Annotation of Human Exome Gene Variants with Consensus Pathogenicity.

A novel approach is developed to address the challenge of annotating with phenotypic effects those exome variants for which relevant empirical data are lacking or minimal. The predictive annotation method is implemented as a stacked ensemble of supervised base-learners, including distributed random forest and gradient boosting machines. Ensemble models were trained and cross-validated on evidence-based categorical variant effect annotations from the ClinVar database, and were applied to 84 million non-synonymous single nucleotide variants (SNVs).

Expitope 2.0: a tool to assess immunotherapeutic antigens for their potential cross-reactivity against naturally expressed proteins in human tissues.

Background: Adoptive immunotherapy offers great potential for treating many types of cancer but its clinical application is hampered by cross-reactive T cell responses in healthy human tissues, representing serious safety risks for patients. We previously developed a computational tool called Expitope for assessing cross-reactivity (CR) of antigens based on tissue-specific gene expression. However, transcript abundance only indirectly indicates protein expression.

Assessment of cancer and virus antigens for cross-reactivity in human tissues.

Motivation: Cross-reactivity (CR) or invocation of autoimmune side effects in various tissues has important safety implications in adoptive immunotherapy directed against selected antigens. The ability to predict CR (on-target and off-target toxicities) may help in the early selection of safer therapeutically relevant target antigens.

Results: We developed a methodology for the calculation of quantitative CR for any defined peptide epitope.

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.

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.

Estimating structure quality trends in the Protein Data Bank by equivalent resolution.

The quality of protein structures obtained by different experimental and ab-initio calculation methods varies considerably. The methods have been evolving over time by improving both experimental designs and computational techniques, and since the primary aim of these developments is the procurement of reliable and high-quality data, better techniques resulted on average in an evolution toward higher quality structures in the Protein Data Bank (PDB). Each method leaves a specific quantitative and qualitative "trace" in the PDB entry.

Fast automated NMR spectroscopy of short-lived biological samples.

Faster than death: NMR techniques that make use of nonlinear sampling and hyperdimensional processing enable the recording of complete NMR data sets for the automated assignment of the backbone and side-chain resonances of short-lived protein samples of cell lysates.

A universal expression tag for structural and functional studies of proteins.

Modified ubiquitin sequences, each completed with a His tag and a TEV cleavage site, were designed to enhance the expression of protein/peptide targets. With this new system we have been able to characterize several peptide-protein interactions by ITC and by NMR and CD spectroscopic methods, including the interactions of LIR domains with autophagy modifiers.

Blind testing of routine, fully automated determination of protein structures from NMR data.

The protocols currently used for protein structure determination by nuclear magnetic resonance (NMR) depend on the determination of a large number of upper distance limits for proton-proton pairs. Typically, this task is performed manually by an experienced researcher rather than automatically by using a specific computer program. To assess whether it is indeed possible to generate in a fully automated manner NMR structures adequate for deposition in the Protein Data Bank, we gathered 10 experimental data sets with unassigned nuclear Overhauser effect spectroscopy (NOESY) peak lists for various proteins of unknown structure, computed structures for each of them using different, fully automatic programs, and compared the results to each other and to the manually solved reference structures that were not available at the time the data were provided.

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.

Automatic assignment of protein backbone resonances by direct spectrum inspection in targeted acquisition of NMR data.

The necessity to acquire large multidimensional datasets, a basis for assignment of NMR resonances, results in long data acquisition times during which substantial degradation of a protein sample might occur. Here we propose a method applicable for such a protein for automatic assignment of backbone resonances by direct inspection of multidimensional NMR spectra. In order to establish an optimal balance between completeness of resonance assignment and losses of cross-peaks due to dynamic processes/degradation of protein, assignment of backbone resonances is set as a stirring criterion for dynamically controlled targeted nonlinear NMR data acquisition.

Hyperdimensional NMR spectroscopy with nonlinear sampling.

An approach is described for joint interleaved recording, real-time processing, and analysis of NMR data sets. The method employs multidimensional decomposition to find common information in a set of conventional triple-resonance spectra recorded in the nonlinear sampling mode, and builds a model of hyperdimensional (HD) spectrum. While preserving sensitivity per unit of measurement time and allowing for maximal spectral resolution, the approach reduces data collection time on average by 2 orders of magnitude compared to the conventional method.

Targeted acquisition for real-time NMR spectroscopy.

A target-oriented approach for the acquisition of information in biomolecular NMR spectroscopy is being developed. This approach combines concurrent data accumulation, processing, and monitoring of spectral quality. Real-time estimation of parameters allows acquisition to be stopped when results are complete and have a specified precision.

Removal of a time barrier for high-resolution multidimensional NMR spectroscopy.

We introduce the recursive multidimensional decomposition (R-MDD) method to speed recording of high-resolution NMR spectra. The measurement time is logarithmically dependent on the sizes of indirect spectral dimensions. R-MDD has the sensitivity and resolution advantages of optimized nonuniform acquisition schemes and is applicable to all types of biomolecular spectra.

Quantification of H/D isotope effects on protein hydrogen-bonds by h3JNC' and 1JNC' couplings and peptide group 15N and 13C' chemical shifts.

The effect of hydrogen/deuterium exchange on protein hydrogen bond coupling constants (h3)J(NC') has been investigated in the small globular protein ubiquitin. The couplings across deuterated or protonated hydrogen bonds were measured by a long-range quantitative HA(CACO)NCO experiment. The analysis is combined with a determination of the H(N)/D(N) isotope effect on the amide group (1)J(NC') couplings and the (15)N and (13)C' chemical shifts.

From structure and dynamics of protein L7/L12 to molecular switching in ribosome.

Based on the (1)H-(15)N NMR spectroscopy data, the three-dimensional structure and internal dynamic properties of ribosomal protein L7 from Escherichia coli were derived. The structure of L7 dimer in solution can be described as a set of three distinct domains, tumbling rather independently and linked via flexible hinge regions. The dimeric N-terminal domain (residues 1-32) consists of two antiparallel alpha-alpha-hairpins forming a symmetrical four-helical bundle, whereas the two identical C-terminal domains (residues 52-120) adopt a compact alpha/beta-fold.