembly. The model predicts that all three cysteines of IscU are metal ligands. We confirmed these results by (i) examining the effect of metal chelation on the NMR spectrum of IscU, and (ii) inductively coupled plasma mass spectrometry analysis. To gain further insight into the frequency of occurrence of non-cysteine Zn ligands, we analyzed the Protein Data Bank and found that 78% of the Zn ligands are histidine and cysteine (with nearly identical frequencies), and 18% are acidic residues aspartate and glutamate.

Bacillus subtilis↗
PubMed2005

Crystal structures of two bacterial 3-hydroxy-3-methylglutaryl-CoA lyases suggest a common catalytic mechanism among a family of TIM barrel metalloenzymes cleaving carbon-carbon bonds.

The enzyme 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) lyase catalyzes the terminal steps in ketone body generation and leucine degradation. Mutations in this enzyme cause a human autosomal recessive disorder called primary metabolic aciduria, which typically kills victims because of an inability to tolerate hypoglycemia. Here we present crystal structures of the HMG-CoA lyases from Bacillus subtilis and Brucella melitensis at 2.7 and 2.3 A resolution, respectively. These enzymes share greater than 45% sequence identity with the human orthologue. Although the enzyme has the anticipated triose-phosphate isomerase (TIM) barrel fold, the catalytic center contains a divalent cation-binding site formed by a cluster of invariant residues that cap the core of the barrel, contrary to the predictions of homology models. Surprisingly, the residues forming this cation-binding site and most of their interaction partners are shared with three other TIM barrel enzymes that catalyze diverse carbon-carbon bond cleavage reactions believed to proceed through enolate intermediates (4-hydroxy-2-ketovalerate aldolase, 2-isopropylmalate synthase, and transcarboxylase 5S). We propose the name "DRE-TIM metallolyases" for this newly identified enzyme family likely to employ a common catalytic reaction mechanism involving an invariant Asp-Arg-Glu (DRE) triplet. The Asp ligates the divalent cation, while the Arg probably stabilizes charge accumulation in the enolate intermediate, and the Glu maintains the precise structural alignment of the Asp and Arg. We propose a detailed model for the catalytic reaction mechanism of HMG-CoA lyase based on the examination of previously reported product complexes of other DRE-TIM metallolyases and induced fit substrate docking studies conducted using the crystal structure of human HMG-CoA lyase (reported in the accompanying paper by Fu, et al. (2006) J. Biol. Chem. 281, 7526-7532). Our model is consistent with extensive mutagenesis results and can guide subsequent studies directed at definitive experimental elucidation of this enzyme's reaction mechanism.

2-Isopropylmalate Synthase↗
PubMed2005

Comparisons of NMR spectral quality and success in crystallization demonstrate that NMR and X-ray crystallography are complementary methods for small protein structure determination.

X-ray crystallography and NMR spectroscopy provide the only sources of experimental data from which protein structures can be analyzed at high or even atomic resolution. The degree to which these methods complement each other as sources of structural knowledge is a matter of debate; it is often proposed that small proteins yielding high quality, readily analyzed NMR spectra are a subset of those that readily yield strongly diffracting crystals. We have examined the correlation between NMR spectral quality and success in structure determination by X-ray crystallography for 159 prokaryotic and eukaryotic proteins, prescreened to avoid proteins providing polydisperse and/or aggregated samples. This study demonstrates that, across this protein sample set, the quality of a protein's [15N-1H]-heteronuclear correlation (HSQC) spectrum recorded under conditions generally suitable for 3D structure determination by NMR, a key predictor of the ability to determine a structure by NMR, is not correlated with successful crystallization and structure determination by X-ray crystallography. These results, together with similar results of an independent study presented in the accompanying paper (Yee, et al., J. Am. Chem. Soc., accompanying paper), demonstrate that X-ray crystallography and NMR often provide complementary sources of structural data and that both methods are required in order to optimize success for as many targets as possible in large-scale structural proteomics efforts.

Animals↗
PubMed2005

Structural and functional evidence for Bacillus subtilis PaiA as a novel N1-spermidine/spermine acetyltransferase.

Bacillus subtilis PaiA has been implicated in the negative control of sporulation as well as production of degradative enzymes. PaiA shares recognizable sequence homology with N-acetyltransferases, including those that can acetylate spermidine/spermine substrates. We have determined the crystal structure of PaiA in complex with CoA at 1.9 A resolution and found that PaiA is a member of the N-acetyltransferase superfamily of enzymes. Unexpectedly, we observed the binding of an oxidized CoA dimer in the active site of PaiA, and the structural information suggests the substrates of the enzyme could be linear, positively charged compounds. Our biochemical characterization is also consistent with this possibility, since purified PaiA possesses N1-acetyltransferase activity toward polyamine substrates including spermidine and spermine. Further, conditional overexpression of PaiA in bacteria results in increased acetylation of endogenous spermidine pools. Thus, our structural and biochemical analyses indicate that PaiA is a novel N-acetyltransferase capable of acetylating both spermidine and spermine. In this way, the pai operon may function in regulating intracellular polyamine concentrations and/or binding capabilities. In addition to preventing toxicity due to polyamine excess, this function may also serve to regulate expression of certain bacterial gene products such as those involved in sporulation.

Acetyltransferases↗
PubMed2005

PubNet: a flexible system for visualizing literature derived networks.

We have developed PubNet, a web-based tool that extracts several types of relationships returned by PubMed queries and maps them into networks, allowing for graphical visualization, textual navigation, and topological analysis. PubNet supports the creation of complex networks derived from the contents of individual citations, such as genes, proteins, Protein Data Bank (PDB) IDs, Medical Subject Headings (MeSH) terms, and authors. This feature allows one to, for example, examine a literature derived network of genes based on functional similarity.

Databases, Bibliographic↗
PubMed2005

NMR data collection and analysis protocol for high-throughput protein structure determination.

A standardized protocol enabling rapid NMR data collection for high-quality protein structure determination is presented that allows one to capitalize on high spectrometer sensitivity: a set of five G-matrix Fourier transform NMR experiments for resonance assignment based on highly resolved 4D and 5D spectral information is acquired in conjunction with a single simultaneous 3D 15N,13C(aliphatic),13C(aromatic)-resolved [1H,1H]-NOESY spectrum providing 1H-1H upper distance limit constraints. The protocol was integrated with methodology for semiautomated data analysis and used to solve eight NMR protein structures of the Northeast Structural Genomics Consortium pipeline. The molecular masses of the hypothetical target proteins ranged from 9 to 20 kDa with an average of approximately 14 kDa. Between 1 and 9 days of instrument time were invested per structure, which is less than approximately 10-25% of the measurement time routinely required to date with conventional approaches. The protocol presented here effectively removes data collection as a bottleneck for high-throughput solution structure determination of proteins up to at least approximately 20 kDa, while concurrently providing spectra that are highly amenable to fast and robust analysis.

Data Collection↗
PubMed2005

Clustering algorithms for identifying core atom sets and for assessing the precision of protein structure ensembles.

An important open question in the field of NMR-based biomolecular structure determination is how best to characterize the precision of the resulting ensemble of structures. Typically, the RMSD, as minimized in superimposing the ensemble of structures, is the preferred measure of precision. However, the presence of poorly determined atomic coordinates and multiple "RMSD-stable domains"--locally well-defined regions that are not aligned in global superimpositions--complicate RMSD calculations. In this paper, we present a method, based on a novel, structurally defined order parameter, for identifying a set of core atoms to use in determining superimpositions for RMSD calculations. In addition we present a method for deciding whether to partition that core atom set into "RMSD-stable domains" and, if so, how to determine partitioning of the core atom set. We demonstrate our algorithm and its application in calculating statistically sound RMSD values by applying it to a set of NMR-derived structural ensembles, superimposing each RMSD-stable domain (or the entire core atom set, where appropriate) found in each protein structure under consideration. A parameter calculated by our algorithm using a novel, kurtosis-based criterion, the epsilon-value, is a measure of precision of the superimposition that complements the RMSD. In addition, we compare our algorithm with previously described algorithms for determining core atom sets. The methods presented in this paper for biomolecular structure superimposition are quite general, and have application in many areas of structural bioinformatics and structural biology.

Algorithms↗