Effects of NMR spectral resolution on protein structure calculation

Adequate digital resolution and signal sensitivity are two critical factors for protein structure determinations by solution NMR spectroscopy. The prime objective for obtaining high digital resolution is to resolve peak overlap, especially in NOESY spectra with thousands of signals where the signal analysis needs to be performed on a large scale. Achieving maximum digital resolution is usually limited by the practically available measurement time. We developed a method utilizing non-uniform sampling for balancing digital resolution and signal sensitivity, and performed a large-scale analysis of the effect of the digital resolution on the accuracy of the resulting protein structures. Structure calculations were performed as a function of digital resolution for about 400 proteins with molecular sizes ranging between 5 and 33 kDa. The structural accuracy was assessed by atomic coordinate RMSD values from the reference structures of the proteins. In addition, we monitored also the number of assigned NOESY cross peaks, the average signal sensitivity, and the chemical shift spectral overlap. We show that high resolution is equally important for proteins of every molecular size. The chemical shift spectral overlap depends strongly on the corresponding spectral digital resolution. Thus, knowing the extent of overlap can be a predictor of the resulting structural accuracy. Our results show that for every molecular size a minimal digital resolution, corresponding to the natural linewidth, needs to be achieved for obtaining the highest accuracy possible for the given protein size using state-of-the-art automated NOESY assignment and structure calculation methods

NMR solution structure of a chymotrypsin inhibitor from the Taiwan cobra Naja naja atra

The Taiwan cobra (Naja naja atra) chymotrypsin inhibitor (NACI) consists of 57 amino acids and is related to other Kunitz-type inhibitors such as bovine pancreatic trypsin inhibitor (BPTI) and Bungarus fasciatus fraction IX (BF9), another chymotrypsin inhibitor. Here we present the solution structure of NACI. We determined the NMR structure of NACI with a root-mean-square deviation of 0.37 Å for the backbone atoms and 0.73 Å for the heavy atoms on the basis of 1,075 upper distance limits derived from NOE peaks measured in its NOESY spectra. To investigate the structural characteristics of NACI, we compared the three-dimensional structure of NACI with BPTI and BF9. The structure of the NACI protein comprises one 310-helix, one α-helix and one double-stranded antiparallel β-sheet, which is comparable with the secondary structures in BPTI and BF9. The RMSD value between the mean structures is 1.09 Å between NACI and BPTI and 1.27 Å between NACI and BF9. In addition to similar secondary and tertiary structure, NACI might possess similar types of protein conformational fluctuations as reported in BPTI, such as Cys14–Cys38 disulfide bond isomerization, based on line broadening of resonances from residues which are mainly confined to a region around the Cys14–Cys38 disulfide bond

El carácter prefigurativo de los capítulos iniciales de El Buscón y su tematización del código de lectura

En este trabajo se sostiene que El Buscón no es un mero continuador de la línea inaugurada por el Lazarillo y seguida por el Guzmán, sino una obra singular que, aun utilizando algunos elementos característicos del modelo picaresco, deja entrever un pensamiento y un estilo muy originales. Para captar la novedad de la escritura quevedesca, basta analizar los primeros tres capítulos de la obra, concebidos, cada uno a su manera, como prefiguraciones. El capítulo I contiene una honda reflexión, poéticamente transformada en imágenes y situaciones cotidianas, sobre ese círculo vicioso que es el mundo. El capítulo II contiene una mise-enabyme del enunciado presente en la obra: el anhelo de ascensión social del protagonista y su inevitable fracaso. El III tematiza, a través del famoso retrato del licenciado Cabra, el código de la escritura, basado en la tensa relación que existe entre un mundo falto de sustancia y la compensación de tal carencia a través de una escritura ingeniosa, que es lo que más importa a este autor. The present essay states that El Buscón is not merely a continuation of the picaresque sequence started by Lázaro de Tormes and followed by Guzmán de Alfarache, but a singular work that, even though uses some key features of the picaresque genre, shows a highly original style and thought. An analysis of chapters one to three, which have been conceived of as anticipatory, helps to understand the newness of Quevedo’s art. Chapter one contains a deep, poetically hidden reflection on the vicious circle the world is supposed to be. Chapter two contains a miseen- abyme of the main motif of the novel as a whole: Pablos’ unfulfilled desire for social climbing. Chapter three underlines writing itself through licentiate Cabra’s unforgettable portrait, which reveals the existence of a tense relationship between a world lacking of substance and an ingenious writing capable of making up for that lack of substance, which is Quevedo’s primary concern

La «prova glorificante»: Paradiso XXXIII

Nella sua lettura del canto finale, Paradiso XXXIII, Georges Güntert ricorda come da un punto di vista semiotico la visione mistica corrisponda alla fase glorificante della prova, che conduce al definitivo riconoscimento dell’eroe. Si tratta quindi della sanzione ultima tramite cui Dante fa legittimare la propria missione poetica. Anche in quest’esperienza del trascendente è comunque necessario distinguere tra il personaggiovisionario (al passato e al presente), il narratore e il livello del testo. – Un aspetto importante del livello discorsivo (o del testo) è la configurazione numerica. La prima macrosequenza di 45 versi, riservata alla preghiera mariana di San Bernardo, è dominata dal numero di Beatrice, il 9. L’intero canto ha 145 versi (45+100) ed è informato, nella seconda macrosequenza, dal numero divino 10 (33 terzine +1 verso). Il climax del canto «Un punto solo m’è maggior letargo...», che merita particolare attenzione, è fatto oggetto di uno studio approfondito che mostra la centralità del concetto dell’admiratio.In his reading of Paradiso XXXIII, Georges Güntert emphasises the semiotic correspondence of the mystical vision and the glorifying test that leads to the final acknowledgement of the hero. It is through this final sanction that Dante legitimises his own poetic mission. However, even within this experience of the transcendent, a clear distinction has to be made between the figure of the visionary hero (past and present), that of the narrator and the text itself. – An important aspect on the level of discourse (i.e. that of the text) is represented by the numerical configuration of this canto. Its first part consists of 45 verses entirely occupied by Saint Bernard’s prayer to the Virgin and is dominated by Beatrice’s number 9 (nine tercets). The whole canto counts 145 verses (45+100) and its second part is marked by the divine number 10 (33 tercets + 1 verse). The canto’s climax («Un punto solo m’è maggior letargo...») is particularly meaningful: a close analysis of this verse shows that the concept of admiratio is at the heart of it

Increased Reliability of Nuclear Magnetic Resonance Protein Structures by Consensus Structure Bundles

SummaryNuclear magnetic resonance (NMR) structures are represented by bundles of conformers calculated from different randomized initial structures using identical experimental input data. The spread among these conformers indicates the precision of the atomic coordinates. However, there is as yet no reliable measure of structural accuracy, i.e., how close NMR conformers are to the “true” structure. Instead, the precision of structure bundles is widely (mis)interpreted as a measure of structural quality. Attempts to increase precision often overestimate accuracy by tight bundles of high precision but much lower accuracy. To overcome this problem, we introduce a protocol for NMR structure determination with the software package CYANA, which produces, like the traditional method, bundles of conformers in agreement with a common set of conformational restraints but with a realistic precision that is, throughout a variety of proteins and NMR data sets, a much better estimate of structural accuracy than the precision of conventional structure bundles

Objective identification of residue ranges for the superposition of protein structures

<p>Abstract</p> <p>Background</p> <p>The automation of objectively selecting amino acid residue ranges for structure superpositions is important for meaningful and consistent protein structure analyses. So far there is no widely-used standard for choosing these residue ranges for experimentally determined protein structures, where the manual selection of residue ranges or the use of suboptimal criteria remain commonplace.</p> <p>Results</p> <p>We present an automated and objective method for finding amino acid residue ranges for the superposition and analysis of protein structures, in particular for structure bundles resulting from NMR structure calculations. The method is implemented in an algorithm, CYRANGE, that yields, without protein-specific parameter adjustment, appropriate residue ranges in most commonly occurring situations, including low-precision structure bundles, multi-domain proteins, symmetric multimers, and protein complexes. Residue ranges are chosen to comprise as many residues of a protein domain that increasing their number would lead to a steep rise in the RMSD value. Residue ranges are determined by first clustering residues into domains based on the distance variance matrix, and then refining for each domain the initial choice of residues by excluding residues one by one until the relative decrease of the RMSD value becomes insignificant. A penalty for the opening of gaps favours contiguous residue ranges in order to obtain a result that is as simple as possible, but not simpler. Results are given for a set of 37 proteins and compared with those of commonly used protein structure validation packages. We also provide residue ranges for 6351 NMR structures in the Protein Data Bank.</p> <p>Conclusions</p> <p>The CYRANGE method is capable of automatically determining residue ranges for the superposition of protein structure bundles for a large variety of protein structures. The method correctly identifies ordered regions. Global structure superpositions based on the CYRANGE residue ranges allow a clear presentation of the structure, and unnecessary small gaps within the selected ranges are absent. In the majority of cases, the residue ranges from CYRANGE contain fewer gaps and cover considerably larger parts of the sequence than those from other methods without significantly increasing the RMSD values. CYRANGE thus provides an objective and automatic method for standardizing the choice of residue ranges for the superposition of protein structures.</p

Protein NMR structure determination with automated NOE-identification in the NOESY spectra using the new software ATNOS

Novel algorithms are presented for automated NOESY peak picking and NOE signal identification in homonuclear 2D and heteronuclear-resolved 3D [1H,1H]-NOESY spectra during denovoprotein structure determination by NMR, which have been implemented in the new software ATNOS (automated NOESY peak picking). The input for ATNOS consists of the amino acid sequence of the protein, chemical shift lists from the sequence-specific resonance assignment, and one or several 2D or 3D NOESY spectra. In the present implementation, ATNOS performs multiple cycles of NOE peak identification in concert with automated NOE assignment with the software CANDID and protein structure calculation with the program DYANA. In the second and subsequent cycles, the intermediate protein structures are used as an additional guide for the interpretation of the NOESY spectra. By incorporating the analysis of the raw NMR data into the process of automated denovoprotein NMR structure determination, ATNOS enables direct feedback between the protein structure, the NOE assignments and the experimental NOESY spectra. The main elements of the algorithms for NOESY spectral analysis are techniques for local baseline correction and evaluation of local noise level amplitudes, automated determination of spectrum-specific threshold parameters, the use of symmetry relations, and the inclusion of the chemical shift information and the intermediate protein structures in the process of distinguishing between NOE peaks and artifacts. The ATNOS procedure has been validated with experimental NMR data sets of three proteins, for which high-quality NMR structures had previously been obtained by interactive interpretation of the NOESY spectra. The ATNOS-based structures coincide closely with those obtained with interactive peak picking. Overall, we present the algorithms used in this paper as a further important step towards objective and efficient de novoprotein structure determination by NM

Rapid protein assignments and structures from raw NMR spectra with the deep learning technique ARTINA

Nuclear Magnetic Resonance (NMR) spectroscopy is one of the major techniques in structural biology with over 11,800 protein structures deposited in the Protein Data Bank. NMR can elucidate structures and dynamics of small and medium size proteins in solution, living cells, and solids, but has been limited by the tedious data analysis process. It typically requires weeks or months of manual work of a trained expert to turn NMR measurements into a protein structure. Automation of this process is an open problem, formulated in the field over 30 years ago. Here, we present a solution to this challenge that enables the completely automated analysis of protein NMR data within hours after completing the measurements. Using only NMR spectra and the protein sequence as input, our machine learning-based method, ARTINA, delivers signal positions, resonance assignments, and structures strictly without any human intervention. Tested on a 100-protein benchmark comprising 1329 multidimensional NMR spectra, ARTINA demonstrated its ability to solve structures with 1.44 {\AA} median RMSD to the PDB reference and to identify 91.36% correct NMR resonance assignments. ARTINA can be used by non-experts, reducing the effort for a protein assignment or structure determination by NMR essentially to the preparation of the sample and the spectra measurements