The Tools We Use For Our Research
ASDP is an automated NMR NOE assignment engine. It uses a distinct bottom-up topology-constrained approach for iterative NOE interpretation and generates 3D structures of the protein that is as close to the true structure as possible.
Primer Prim’er designs PCR primer sets for endonuclease and viral recombinase based cloning strategies.
pXs (probability of crystal structure) calculator
pXs calculates the probability of a given protein sequence to yield
a X-Ray structure.
PSVS is used for assessment of protein structures generated from
NMR, X-ray crystallographic and homology modeling methods.
RPF (Recall, Precision, and F-measure scores)
Structure quality assessment measurements based on information retrieval statistics. We describe the RPF web server, a quality assessment tool for protein NMR structures. The RPF server measures the ‘goodness-of-fit’ of the 3D structure with NMR chemical shift and unassigned NOESY data, and calculates a discrimination power (DP) score, which estimates the differences between the fits of the query structures and random coil structures to these experimental data. The DP-score is an accuracy predictor of the query structure. The RPF server also maps local structure quality measures onto the 3D structure using an online molecular viewer, and onto the NMR spectra, allowing refinement of the structure and/or NOESY peak list data.
Dismeta polls a number of disorder predictors and reports the results of each. Consensus disorder is plotted per residue.
The NESG wiki shares experimental protocols as well as training and educational materials in the fields of structural biology, structural genomics and biomolecular NMR.
AutoAssign is an artificial intelligence package for automating the analysis of backbone resonance assignments using triple-resonance NMR spectra of proteins[1,2,3,4]. Specifically, AutoAssign is a constraint-based expert system implemented in C++, Java2, and Perl programming languages and supported on SGI-IRIX, Sun-Solaris, MAC-OSX, x86-Linux, and x86_64-Linux architectures. The new AutoAssign distribution automates the assignments of HN, NH, CO, CA, CB, HA, and HB resonances in non-, partially-, and fully-deuterated samples. The rich graphical user interface (GUI) provides a many sets of tools for dataset conversions, assignment validations, and various graphical displays of assignment results. AutoAssign is well tested on a large number of independently-collected triple-resonance NMR data sets of proteins ranging in size from ~6 to ~32 kD, including one fully-deuterated protein and and a dataset with reduced-dimensionality experiments. AutoAssign performs the automated analysis of assignments in only seconds on current RISC and x86 platforms.
Structure Superposition with FindCore and PDBstat
A structure superimposition server using ordered residues or core residues,
based on PdbStat and FindCore respectively.
AVS- Chemical Shift Assignment Validation Server
AVS is used to validate chemical shift data, flagging shifts that are outside
the range typically observed in proteins.
NESG Homology Model Database Search
Search the NESG homology model database for your protein sequence.
Homology modeling server that generates models by satisfying sets
of spatial restraints dervided from the provided template.
NMR 2.0 provides a collection of collaborative and instructive tools
to advance NMR studies.
NESG structure deposition and data archival tools
NESG Residual Dipolar Coupling (RDC) Public Database
A publicly-accessible searchable database of > 150 RDC data sets and alignment conditions obtained for NESG target proteins.
Northeast Structural Genomics (NESG)
The Northeast Structural Genomics (NESG) consortium is one of the four large scale NIH funded structural genomics centers of the Protein Structure Initiative (PSI:Biology)
The NESG employs both X-Ray Crystallography and NMR Spectroscopy to determine the three-dimensional structures of novel proteins. NESG protein structures provide novel structural information useful in modeling thousands protein domains.
Click here to learn more