Resonance Assignment/Abacus/Introduction to ABACUS: Difference between revisions

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Flowchart of resonance assignmnent by ABACUS''.&nbsp;''  
Flowchart of resonance assignment by ABACUS''.&nbsp;''  


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====  ====
==== &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; ====
 
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==== '''<span>Some features /advantages of the ABACUS protocol:</span>'''  ====
==== '''<span>Some features /advantages of the ABACUS protocol:</span>'''  ====


*<span><span>&nbsp;</span></span>It does not rely on sequential connectivities from less sensitive experiments such as HNCACB indispensable for most traditional sequential assignment procedures;  
*It does not rely on sequential connectivities from less sensitive experiments (ie.&nbsp;HNCACB)&nbsp;that&nbsp;are&nbsp;indispensable for most traditional sequential assignment procedures;  
*Inter-residue sequential connectivities are established mainly from NOE data, which saves time at a later stage in “troubleshooting” NOE and resonance assignments.;  
*Inter-residue sequential connectivities are established mainly from NOE data, which saves time&nbsp;while “troubleshooting” NOE and resonance assignments;  
*Probabilistic nature of the ABACUS procedure provides measure of reliability of assignments, and therefore one can obtain a partial, yet highly reliable assignment (even when the NMR data are sub-optimal) with the knowledge of where to focus manual intervention<font size="3">;</font>  
*Probabilistic nature of the ABACUS procedure provides a measure of reliability&nbsp;for the assignments, and therefore one can obtain a partial, yet highly reliable assignment (even when the NMR data are sub-optimal)&nbsp;because of&nbsp;knowing where to focus manual intervention<font size="3">;</font>  
*It can make use of&nbsp;partial spin-systems;  
*It can make use of&nbsp;partial spin-systems;  
*It can efficiently identify manual errors in the input peak lists;
*It can efficiently identify manual errors in the input peak lists;
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= NMR spectra required for ABACUS  =
= NMR spectra required for ABACUS  =
<div></div><div></div><div></div><div>The spectra typically needed for ABACUS approach are most conveniently separated into 3 groups: NH-rooted, the CH-rooted and the aromatic (also CH-rooted). &nbsp;Table 1 shows the optimal set of NMR spectra. This, of course, is neither an exclusive or exhaustive list. For example, a simultaneous CN-NOESY could be recorded instead of three different ones listed in the table. In case there are very few aromatic residues in a protein, to collect only one aromatic spectrum, namely aromatic NOESY, could be enough for assignment of aromatic resonances. </div><div>&nbsp;</div><div>'''Table 1.''' '''ABACUS optimal set of experiments''' </div><div>&nbsp;</div>  
<div></div><div></div><div></div><div>The spectra typically needed for the&nbsp;ABACUS approach are most conveniently separated into 3 groups: NH-rooted, the CH-rooted and the aromatic (also CH-rooted). &nbsp;Table 1 shows the optimal set of NMR spectra. This, of course, is neither an exclusive or exhaustive list. For example, a simultaneous CN-NOESY could be recorded instead of three different ones listed in the table.&nbsp;For proteins with very few aromatic residues,&nbsp;collecting only one aromatic spectrum (ie.&nbsp;aromatic NOESY) could be&nbsp;sufficient for the assignment of aromatic resonances. </div><div>&nbsp;</div><div>'''Table 1.''' '''ABACUS optimal set of experiments''' </div><div>&nbsp;</div>
{| cellspacing="0" cellpadding="0" border="0" class="FCK__ShowTableBorders"
{| class="FCK__ShowTableBorders" cellspacing="0" cellpadding="0" border="0"
|-
|-
| width="197" valign="top" | <div>'''NH-rooted'''</div>  
| valign="top" width="197" | <div>'''NH-rooted'''</div>
| width="197" valign="top" | <div>'''CH-rooted'''</div>  
| valign="top" width="197" | <div>'''CH-rooted'''</div>
| width="197" valign="top" | <div>'''Aromatic'''</div>
| valign="top" width="197" | <div>'''Aromatic'''</div>
|-
|-
| width="197" valign="top" | <div><sup>15</sup>N-HSQC</div>  
| valign="top" width="197" | <div><sup>15</sup>N-HSQC</div>
| width="197" valign="top" | <div><sup>13</sup>C-CT-HSQC</div>  
| valign="top" width="197" | <div><sup>13</sup>C-CT-HSQC</div>
| width="197" valign="top" | <div><sup>13</sup>C-HSQC-aro</div>
| valign="top" width="197" | <div><sup>13</sup>C-HSQC-aro</div>
|-
|-
| width="197" valign="top" | <div>HNCO</div>  
| valign="top" width="197" | <div>HNCO</div>
| width="197" valign="top" | <div><sup>13</sup>C-HSQC</div>  
| valign="top" width="197" | <div><sup>13</sup>C-HSQC</div>
| width="197" valign="top" | <div>H(C)CH-TOCSY-aro</div>
| valign="top" width="197" | <div>H(C)CH-TOCSY-aro</div>
|-
|-
| width="197" valign="top" | <div>HNCA</div>  
| valign="top" width="197" | <div>HNCA</div>
| width="197" valign="top" | <div>H(C)CH-TOCSY</div>  
| valign="top" width="197" | <div>H(C)CH-TOCSY</div>
| width="197" valign="top" | <div>(H)CCH-TOCSY-aro</div>
| valign="top" width="197" | <div>(H)CCH-TOCSY-aro</div>
|-
|-
| width="197" valign="top" | <div>CBCA(CO)NH</div>  
| valign="top" width="197" | <div>CBCA(CO)NH</div>
| width="197" valign="top" | <div>(H)CCH-TOCSY</div>  
| valign="top" width="197" | <div>(H)CCH-TOCSY</div>
| width="197" valign="top" | <div><sup>13</sup>C-NOESY-HSQC-aro</div>
| valign="top" width="197" | <div><sup>13</sup>C-NOESY-HSQC-aro</div>
|-
|-
| width="197" valign="top" | <div>HBHA(CO)NH</div>  
| valign="top" width="197" | <div>HBHA(CO)NH</div>
| width="197" valign="top" | <div><sup>13</sup>C-NOESY-HSQC</div>  
| valign="top" width="197" | <div><sup>13</sup>C-NOESY-HSQC</div>
| width="197" valign="top" | <div>&nbsp;</div>
| valign="top" width="197" | <div>&nbsp;</div>
|-
|-
| width="197" valign="top" | <div><sup>15</sup>N-NOESY-HSQC</div>  
| valign="top" width="197" | <div><sup>15</sup>N-NOESY-HSQC</div>
| width="197" valign="top" | <div>&nbsp;</div>  
| valign="top" width="197" | <div>&nbsp;</div>
| width="197" valign="top" | <div>&nbsp;</div>
| valign="top" width="197" | <div>&nbsp;</div>
|-
|-
| width="590" valign="top" colspan="3" | <div>''CCCONH-TOCSY (optional)''</div>
| valign="top" width="590" colspan="3" | <div>''CCCONH-TOCSY (optional)''</div>
|-
|-
| width="590" valign="top" colspan="3" | <div>''H(CCCO)NH-TOCSY (optional)''</div>
| valign="top" width="590" colspan="3" | <div>''H(CCCO)NH-TOCSY (optional)''</div>
|}
|}
<div>&nbsp;</div><div>&nbsp;</div><div>'''<font size="5"></font>'''</div>  
<div>&nbsp;</div><div>&nbsp;</div><div>'''<font size="5"></font>'''</div>
 
= Spin-system identification strategy  =
= Spin-system identification strategy  =
<div></div><div></div><div></div><div>The resonance assignment procedure starts from grouping resonances in spin systems. Two kind of spin-system will be considered in this manual.</div><div></div>  
<div></div><div></div><div></div><div>The resonance assignment procedure starts by grouping resonances into spin systems. Two&nbsp;types of spin-systems will be&nbsp;described in this manual.</div><div></div>
==== PB fragment  ====
==== PB fragment  ====
<div></div><div>PB (Peptide Bond) fragment comprise correlated resonances from the side chain of residue''i'' and the NH resonances of residue ''i+1'' (see Figure 1.1B).</div><div>
<div></div><div>PB (Peptide Bond) fragments&nbsp;consist of&nbsp;correlated resonances from the side chain of residue ''i'' and the NH resonances of residue ''i+1'' (see Figure 1.1B).</div><div>
&nbsp;  
&nbsp;  


'''Figure 1.1B'''  
'''Figure 1.1B'''  


[[Image:PBfragment.jpg|thumb|right|440px]]Schematic description of two types of molecular fragments: traditional spin-system (AA-fragment)<span>
[[Image:PBfragment.jpg|thumb|right|440px]]Schematic description of two types of molecular fragments: traditional spin-system (AA-fragment)<span> include all the atoms belonging to the same residue; PB-fragment includes all the atoms from one residue except the backbone amide group, plus the amide group from the next residue in the protein</span>  
include all the atoms belonging to the same residue; PB-fragment
includes all the atoms from one residue except the backbone amide
group, plus the amide group from the next residue in the protein</span>  


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==== ''b''PB fragment  ====
==== ''b''PB fragment  ====
<div>Uncompleted HN-rooted PB spin-systems, which include resonances of<span>&nbsp;&nbsp; Cα, Hα, Cβ, and Hβ&nbsp;&nbsp; atoms of residue ''i'' </span>and the NH resonances of residue ''i+1''<span>, is called ''b''PB fragment.
<div>Uncompleted HN-rooted PB spin-systems, which include resonances of<span>&nbsp;&nbsp; Cα, Hα, Cβ, and Hβ&nbsp;&nbsp; atoms of residue ''i'' </span>and the NH resonances of residue ''i+1''<span>,&nbsp;are called ''b''PB fragments. </span></div><div>&nbsp;</div><div>Spin-system identification in the ABACUS approach consists of 3 main steps.</div><div>&nbsp;</div><div>&nbsp;&nbsp;&nbsp;&nbsp; 1.&nbsp;During the first step, ''b''PB fragments are collected from high sensitivity NMR correlation experiments (such as HNCO, CBCA(CO)NH, and HBHA(CO)NH ) that transfer magnetization via the intervening peptide bond (see Figure 4.1A). </div><div>&nbsp;</div><div>&nbsp;&nbsp;&nbsp;&nbsp; 2. During the second step, completion of ''b''PB fragments with side-chain aliphatic resonances&nbsp;and identification of additional spin-systems (lacking HN resonances)&nbsp;are performed using HCCH-TOCSY and 13C-NOESY spectra (see Figure 4.1B).</div><div>&nbsp;</div><div>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 3. During the final step, spin-system validation and correction&nbsp;are performed. This step allows the user to find mistakes made during spectra peak-picking and to correct the mistakes by&nbsp;referring back to the spectra. </div><div>&nbsp;</div>
</span></div><div>&nbsp;</div><div>Spin-system identification in ABACUS approach consists of 3 main steps.</div><div>&nbsp;</div><div>&nbsp;&nbsp;&nbsp;&nbsp; 1. On the first step, ''b''PB fragments are collected from high sensitivity NMR correlation experiments (such as HNCO, CBCA(CO)NH, and HBHA(CO)NH) that transfer magnetization via the intervening peptide bond (see Figure 4.1A). </div><div>&nbsp;</div><div>&nbsp;&nbsp;&nbsp;&nbsp; 2. On the second step, completion of ''b''PB fragments with side-chain aliphatic resonances as well as identification of additional spin-systems (lacking HN resonances) is performed using HCCH-TOCSY and 13C-NOESY spectra (see Figure 4.1B) &nbsp;</div><div>&nbsp;</div><div>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; 3. Finally, spin-system validation and correction is performed. This step allows one to find mistakes made during spectra peak-picking and to correct the mistakes by going back to the spectra. </div><div>&nbsp;</div>  
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==== '''Figure 1.2<br>''' ====
<div><span>[[Image:Fmcgui Fig1.2.jpg|thumb|center|600px]]&nbsp;&nbsp;&nbsp;&nbsp;</span></div><div><div>During the validation step, twenty&nbsp;S(T) scores were calculated&nbsp;for each spin-system&nbsp;(see Figure 1.2 ). &nbsp;Here ''T'' corresponds to amino acid type, and ''T ''= A, R, D, …, and V, respectively. &nbsp;The score evaluates goodness-of-fit for the spin-system resonances in comparison&nbsp;to observed data&nbsp;obtained&nbsp;from the BMRB database.&nbsp; When&nbsp;the best&nbsp;S(T) score is low &nbsp;(ie.&nbsp;S<sub>max </sub>&lt; 10<sup>-4</sup>, where <span>S<sub>max&nbsp;</sub></span> = max{ S(T)}), it means&nbsp;that either the spin-system has very unusual chemical shifts or the spin-system does not make sense and needs to be&nbsp;<span>corrected. </span></div><div>&nbsp;</div></div><div><br></div><div>'''<font size="5"></font>'''</div>


==== '''Figure 1.2<br>'''  ====
<div><span>[[Image:Fmcgui Fig1.2.jpg|thumb|center|600px]]&nbsp;&nbsp;&nbsp;&nbsp;</span></div> <div><div>For each spin-system, 20 scores S(T) were calculated during the validation (see Figure 1.2). Here ''T'' corresponds to amino acid type, and ''T''=A,R,D,…, and V, respectively. The score evaluate goodness-of-fit of the spin-system resonances to those observed in BMRB data base. Too low value of the best score S<sub>max</sub>, where <span>S<sub>max&nbsp;</sub></span> = max{ S(T)} ,&nbsp; means that either the spin-system has very unusual chemical shifts or the spin-system does not make sense and need to be&nbsp;<span>
corrected. </span></div><div>&nbsp;</div></div><div><br></div><div>'''<font size="5"></font>'''</div>
= Fragment assignment by FMC procedure  =
= Fragment assignment by FMC procedure  =
<div></div><div></div><div></div><div></div><div>Sequence-specific assignment of PB-fragments is achieved using a Fragment Monte Carlo (FMC) stochastic search procedure. The scoring function used in the FMC procedure is based on both fragment amino acid typing (matching the spin system to amino acid types) and fragment contact map (reflecting which residue is next to which) derived from HNCA data and the analysis of NOEs interpreted by BACUS (see Figure 1.3)</div><div>&nbsp;</div>  
<div></div><div></div><div></div><div></div><div>Sequence-specific assignment of PB-fragments is achieved using a Fragment Monte Carlo (FMC) stochastic search procedure. The scoring function used in the FMC procedure is based on both fragment amino acid typing (matching the spin system to amino acid types) and fragment contact map (identifying neighbouring residues) derived from HNCA data and the analysis of NOEs interpreted by BACUS (see Figure 1.3)</div><div>&nbsp;</div>
==== Figure 1.3  ====
==== Figure 1.3  ====
<div>[[Image:Fmcgui Fig1.3.jpg|thumb|center|600px]]</div><div></div><div></div><div>&nbsp;FMC procedure performs ''<u>probabilistic assignment</u>'' of PB-fragments. The assignment probabilities <span>P<sub>s</sub><sup>k</sup></span><span> are calculated by Simulated Annealing (SA) or Replica Exchange Method (REM) Monte Carlo (MC) simulations. &nbsp;Here, P<sub>s</sub><sup>k</sup> is a </span>probability of fragment ''k'' to occupy position ''s;'<span style="display: none;" id="1259188877701S">&nbsp;</span>k = 1,….,N<sub>f.&nbsp;;</sub>''</div>  
<div>[[Image:Fmcgui Fig1.3.jpg|thumb|center|600px]]</div><div></div><div></div><div>&nbsp;FMC procedure performs ''<u>probabilistic assignment</u>'' of PB-fragments. The assignment probabilities <span>P<sub>s</sub><sup>k</sup></span><span> are calculated by Simulated Annealing (SA) or Replica Exchange Method (REM) Monte Carlo (MC) simulations. &nbsp;Here, P<sub>s</sub><sup>k</sup> is a </span>probability of fragment ''k'' to occupy position ''s;'<span id="1259188877701S" style="display: none">&nbsp;</span>k = 1,….,N<sub>f.&nbsp;;</sub>''</div>
==== Figure 1.4<br> ====
==== Figure 1.4<br> ====
 
[[Image:Fmcgui Fig1.4.jpg|thumb|left|600px]]
 
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[[Image:Fmcgui Fig1.4.jpg|thumb|center|600px]]&nbsp;


= &nbsp;FMC Graphical User Interface  =
= FMC Graphical User Interface  =
<div>FMCGUI is a graphical interface that assist user to carry out resonance assignment and structure calculation using ABACUS approach. FMCGUI integrate a number of FORTRAN applications: performs control of the data-flow between the applications, execute the applications, and helps to analyze effectively obtained results by visualizing data. <br></div><div>The main purpose of FMCGUI is to provide interactive tool for resonance assignment.</div><div>Structural part of FMCGUI can be used&nbsp; independently from the resonance assignment part. It helps to set up both structure calculations with CAYNA and water refinement calculations with CNS and to analyse results. The actual structure calculations are supposed to be carried out outside FMCGUI on linux cluster. </div>
<div>FMCGUI is a graphical interface that&nbsp;allows the&nbsp;user to carry out resonance assignment and structure calculation using the ABACUS approach.&nbsp; FMCGUI integrates a number of FORTRAN applications: controlling&nbsp;the data-flow between the applications, executing&nbsp;applications, and visualizing&nbsp;data for effective analysis of results. <br></div><div></div><div>The main purpose of FMCGUI is to provide an interactive tool for resonance assignment.&nbsp;&nbsp;FMCGUI includes a&nbsp;structure calculation&nbsp;component, which can be used&nbsp;independently from the resonance assignment component.&nbsp;&nbsp;The structure calculation component&nbsp;assists the user&nbsp;by&nbsp;setting up&nbsp;structure calculations with CYANA,&nbsp;water refinement calculations with CNS, and performs an&nbsp;analysis of&nbsp;their results.&nbsp;&nbsp;The&nbsp;structure calculations are to be&nbsp;run externally from&nbsp;FMCGUI, on a&nbsp;linux cluster. </div>

Latest revision as of 21:39, 6 January 2010

ABACUS approach.

ABACUS (Applied BACUS) is a novel approach for protein structure determination that has been applied successfully for more than 20 NESG targets. ABACUS is characterized by use of BACUS, a procedure for automated probabilistic interpretation of NOESY spectra in terms of unassigned proton chemical shifts based on the known information about the "connectivity" between proton resonances. BACUS is used in both the resonance assignment and structure calculation steps. The resonance assignment strategy of ABACUS is what distinguishes it the most from conventional NMR structure determination approaches (see Fig.1.1A).

Figure 1.1A

Abacus.JPG








                               

Flowchart of resonance assignment by ABACUS






                                                   

      

 

Some features /advantages of the ABACUS protocol:

  • It does not rely on sequential connectivities from less sensitive experiments (ie. HNCACB) that are indispensable for most traditional sequential assignment procedures;
  • Inter-residue sequential connectivities are established mainly from NOE data, which saves time while “troubleshooting” NOE and resonance assignments;
  • Probabilistic nature of the ABACUS procedure provides a measure of reliability for the assignments, and therefore one can obtain a partial, yet highly reliable assignment (even when the NMR data are sub-optimal) because of knowing where to focus manual intervention;
  • It can make use of partial spin-systems;
  • It can efficiently identify manual errors in the input peak lists;


 

NMR spectra required for ABACUS

The spectra typically needed for the ABACUS approach are most conveniently separated into 3 groups: NH-rooted, the CH-rooted and the aromatic (also CH-rooted).  Table 1 shows the optimal set of NMR spectra. This, of course, is neither an exclusive or exhaustive list. For example, a simultaneous CN-NOESY could be recorded instead of three different ones listed in the table. For proteins with very few aromatic residues, collecting only one aromatic spectrum (ie. aromatic NOESY) could be sufficient for the assignment of aromatic resonances.
 
Table 1. ABACUS optimal set of experiments
 
NH-rooted
CH-rooted
Aromatic
15N-HSQC
13C-CT-HSQC
13C-HSQC-aro
HNCO
13C-HSQC
H(C)CH-TOCSY-aro
HNCA
H(C)CH-TOCSY
(H)CCH-TOCSY-aro
CBCA(CO)NH
(H)CCH-TOCSY
13C-NOESY-HSQC-aro
HBHA(CO)NH
13C-NOESY-HSQC
 
15N-NOESY-HSQC
 
 
CCCONH-TOCSY (optional)
H(CCCO)NH-TOCSY (optional)
 
 

Spin-system identification strategy

The resonance assignment procedure starts by grouping resonances into spin systems. Two types of spin-systems will be described in this manual.

PB fragment

PB (Peptide Bond) fragments consist of correlated resonances from the side chain of residue i and the NH resonances of residue i+1 (see Figure 1.1B).

 

Figure 1.1B

PBfragment.jpg
Schematic description of two types of molecular fragments: traditional spin-system (AA-fragment) include all the atoms belonging to the same residue; PB-fragment includes all the atoms from one residue except the backbone amide group, plus the amide group from the next residue in the protein












 

 

 

bPB fragment

Uncompleted HN-rooted PB spin-systems, which include resonances of   Cα, Hα, Cβ, and Hβ   atoms of residue i and the NH resonances of residue i+1, are called bPB fragments.
 
Spin-system identification in the ABACUS approach consists of 3 main steps.
 
     1. During the first step, bPB fragments are collected from high sensitivity NMR correlation experiments (such as HNCO, CBCA(CO)NH, and HBHA(CO)NH ) that transfer magnetization via the intervening peptide bond (see Figure 4.1A).
 
     2. During the second step, completion of bPB fragments with side-chain aliphatic resonances and identification of additional spin-systems (lacking HN resonances) are performed using HCCH-TOCSY and 13C-NOESY spectra (see Figure 4.1B).
 
      3. During the final step, spin-system validation and correction are performed. This step allows the user to find mistakes made during spectra peak-picking and to correct the mistakes by referring back to the spectra.
 


Figure 1.2

Fmcgui Fig1.2.jpg
    
During the validation step, twenty S(T) scores were calculated for each spin-system (see Figure 1.2 ).  Here T corresponds to amino acid type, and T = A, R, D, …, and V, respectively.  The score evaluates goodness-of-fit for the spin-system resonances in comparison to observed data obtained from the BMRB database.  When the best S(T) score is low  (ie. Smax < 10-4, where Smax  = max{ S(T)}), it means that either the spin-system has very unusual chemical shifts or the spin-system does not make sense and needs to be corrected.
 

Fragment assignment by FMC procedure

Sequence-specific assignment of PB-fragments is achieved using a Fragment Monte Carlo (FMC) stochastic search procedure. The scoring function used in the FMC procedure is based on both fragment amino acid typing (matching the spin system to amino acid types) and fragment contact map (identifying neighbouring residues) derived from HNCA data and the analysis of NOEs interpreted by BACUS (see Figure 1.3)
 

Figure 1.3

Fmcgui Fig1.3.jpg
 FMC procedure performs probabilistic assignment of PB-fragments. The assignment probabilities Psk are calculated by Simulated Annealing (SA) or Replica Exchange Method (REM) Monte Carlo (MC) simulations.  Here, Psk is a probability of fragment k to occupy position s;'k = 1,….,Nf. ;

Figure 1.4

Fmcgui Fig1.4.jpg

 

FMC Graphical User Interface

FMCGUI is a graphical interface that allows the user to carry out resonance assignment and structure calculation using the ABACUS approach.  FMCGUI integrates a number of FORTRAN applications: controlling the data-flow between the applications, executing applications, and visualizing data for effective analysis of results.
The main purpose of FMCGUI is to provide an interactive tool for resonance assignment.  FMCGUI includes a structure calculation component, which can be used independently from the resonance assignment component.  The structure calculation component assists the user by setting up structure calculations with CYANA, water refinement calculations with CNS, and performs an analysis of their results.  The structure calculations are to be run externally from FMCGUI, on a linux cluster.