BioNMR
NMR aggregator & online community since 2003
BioNMR    
Learn or help to learn NMR - get free NMR books!
 

Go Back   BioNMR > NMR community > News from NMR blogs
Advanced Search
Home Forums Wiki NMR feeds Downloads Register Today's Posts



Jobs Groups Conferences Literature Pulse sequences Software forums Programs Sample preps Web resources BioNMR issues


Webservers
NMR processing:
MDD
NMR assignment:
Backbone:
Autoassign
MARS
UNIO Match
PINE
Side-chains:
UNIO ATNOS-Ascan
NOEs:
UNIO ATNOS-Candid
UNIO Candid
ASDP
Structure from NMR restraints:
Ab initio:
GeNMR
Cyana
XPLOR-NIH
ASDP
UNIO ATNOS-Candid
UNIO Candid
Fragment-based:
BMRB CS-Rosetta
Rosetta-NMR (Robetta)
Template-based:
GeNMR
I-TASSER
Refinement:
Amber
Structure from chemical shifts:
Fragment-based:
WeNMR CS-Rosetta
BMRB CS-Rosetta
Homology-based:
CS23D
Simshift
Torsion angles from chemical shifts:
Preditor
TALOS
Promega- Proline
Secondary structure from chemical shifts:
CSI (via RCI server)
TALOS
MICS caps, β-turns
d2D
PECAN
Flexibility from chemical shifts:
RCI
Interactions from chemical shifts:
HADDOCK
Chemical shifts re-referencing:
Shiftcor
UNIO Shiftinspector
LACS
CheckShift
RefDB
NMR model quality:
NOEs, other restraints:
PROSESS
PSVS
RPF scores
iCing
Chemical shifts:
PROSESS
CheShift2
Vasco
iCing
RDCs:
DC
Anisofit
Pseudocontact shifts:
Anisofit
Protein geomtery:
Resolution-by-Proxy
PROSESS
What-If
iCing
PSVS
MolProbity
SAVES2 or SAVES4
Vadar
Prosa
ProQ
MetaMQAPII
PSQS
Eval123D
STAN
Ramachandran Plot
Rampage
ERRAT
Verify_3D
Harmony
Quality Control Check
NMR spectrum prediction:
FANDAS
MestReS
V-NMR
Flexibility from structure:
Backbone S2
Methyl S2
B-factor
Molecular dynamics:
Gromacs
Amber
Antechamber
Chemical shifts prediction:
From structure:
Shiftx2
Sparta+
Camshift
CH3shift- Methyl
ArShift- Aromatic
ShiftS
Proshift
PPM
CheShift-2- Cα
From sequence:
Shifty
Camcoil
Poulsen_rc_CS
Disordered proteins:
MAXOCC
Format conversion & validation:
CCPN
From NMR-STAR 3.1
Validate NMR-STAR 3.1
NMR sample preparation:
Protein disorder:
DisMeta
Protein solubility:
camLILA
ccSOL
Camfold
camGroEL
Zyggregator
Isotope labeling:
UPLABEL
Solid-state NMR:
sedNMR


Reply
 
Thread Tools Search this Thread Rate Thread Display Modes
  #1  
Old 02-05-2011, 07:23 PM
nmrlearner's Avatar
Senior Member
 
Join Date: Jan 2005
Posts: 23,777
Points: 193,617, Level: 100
Points: 193,617, Level: 100 Points: 193,617, Level: 100 Points: 193,617, Level: 100
Level up: 0%, 0 Points needed
Level up: 0% Level up: 0% Level up: 0%
Activity: 50.7%
Activity: 50.7% Activity: 50.7% Activity: 50.7%
Last Achievements
Award-Showcase
NMR Credits: 0
NMR Points: 193,617
Downloads: 0
Uploads: 0
Default Bell Bell

Bell Bell

Our friends working in the field of biopolymers can study a single molecules for months and can afford to spend a lot of time with their NMR spectra, if the time invested translates into higher accuracy of their results.
Software makers are more interested in creating automatic tools that work without human intervention, day and night, because of the higher appeal of any push-button solution. Is anybody helping our friends? Yes! One month ago a simple and effective tool appeared for measuring the volume of a 2-D cross peak, courtesy of iNMR. Let's see, with a practical example, what it does and how it works.

We start from the normal contour map. Here you click on a single peak and optionally enter two labels to assign it. In the picture we have selected the peak at the bottom right. Many things automatically happen, if you like: the program can locate the maximum of the peak and fit the overall shape with a gaussian bell. Why a Gaussian instead of a Lorentzian? As you know, 2-D spectra are premultiplied with cosine bells before the FT, and the purpose of this weight is just to transform the shape. The tails of the gaussian are much shorter, so we avoid the lorentzian as far as possible. The additional problem, in this particular case and in many other cases, is the presence of unresolved J-couplings. When they are resolved, you can fit the peak with a combination (sum) of bells. In our case, we could try to fit the peak with a doublet, but for simplicity we'll approximate it to a singlet.
My pictures do not show the moving cross-sections around the border of the contour plot. The cross-sections, that exist into the program, give a graphic idea of the goodness of the fit. Up to now, cross-sections included, there is nothing new. Everything has been copied from more ancient programs (read: Sparky). But now, a single click brings us into the Manual Fitting module, which is the novelty.

We have two orthogonal cross-sections: the yz section at the top and the xz section at the bottom. The experimental spectrum is black, the model (gaussian curve) is red. We can change the 5 parameters that describe the model. The simpler way to change them is by dragging the little square handles. Alternatively, we have the numerical fields or the little arrows. When you change the x frequency in the lower panel, the programs show a different vertical cross-section in the upper panel, corresponding to the new x. When you change the y frequency in the upper panel, a different horizontal section is selected.
The final picture shows my best result, that is the way I would measure the volume of this particular peak. Higher accuracy can likely be obtained with a model comprising two gaussians (something you can also do with this module), yet the present result is accurate enough for many practical applications.

All the values are automatically stored into a bigger module called "Cross Peaks Manager" (CPM in the following; actually you need to create a CPM before starting any volume-fitting operation). The CPM stores things of different kinds: chemical shifts, assignments, integrated volumes, fitted volumes, etc. A real-life problem where a CPM can be precious is the measure of relaxation times of very large molecules, like proteins. These molecules are so large that very few signals are resolved in the 1-D proton spectrum, while the sensitivity of other nuclei is not enough. You collect a series of HSQC spectra, a 2-D experiment that resolves all the signals (or almost all of them). A single CPM can manage the whole series of experiment. When you have processed all of them, you can ask the CPM to create a table with the integrals. The table combines volumes measured by integration and volumes measured by fitting (manual or automatic). You are not confined to a single solution. You are free to integrate each single peak with the most appropriate technique for it. If this is not enough, you have the time-saving option of simultaneous automatic integration.


Source: NMR Software blog
Reply With Quote


Did you find this post helpful? Yes | No

Reply
Similar Threads
Thread Thread Starter Forum Replies Last Post
[NMR900 blog] Russell Bell Symposium, McMaster
Russell Bell Symposium, McMaster McMaster University, November 18, 2010 Russell Bell, Professor Emeritus of Chemistry and Chemical Biology at McMaster, has made significant scientific contributions in the area of NMR, chemical biology using DNA and proteins, organic synthesis and in environmental remediation. In addition, he is renowned at McMaster University for excellence in teaching, particularly of first year chemistry. The department is pleased to recognize his contributions with this special symposium. Hamilton Hall, HH-305 9:30-­9:35 Mike Brook, McMaster University:...
nmrlearner News from NMR blogs 0 11-13-2010 05:00 AM



Posting Rules
You may not post new threads
You may not post replies
You may not post attachments
You may not edit your posts

BB code is On
Smilies are On
[IMG] code is On
HTML code is Off
Trackbacks are Off
Pingbacks are Off
Refbacks are Off



BioNMR advertisements to pay for website hosting and domain registration. Nobody does it for us.



Powered by vBulletin® Version 3.7.3
Copyright ©2000 - 2024, Jelsoft Enterprises Ltd.
Copyright, BioNMR.com, 2003-2013
Search Engine Friendly URLs by vBSEO 3.6.0

All times are GMT. The time now is 09:43 AM.


Map