NMR-Based Determination of the 3D Structure of the Ligand-Protein Interaction Site without Protein Resonance Assignment.

Molecular replacement in X-ray crystallography is the prime method for establishing structure-activity relationships of pharmaceutically relevant molecules. Such an approach is not available for NMR. Here, we establish a comparable method, called NMR molecular replacement (NMR(2)).

Systematic evaluation of combined automated NOE assignment and structure calculation with CYANA.

The automated assignment of NOESY cross peaks has become a fundamental technique for NMR protein structure analysis. A widely used algorithm for this purpose is implemented in the program CYANA. It has been used for a large number of structure determinations of proteins in solution but a systematic evaluation of its performance has not yet been reported.

Increased reliability of nuclear magnetic resonance protein structures by consensus structure bundles.

Nuclear 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.

RBFOX and SUP-12 sandwich a G base to cooperatively regulate tissue-specific splicing.

Tissue-specific alternative pre-mRNA splicing is often cooperatively regulated by multiple splicing factors, but the structural basis of cooperative RNA recognition is poorly understood. In Caenorhabditis elegans, ligand binding specificity of fibroblast growth factor receptors (FGFRs) is determined by mutually exclusive alternative splicing of the sole FGFR gene, egl-15. Here we determined the solution structure of a ternary complex of the RNA-recognition motif (RRM) domains from the RBFOX protein ASD-1, SUP-12 and their target RNA from egl-15.

Peak picking NMR spectral data using non-negative matrix factorization.

Background: Simple peak-picking algorithms, such as those based on lineshape fitting, perform well when peaks are completely resolved in multidimensional NMR spectra, but often produce wrong intensities and frequencies for overlapping peak clusters. For example, NOESY-type spectra have considerable overlaps leading to significant peak-picking intensity errors, which can result in erroneous structural restraints. Precise frequencies are critical for unambiguous resonance assignments.

Automated and assisted RNA resonance assignment using NMR chemical shift statistics.

The three-dimensional structure determination of RNAs by NMR spectroscopy relies on chemical shift assignment, which still constitutes a bottleneck. In order to develop more efficient assignment strategies, we analysed relationships between sequence and (1)H and (13)C chemical shifts. Statistics of resonances from regularly Watson-Crick base-paired RNA revealed highly characteristic chemical shift clusters.

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.

The coherent organization of mental life depends on mechanisms for context-sensitive gain-control that are impaired in schizophrenia.

There is rapidly growing evidence that schizophrenia involves changes in context-sensitive gain-control and probabilistic inference. In addition to the well-known cognitive disorganization to which these changes lead, basic aspects of vision are also impaired, as discussed by other papers on this Frontiers Research Topic. The aim of this paper is to contribute to our understanding of such findings by examining five central hypotheses.

Protein structure validation by generalized linear model root-mean-square deviation prediction.

Large-scale initiatives for obtaining spatial protein structures by experimental or computational means have accentuated the need for the critical assessment of protein structure determination and prediction methods. These include blind test projects such as the critical assessment of protein structure prediction (CASP) and the critical assessment of protein structure determination by nuclear magnetic resonance (CASD-NMR). An important aim is to establish structure validation criteria that can reliably assess the accuracy of a new protein structure.

SORN: a self-organizing recurrent neural network.

Understanding the dynamics of recurrent neural networks is crucial for explaining how the brain processes information. In the neocortex, a range of different plasticity mechanisms are shaping recurrent networks into effective information processing circuits that learn appropriate representations for time-varying sensory stimuli. However, it has been difficult to mimic these abilities in artificial neural network models.

Experience-driven formation of parts-based representations in a model of layered visual memory.

Growing neuropsychological and neurophysiological evidence suggests that the visual cortex uses parts-based representations to encode, store and retrieve relevant objects. In such a scheme, objects are represented as a set of spatially distributed local features, or parts, arranged in stereotypical fashion. To encode the local appearance and to represent the relations between the constituent parts, there has to be an appropriate memory structure formed by previous experience with visual objects.