11 research outputs found
The NMR restraints grid at BMRB for 5,266 protein and nucleic acid PDB entries
Several pilot experiments have indicated that improvements in older NMR structures can be expected by applying modern software and new protocols (Nabuurs et al. in Proteins 55:483â186, 2004; Nederveen et al. in Proteins 59:662â672, 2005; Saccenti and Rosato in J Biomol NMR 40:251â261, 2008). A recent large scale X-ray study also has shown that modern software can significantly improve the quality of X-ray structures that were deposited more than a few years ago (Joosten et al. in J. Appl Crystallogr 42:376â384, 2009; Sanderson in Nature 459:1038â1039, 2009). Recalculation of three-dimensional coordinates requires that the original experimental data are available and complete, and are semantically and syntactically correct, or are at least correct enough to be reconstructed. For multiple reasons, including a lack of standards, the heterogeneity of the experimental data and the many NMR experiment types, it has not been practical to parse a large proportion of the originally deposited NMR experimental data files related to protein NMR structures. This has made impractical the automatic recalculation, and thus improvement, of the three dimensional coordinates of these structures. We here describe a large-scale international collaborative effort to make all deposited experimental NMR data semantically and syntactically homogeneous, and thus useful for further research. A total of 4,014 out of 5,266 entries were âcleanedâ in this process. For 1,387 entries, human intervention was needed. Continuous efforts in automating the parsing of both old, and newly deposited files is steadily decreasing this fraction. The cleaned data files are available from the NMR restraints grid at http://restraintsgrid.bmrb.wisc.edu
An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge
There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance.
RESULTS:
A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization.
CONCLUSIONS:
The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups
Spin System Modeling of Nuclear Magnetic Resonance Spectra for Applications in Metabolomics and Small Molecule Screening
The
exceptionally rich information content of nuclear magnetic
resonance (NMR) spectra is routinely used to identify and characterize
molecules and molecular interactions in a wide range of applications,
including clinical biomarker discovery, drug discovery, environmental
chemistry, and metabolomics. The set of peak positions and intensities
from a reference NMR spectrum generally serves as the identifying
signature for a compound. Reference spectra normally are collected
under specific conditions of pH, temperature, and magnetic field strength,
because changes in conditions can distort the identifying signatures
of compounds. A spin system matrix that parametrizes chemical shifts
and coupling constants among spins provides a much richer feature
set for a compound than a spectral signature based on peak positions
and intensities. Spin system matrices expand the applicability of
NMR spectral libraries beyond the specific conditions under which
data were collected. In addition to being able to simulate spectra
at any field strength, spin parameters can be adjusted to systematically
explore alterations in chemical shift patterns due to variations in
other experimental conditions, such as compound concentration, pH,
or temperature. We present methodology and software for efficient
interactive optimization of spin parameters against experimental 1D-<sup>1</sup>H NMR spectra of small molecules. We have used the software
to generate spin system matrices for a set of key mammalian metabolites
and are also using the software to parametrize spectra of small molecules
used in NMR-based ligand screening. The software, along with optimized
spin system matrix data for a growing number of compounds, is available
from http://gissmo.nmrfam.wisc.edu/
NMR Exchange Format : a unified and open standard for representation of NMR restraints data
We
present
a
unified,
easily
adaptable,
open-Ââsource
NMR
exchange
format
(NEF)
for
NMR
restraints
and
associated
data.
Developers
of
the
major
software
packages
for
NMR
structure
determination
and
refinement
have
agreed
to
make
their
software
able
to
read
and
write
NEF-Ââcompliant
files.
Detailed
specifications
can
be
found
at
https://github.com/NMRExchangeFormat/NEF