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==News==
==News==
2013-01-17:
2020-05-21
*If you are having trouble with installation give [http://www.mtsslsuite.isb.ukbonn.de this] a try


We are just working on Version 1.1 of mtsslWizard. It will come out end of January 2013.
2017-01-17:
*[http://www-hagelueken.thch.uni-bonn.de/index.php/en/2014-08-04-13-28-34/mtssldock Version 2.0 available]!


Some new features:
2015-07-27:
* much faster
* new spin labels
* distances and histogram are directly copied to your clipboard
* improved interface


If you are interested in a test version, please contact hagelueken'at'pc.uni-bonn.de
*uploaded a new version (1.3) to repository. Includes some new spin labels and a distance map feature. Plots can be viewed with [[mtsslPlotter]].


==Program features==
2014-03-04:
An MTSSL spin label can be attached to any position of a protein just by pointing and clicking. The program can then search the conformational space of the label (5 chi angles) and determine which conformations of the label do not clash with the protein surface. In "distance mode", distances between MTSSL ensembles can be determined and exported.
For symmetric molecules, the MTSSL ensemble can be copied to symmetry related positions simply by pointing and clicking ("Copy & Move" mode).


Please reference:
* uploaded a new version (1.12) to repository. Fixes a bug that occurred on some machines. Thanks to C. Engelhard for noticing!


[http://www.springerlink.com/content/7148j5k2ppk475wu/ '''MtsslWizard: In Silico Spin-Labeling and Generation of Distance Distributions in PyMOL''', Gregor Hagelueken, Richard Ward, James H. Naismith and Olav Schiemann, DOI: 10.1007/s00723-012-0314-0]
2013-07-05:


==Screen shot==
* added two new labels: DOTA and K1 (pAcPhe based)
[[File:MtsslWizard_gui.jpg]]


==Usage==
2013-01-31:
===Installation===
Install the program by copying the code below into an empty text file (e.g. "mtsslWizard.py") located in the \Pymol\modules\pmg_tk\startup directory. After PyMOL has been started, the program can be launched from the WIZARDS menu. mtsslWizard has been tested with PyMOL 1.4.
===Labeling===
#Open a protein structure in PyMOL and remove any unwanted solvent molecules or ligands.
#Start the mtsslWizard via Wizards>mtsslWizard
#If needed, vary the search parameters like "Thoroughness", "Cutoff" and "Clashes allowed". Thoroughness determines how many conformations of MTSSL will be checked. The cutoff value determines the minimum allowed distance between label and protein before the conformation is sorted out as clashing. "Clashes allowed" should usually be set to zero. If this value is changed  to e.g. "5", a conformation can violate the "cutoff" parameter five times before the conformation is discarded.
#click "Go" to start the calculation. Depending on the size of the protein, the "Thoroughness" parameter and of course the speed of your computer the duration of the search can vary quite considerably. With the default settings it does usually not take longer than 10-15 seconds.
===Distance calculation===
#change "Mode" to "Distance"
#click the first and second ensemble
#The program will now calculate all possible distances between the conformations in the two ensembles. If both ensembles have many conformations, this can take quite a while!
===Reference===
If you find this program useful, please cite this paper:


Hagelueken G, Ward R, Naismith JH, Schiemann O (2012) MtsslWizard: In silico Spin-Labeling and Generation of Distance Distributions in PyMOL. Appl. Magn. Res. accepted for publication
Version 1.1 in script repository.


It also contains detailed informations about the program, examples and a discussion of limitations of the approach.
Some new features of v1.1:
* Much faster. The algorithm was optimized and the speed of the program is now almost independent off the size of the molecule. Due to this, 'thorough search' is now set as default and the 'copy and move' mode has been dropped.


===Contact===
* New spin labels. The program now contains MTSSL, PROXYL and two labels for nucleic acids. Additional spin labels can be added upon request.
hagelueken'at'pc.uni-bonn.de


==Source Code==
* Distances and histogram are directly copied to the clipboard or written out to a file as before. The result file contains 4 columns: 1-distances, 2-bins for histogram, 3-histogram frequencies, 4-histogram frequencies with highest value normalized to 1.0 for comparisons
<source lang="python">
"""
---mtsslWizard: spin_labeling plugin for PyMOL ---
Author  : Gregor Hagelueken
Date    : Jan 2012
Version : 1.0
Mail    : gh50'at'st-andrews.ac.uk


mtsslWizard is a plugin for the PyMOL Molecular Graphics System.
* Improved interface. Amongst other things, the clash control settings were simplified: There are now only two settings for vdW restraints: 'tight' and 'loose'. Also, only the average and c-Beta distances are displayed in the PyMOL viewer to avoid screen clutter (see screenshot).
The program is useful for in silico spin labeling of proteins with the spin label MTSSL in PyMOL. Also, distances between ensembles of two spin labels can be calculated and exported.
The program was tested with PyMOL versions 1.4.


Thanks to Jason Vertrees for help with the quick_dist function. Thanks to the author of the plane_wizard script for a nice example on how to program a PyMOL wizard.
The new version was thoroughly tested. If you encounter any bugs or problems, please use the contact address below.
Literature:
Hagelueken G, Ward R, Naismith JH, Schiemann O. MtsslWizard: In silico Spin-Labeling and Generation of Distance Distributions in PyMOL. 2012. Appl. Mag. Res., accepted for publication.
----------------------------------------------------------------------
----------------------------------------------------------------------
"""
import pymol
import numpy
import random, time, math
from pymol import cmd
from pymol.wizard import Wizard
from pymol import stored
from chempy import cpv
from pprint import pprint
from operator import itemgetter


Version 1.0 is still available [https://github.com/Pymol-Scripts/Pymol-script-repo/blob/5935bdad82a480a4e004c8c902ef69dc75389ac8/plugins/mtsslWizard.py here].


default_thoroughness = "normal search"
==Program features==
default_cutoff = 3.4
Spin labels can be attached to any position of a protein or nucleic acid just by pointing and clicking. The program then searches the conformational space of the label and determines which conformations of the label do not clash with the macromolecule. In "distance mode", distances between label ensembles can be determined and exported. In "distance map" mode, the program quickly estimates the inter-label distances between all possible spin pairs in a protein molecule. The result is saved as a color coded distance map. It is also possible to calculate difference distance maps between two conformations of a protein.
default_clashes = 0
default_mode = 'Search'
default_rotamers = 'Unrestricted'
default_clashguard = 'on'
internalClash_cutoff = 2.5


def getAtypes(): #for internal clashGuard
Please reference:  
    #        0  1  2  3    4    5    6    7    8    9    10  11  12  13  14  15  16    17
    return [ 'N','C','O','CA','CB','SD','SG','CE','O1','N1','C2','C3','C4','C5','C6','C7','C8', 'C9', ]


def makeKnownExceptions(): #for clashGuard
[http://www.springerlink.com/content/7148j5k2ppk475wu/ '''MtsslWizard: In Silico Spin-Labeling and Generation of Distance Distributions in PyMOL''', Gregor Hagelueken, Richard Ward, James H. Naismith and Olav Schiemann, DOI: 10.1007/s00723-012-0314-0]
    aTypes = getAtypes()
    knownExceptions=[]
    for x in range(len(aTypes)):
        knownExceptions.append({})
    for a in range(len(aTypes)):
        for b in range(len(aTypes)):
            knownExceptions[a][b] = 0
    #pairs of atoms in this list are treated as exceptions for the internal clash guard
    eList = [ [9,12], [0,1], [1,2], [1,3], [3,4], [4,6], [5,6], [5,7], [7,11], [8,9], [9,10], [9,13],
              [10,11], [10,16], [10,17], [0,3], [0,4],  [1,4],  [2,3],  [7,12],  [8,10],  [8,13], 
              [9,11],  [9,14],  [9,15],  [9,16],  [10,12],  [10,13],  [11,13], [11,12], [12,13], [12,14],
              [13,14], [13,15], [12,15], [9,17], ]
    for x in eList:
        a,b = x
        knownExceptions[a][b] = knownExceptions[b][a] = 1


    return knownExceptions
==Screen shot==
[[File:MtsslWizardv1-1.jpg]]


knownExceptions = makeKnownExceptions()
==Installation==
Install the program by copying the code from the link above into an empty text file (e.g. "mtsslWizard.py") located in the \Pymol\modules\pmg_tk\startup directory. After PyMOL has been started, the program can be launched from the WIZARDS menu.
Alternatively install the wizard via the plugins menu.


def __init__(self):
    self.menuBar.addmenuitem('Wizard', 'command',
                            'MtsslWizard',
                            label = 'MtsslWizard',
                            command = lambda s=self : open_wizard())
class MtsslWizard(Wizard):
    def __init__(self):
        Wizard.__init__(self)
        print "MtsslWizard by gha. Please remove any solvent or unwanted heteroatoms before using the wizard!"
       
        #create contents of wizard menu
        self.reset()
        self.menu['mode'] = [
                                      #[1, 'Stochastic','cmd.get_wizard().set_mode("Stochastic")'],
                                      [1, 'Search','cmd.get_wizard().set_mode("Search")'],
                                      [1, 'Measure','cmd.get_wizard().set_mode("Measure")'],
                                      [1, 'Copy & Move','cmd.get_wizard().set_mode("Copy & Move")']
                                      ]
        #self.menu['rotamers'] =[
        #                              [ 2, '\\955NOTE:\\559"Unrestricted" does not constrain the', ''],
        #                              [ 2, '\\559chi angles at all. "Restricted" restrains the', ''],
        #                              [ 2, '\\559chi angles to a rotamer library of MTSSL.', ''],
        #                              [1, 'Unrestricted','cmd.get_wizard().set_rotamers("Unrestricted")'],
        #                              [1, 'Restricted','cmd.get_wizard().set_rotamers("Restricted")']
        #                              ]
       
        self.menu['thoroughness'] = [
                                      [1, 'painstaking','cmd.get_wizard().set_thoroughness("painstaking")'],
                                      [1, 'thorough search','cmd.get_wizard().set_thoroughness("thorough search")'],
                                      [1, 'normal search','cmd.get_wizard().set_thoroughness("normal search")'],
                                      [1, 'quick search','cmd.get_wizard().set_thoroughness("quick search")']
                                      ]
        self.menu['clashes'] = [
                                      [ 2, '\\955NOTE:\\559This parameter should normally ', ''],
                                      [ 2, '\\559be set to "0"! Use it with care and only ', ''],
                                      [ 2, '\\559change it if conformational changes of ', ''],
                                      [ 2, '\\559the protein are expected!!!', ''],
                                      [1, '0 clashes','cmd.get_wizard().set_clashes(0)'],
                                      [1, '1 clashes','cmd.get_wizard().set_clashes(1)'],
                                      [1, '2 clashes','cmd.get_wizard().set_clashes(2)'],
                                      [1, '3 clashes','cmd.get_wizard().set_clashes(3)'],
                                      [1, '4 clashes','cmd.get_wizard().set_clashes(4)'],
                                      [1, '5 clashes','cmd.get_wizard().set_clashes(5)']
                                      ]
        self.menu['cutoff'] = [
                                      [ 2, '\\955NOTE:\\559This parameter determines ', ''],
                                      [ 2, '\\559the minimum allowed distance between', ''],
                                      [ 2, '\\559label and  protein atoms. Only change', ''],
                                      [ 2, '\\559this parameter if conformational ch-', ''],
                                      [ 2, '\\559anges at the labeling site are expected!', ''],
                                      [1, '2.6 A','cmd.get_wizard().set_cutoff(2.6)'],
                                      [1, '2.8 A','cmd.get_wizard().set_cutoff(2.8)'],
                                      [1, '3.0 A','cmd.get_wizard().set_cutoff(3.0)'],
                                      [1, '3.2 A','cmd.get_wizard().set_cutoff(3.2)'],
                                      [1, '3.4 A','cmd.get_wizard().set_cutoff(3.4)'],
                                      [1, '3.6 A','cmd.get_wizard().set_cutoff(3.6)'],
                                      [1, '3.8 A','cmd.get_wizard().set_cutoff(3.8)']
                                      ]
       
        self.menu['clashGuard'] = [
                                      [ 2, '\\955NOTE:\\559The clashGuard checks for', ''],
                                      [ 2, '\\559internal clashes of the label. ', ''],
                                      [ 2, '\\559This should usually be set to "on"!', ''],
                                      [1, 'on','cmd.get_wizard().set_clashGuard("on")'],
                                      [1, 'off','cmd.get_wizard().set_clashGuard("off")']
                                      ]
       
        self.menu['writeToFile'] = [
                                      [1, 'no','cmd.get_wizard().set_writeToFile("no")'],
                                      [1, 'yes','cmd.get_wizard().set_writeToFile("yes")']
                                      ]


    #some setter functions   
mtsslWizard has been tested with PyMOL 1.7. It does not work with PyMOL 1.3. Here are manuals on how to install it on [[MAC_Install | Mac]] or [[Windows_Install | Windows]].
    def set_rotamers(self,rotamers):
        self.rotamers = rotamers
        self.cmd.refresh_wizard()
   
    def set_thoroughness(self,thoroughness):
        self.thoroughness = thoroughness
        self.cmd.refresh_wizard()
       
    def set_writeToFile(self,writeToFile):
        self.writeToFile = writeToFile
        self.cmd.refresh_wizard()
   
    def set_clashGuard(self,clashGuard):
        self.clashGuard = clashGuard
        self.cmd.refresh_wizard()
       
    def set_cutoff(self,cutoff):
        self.cutoff = cutoff
        self.cmd.refresh_wizard()
       
    def set_clashes(self,clashes):
        self.clashes = clashes
        self.cmd.refresh_wizard()
   
    #reset wizard to defaults
    def reset(self):
        self.toggleStatesCaption='Toggle states: ON'
        self.start_time=time.time()
        self.conformationList=[]
        self.object_prefix = "mtsslWiz"
        self.pick_count = 0
        self.object_count = 0
        self.allowedAngle=[False,False,False,False,False]
        self.thoroughness = default_thoroughness
        self.cutoff = default_cutoff
        self.clashes = default_clashes
        self.rotamers = default_rotamers
        self.residue1_name = None
        self.residue2_name = None
        self.picked_object1 = None
        self.picked_object2 = None
        self.numberOfLabel = 0
        self.mode=default_mode
        self.writeToFile='no'
        self.clashGuard=default_clashguard
        self.selection_mode = cmd.get_setting_legacy("mouse_selection_mode")
        cmd.set("mouse_selection_mode",1) # set selection mode to residue
        cmd.deselect()
        cmd.unpick()
        cmd.delete(self.object_prefix + "*")
        cmd.delete("sele*")
        cmd.delete("_indicate*")
        cmd.delete("pk*")
        cmd.delete("*_tmp*")
        cmd.refresh_wizard()
    def delete_all(self):
        cmd.delete(self.object_prefix + "*")
       
    def set_mode(self, mode):
        self.mode = mode
        self.cmd.refresh_wizard()
    def cleanup(self):
        cmd.set("mouse_selection_mode",self.selection_mode) # restore selection mode
        self.reset()
        self.delete_all()
    def get_prompt(self):
        self.prompt = None
        if self.mode == 'Search' or 'Stochastic':
            self.prompt = [ 'Select a residue to label...']
        if self.pick_count == 0 and self.mode == 'Measure':
            self.prompt = [ 'Select first label...']
        if self.pick_count == 0 and self.mode == 'Copy & Move':
            self.prompt = [ 'Select label to be copied & moved ...']
        if self.pick_count == 1 and self.mode == 'Measure':
            self.prompt = [ 'Select second label...']
        if self.pick_count == 1 and self.mode == 'Copy & Move':
            self.prompt = [ 'Select position for copied label ...']
        return self.prompt
    def do_select(self, name):
        # "edit" only this atom, and not others with the object prefix
        try:
            #cmd.edit("%s and not %s*" % (name, self.object_prefix))
            self.do_pick(0)
        except pymol.CmdException, pmce:
            print pmce
    def do_pick(self, picked_bond):
        # this shouldn't actually happen if going through the "do_select"
        if picked_bond:
            self.error = "Error: please select bonds, not atoms"
            print self.error
            return
        if self.pick_count == 0:
            self.residue1_name = self.object_prefix + "_selectedResidue_" + str(self.pick_count)   
            # transfer the click selection to a named selection
            cmd.select(self.residue1_name+"_tmp", "(sele)")
            # delete the click selection
            # highlight stuff
            indicate_selection = "_indicate" + self.object_prefix + str(self.pick_count)
            cmd.select(indicate_selection, self.residue1_name)
            cmd.enable(indicate_selection)
            # find the name of the object which contains the selection
            new_name = None
            obj_list = cmd.get_names('objects')
            for object in obj_list:
                if cmd.get_type(object)=="object:molecule":
                    if cmd.count_atoms("(%s and (sele))"%(object)):
                        self.picked_object1 = object
                        print self.picked_object1
                        break
            src_frame = cmd.get_state()
            if self.picked_object1 == None:
                print " MtsslWizard: object not found."
            self.pick_count += 1
            if self.mode == 'Measure' or self.mode == 'Copy & Move':
                #deselect before next pick
                cmd.deselect()
            self.cmd.refresh_wizard()
           
        elif self.pick_count == 1  and (self.mode == 'Measure' or self.mode == 'Copy & Move'):
            self.residue2_name = self.object_prefix + "_selectedResidue_" + str(self.pick_count)
            print self.residue2_name
            # transfer the click selection to a named selection
            cmd.select(self.residue2_name+"_tmp", "(sele)")
            # highlight stuff
            indicate_selection = "_indicate" + self.object_prefix + str(self.pick_count)
            cmd.select(indicate_selection, self.residue2_name)
            cmd.enable(indicate_selection)
            # find the name of the object which contains the selection
            new_name = None
            obj_list = cmd.get_names('objects')
            for object in obj_list:
                if cmd.get_type(object)=="object:molecule":
                    if cmd.count_atoms("(%s and (sele))"%(object)):
                        self.picked_object2 = object
                        break
            src_frame = cmd.get_state()
            if self.picked_object2 == None:
                print " MtsslWizard: object not found."
            self.pick_count += 1
            #deselect before next pick
            self.run()
            cmd.deselect()
       
        if self.mode == 'Search' or self.mode == 'Stochastic':
            #print "increase numberOfLabel"
            self.numberOfLabel += 1
           


    def run(self):
Additional requirements:
        self.conformationList=[]
*SciPy has to be installed
        my_view= cmd.get_view()
*Pyperclip or xerox have to be installed for the clipboard support.
        if self.pick_count == 1 and self.mode == 'Search':
            print "\n\n\nNew run:\n"
            mtsslify(self, self.picked_object1, self.residue1_name, self.numberOfLabel, self.thoroughness, self.cutoff, self.clashes)
           
        if self.pick_count == 1 and self.mode == 'Stochastic':
            #testing selection...
            print "\n\n\nNew run:\n"
            stochasticMtsslify(self, self.picked_object1, self.residue1_name, self.numberOfLabel, self.thoroughness, self.cutoff, self.clashes)
           
        elif self.pick_count == 2 and self.mode == 'Measure':
            print "\n\n\nNew run:\n"
            quick_dist(self, self.picked_object1+" & name N1", self.picked_object2+" & name N1")
       
        elif self.pick_count == 2 and self.mode == 'Copy & Move':
            print "\n\n\nNew run:\n"
            copyAndMove(self.residue1_name, self.residue2_name, self.picked_object1, self.numberOfLabel)
               
        #some cleanup
        self.pick_count = 0
        cmd.delete("pk*")
        cmd.delete("sele*")
        cmd.delete("*_tmp*")
        cmd.delete("_indicate*")
        cmd.delete("labelEnvironment*")
        self.cmd.refresh_wizard()
        cmd.set_view(my_view)
       
   
    def delete_last(self):
        try:
            print self.numberOfLabel
            if self.numberOfLabel >= 1:
                cmd.delete("mtsslWiz_"+str(self.numberOfLabel)+"*")
                self.numberOfLabel-=1
        except pymol.CmdException, pmce:
            print pmce
   
    def toggle_states(self):
        if cmd.get("all_states")=='on':
            self.toggleStatesCaption='Toggle states: OFF'
            cmd.set("all_states",0)
        elif cmd.get("all_states")=='off':
            self.toggleStatesCaption='Toggle states: ON'
            cmd.set("all_states",1)
        self.cmd.refresh_wizard()
           
    def get_panel(self):
        if not ((self.mode == 'Measure') or (self.mode == 'Copy & Move')):
            return [
                    [ 1, 'Mtssl Wizard',''],
                    [ 3, 'Mode: %s'%self.mode,'mode'],
                    #[ 3, 'Rotamers: %s'%self.rotamers,'rotamers'],
                    [ 3, 'Thoroughness: %s'%self.thoroughness,'thoroughness'],
                    [ 3, 'Cutoff: %3.1f A'%self.cutoff,'cutoff'],
                    [ 3, 'Clashes allowed: %i'%self.clashes,'clashes'],
                    #[ 3, 'Clash guard: %s'%self.clashGuard,'clashGuard'],
                    [ 3, 'Angles to file?: %s'%self.writeToFile,'writeToFile'],
                    [ 2, 'Go!','cmd.get_wizard().run()'],
                    [ 2, self.toggleStatesCaption,'cmd.get_wizard().toggle_states()'],
                    [ 2, 'Delete last label','cmd.get_wizard().delete_last()'],
                    [ 2, 'Reset','cmd.get_wizard().reset()'],
                    [ 2, 'Done','cmd.set_wizard()'],
                    ]
        elif self.mode == 'Measure':
            return [
                    [ 1, 'Mtssl Wizard',''],
                    [ 3, 'Mode: %s'%self.mode,'mode'],
                    [ 3, 'Distances to file?: %s'%self.writeToFile,'writeToFile'],
                    [ 2, 'Reset','cmd.get_wizard().reset()'],
                    [ 2, 'Done','cmd.set_wizard()']
                    ]
        elif self.mode == 'Copy & Move':
            return [
                    [ 1, 'Mtssl Wizard',''],
                    [ 3, 'Mode: %s'%self.mode,'mode'],
                    [ 2, 'Reset','cmd.get_wizard().reset()'],
                    [ 2, 'Done','cmd.set_wizard()']
                    ]
                   


def open_wizard():
====How people got it to run...====
    wiz = MtsslWizard()
*On a Mac it is easiest to install Pymol, Numpy, WxPython, Scipy and Matplotlib via fink.
    cmd.set_wizard(wiz)
"I installed Pymol 1.5 via MacPorts. After putting pyperclip in the python 2.6 library folder, I then downloaded mtsslWizard and used the plugin installer to incorporate it. This was very simple and trouble-free."


cmd.extend('mtssl_wizard', open_wizard)
==Usage==
===Labeling===
#Open a structure in PyMOL and remove any unwanted solvent molecules or ligands.  
#Start the mtsslWizard via Wizards>mtsslWizard
#If needed, vary the search parameters: "Speed" and "vdW restraints". 'Speed' determines how many conformations of the label will be generated and checked for clashes. The 'vdW restraints' parameter determines how stringent conformations are checked for clashes with the macromolecular surface.
#Click "Search conformers!" to start the calculation.


def generateRandomChiAngle():
===Distance calculation===
    chi=random.random()*360.0
#change "Mode" to "Distance"
    return chi
#click the first and second ensemble
#The program will now calculate all possible distances between the conformations in the two ensembles. If both ensembles have many conformations, this can take a couple of seconds!
#The calculated distributions can be viewed with [[mtsslPlotter]].


Distances and a histogram are directly copied to the clipboard or written out to a file. The result file contains 4 columns:
#distances
#bins for histogram
#histogram frequencies
#histogram frequencies with highest value normalized to 1.0 for comparisons


def checkChi(self, chi, chiId):
    #in free mode, all angles are allowed
    if self.rotamers == 'Unrestricted':
        self.allowedAngle=[True, True, True, True, True]
    #restrict chi angles to values from MMM rotamer library
    elif self.rotamers == 'Restricted':
        if chiId == 'chi1' and ((55.0 <= chi < 65.0) or (185.0 <= chi < 195.0) or (295.0 <= chi < 305.0)):
            self.allowedAngle[0]=True
        else:
            self.allowedAngle[0]=False
        if chiId == 'chi2' and ((60.0 <= chi < 90.0) or (165.0 <= chi < 195.0) or (272.0 <= chi < 303.0)):
            self.allowedAngle[1]=True
        else:
            self.allowedAngle[1]=False
        if chiId == 'chi3' and ((75.0 <= chi < 105.0) or (255.0 <= chi < 285.0)):
            self.allowedAngle[2]=True
        else:
            self.allowedAngle[2]=False
        if chiId == 'chi4' and ((70.0 <= chi < 90.0) or (165.0 <= chi < 195.0) or (272.0 <= chi < 292.0)):
            self.allowedAngle[3]=True
        else:
            self.allowedAngle[3]=False
        if chiId == 'chi5' and ((75.0 <= chi < 95.0) or (130.0 <= chi < 150.0) or (210.0 <= chi < 230.0) or (270.0 <= chi < 290.0)):
            self.allowedAngle[4]=True
        else:
            self.allowedAngle[4]=False


===Distance maps===
#change "Mode" to "Distance map"
#For a simple distance map: click twice on the protein of interest
#For a difference distance map between two conformations of a protein: click once on each of the two conformations. For this feature to work properly, both conformations should have the same number of residues. This can be easily achieved using standard PyMOL commands.
#The maps can be viewed with [[mtsslPlotter]]


==Reference==
If you find this program useful, please cite this paper:


def internalClash(self,selection): #this function checks for internal clashes of a new conformation
Hagelueken G, Ward R, Naismith JH, Schiemann O (2012) MtsslWizard: In silico Spin-Labeling and Generation of Distance Distributions in PyMOL. Appl. Magn. Res. accepted for publication
    atoms=getAtypes()
    for atom1 in range(len(atoms)-1):
        for atom2 in range(atom1+1, len(atoms)):
            # skip exceptions
            if knownExceptions[atom1][atom2]==1:
                #print "Excepted %s and %s" % (atoms[atom1], atoms[atom2])
                continue
            sel1, sel2 = selection + " & name " + atoms[atom1], selection + " & name " + atoms[atom2]
            dist=cmd.dist("tmp_dist", sel1, sel2)
            #cmd.select("isNeighbor", "(neighbor "+ sel1 + ") & (" + sel2 +")")
            #count=cmd.count_atoms("isNeighbor")
            #cmd.delete("isNeighbor")
            cmd.delete("tmp_dist")
           
            if dist < internalClash_cutoff:
                #print sel1, sel2, dist
                return True


    return False
It also contains detailed informations about the program, examples and a discussion of limitations of the approach.
 
def superpose(residue1,residue2):
    #get the position of the selected residue's O atom
    stored.xyz = []
    cmd.iterate_state(1,residue2+" & name O","stored.xyz.append([x,y,z])")
    #print stored.xyz.pop(0)
    if cmd.pair_fit(residue1+" & name CA",residue2+" & name CA",
                    residue1+" & name N", residue2+" & name N",
                    residue1+" & name C", residue2+" & name C",
                    residue1+" & name CB",residue2+" & name CB"):
        #set the label's O atom to the stored position
        cmd.alter_state(1,residue1+" & name O","(x,y,z)=stored.xyz.pop(0)")
        return True
    else:
        return False
 
def copyAndMove(residue1_name, residue2_name, picked_object1, numberOfLabel):
    label="mtssl_"+str(numberOfLabel)   
    cmd.copy(label+"_copied", picked_object1)
    superpose(label+"_copied", residue2_name)
 
def mtsslify(self, selected_object, selected_residue, numberOfLabel, thoroughness, cutoff, maxClash):  #generate and check conformations semi-systematically
    #max number of conformations
    numberToFind=5000
   
    if thoroughness == 'painstaking':
        repeat=500
    elif thoroughness == 'thorough search':
        repeat=100
    elif thoroughness == 'normal search':
        repeat=30
        numberToFind=200
    elif thoroughness == 'quick search':
        repeat=10
        numberToFind=100
   
    #generate the label and superpose onto selected position
    generateMtssl(numberOfLabel)
    label="mtssl_"+str(numberOfLabel)
    print "Attempting superposition..."
    if not superpose(label, selected_residue):
        print "Superposition does not work. Glycine? Mutate to Ala first."
        return
    else:
        print "Superposition worked!"
   
    #create object with only the atoms around the label to speed everything up
    protein=selected_object+" &! "+ selected_residue + " within 15.0 of "+label
    cmd.create("labelEnvironment_"+label,protein)
   
    #reset some counters and initialize variables
    clashStateCounter=1
    noClashStateCounter=1
    internalClashCounter=1
    snugglyFitStateCounter=1
    chi1=0
    chi2=0
    chi3=0
    chi4=0
    chi5=0
    if self.rotamers=='Unrestricted':
        step=120
    else:
        step=30
   
    print "Trying to find conformations for label %s with thoroughness: %s" % (label, thoroughness)
   
    found=0
    snugglyFitAtomCountList=[]
    bestSnugglyFitAtomCount = 0
    snugglyFitAtomCountSum = 0
    bestSnugglyFitChiAngles = ""
    cmd.select(label+"_r1a_head", label+" &! name N+CA+CB+O+C")
   
    #by running this repeatedly with different starting angles, the conformational space is sampled more quickly then by using a very small step size
    x=0
    for x in range (0,repeat):
        self.allowedAngle=[False,False,False,False,False]
        offset1=int(random.random()*step)
        offset2=int(random.random()*step)
        offset3=int(random.random()*step)
        offset4=int(random.random()*step)
        offset5=int(random.random()*step)
        #chi1 loop
        for chi1 in range(0+offset1,360+offset1,step):
            checkChi(self, chi1, 'chi1')
            if self.allowedAngle[0]==True and numberToFind > found:
                cmd.set_dihedral(label+" & name N",label+" & name CA",label+" & name CB",label+" & name SG",chi1,state=1,quiet=1)
                #check which atoms of protein lie within specified cutoff
                cmd.create(label+"_clashAtoms", "labelEnvironment_"+label+" within  "+str(cutoff)+" of "+label+" & name SG",1,clashStateCounter,1)
                bumps=cmd.count_atoms(label+"_clashAtoms & state "+str(clashStateCounter))
                cmd.delete(label+"_clashAtoms") 
                if bumps > 0:
                    print ".",
                else:
                    #chi2 loop
                    for chi2 in range(0+offset2,360+offset2,step):
                        checkChi(self, chi2, 'chi2')
                        if self.allowedAngle[1]==True and numberToFind > found:
                            cmd.set_dihedral(label+" & name CA",label+" & name CB",label+" & name SG",label+" & name SD",chi2,state=1,quiet=1)
                            cmd.create(label+"_clashAtoms", "labelEnvironment_"+label+" within  "+str(cutoff)+" of "+label+" & name SD",1,clashStateCounter,1)
                            bumps=cmd.count_atoms(label+"_clashAtoms & state "+str(clashStateCounter))
                            cmd.delete(label+"_clashAtoms")
                            if bumps>0:
                                print ".",
                            else:
                                #chi3 loop
                                for chi3 in range (0+offset3,360+offset3,step):
                                    checkChi(self, chi3, 'chi3')
                                    if self.allowedAngle[2]==True and numberToFind > found:
                                        cmd.set_dihedral(label+" & name CB",label+" & name SG",label+" & name SD",label+" & name CE",chi3,state=1,quiet=1)
                                        cmd.create(label+"_clashAtoms", "labelEnvironment_"+label+" within  "+str(cutoff)+" of "+label+" & name CE",1,clashStateCounter,1)
                                        bumps=cmd.count_atoms(label+"_clashAtoms & state "+str(clashStateCounter))
                                        cmd.delete(label+"_clashAtoms")
                                        if bumps>0:
                                            print ".",
                                        else:
                                            #chi4 loop
                                            for chi4 in range (0+offset4,360+offset4,step):   
                                                checkChi(self, chi4, 'chi4')
                                                if self.allowedAngle[3]==True and numberToFind > found:
                                                    cmd.set_dihedral(label+" & name SG",label+" & name SD",label+" & name CE",label+" & name C3",chi4,state=1,quiet=1)
                                                    #cmd.select(label+"_r1a_head", label+" &! name N+CA+CB+O+C")
                                                    cmd.create(label+"_clashAtoms", "labelEnvironment_"+label+" within  "+str(cutoff)+" of "+label+"_r1a_head",1,clashStateCounter,1)
                                                    bumps=cmd.count_atoms(label+"_clashAtoms & state "+str(clashStateCounter))
                                                    cmd.delete(label+"_clashAtoms")
                                                    if bumps>0:
                                                        print ".",
                                                    else:
                                                        #chi5 loop
                                                        for chi5 in range (0+offset5,360+offset5,step):   
                                                            checkChi(self, chi5, 'chi5')
                                                            if self.allowedAngle[4]==True and numberToFind > found:
                                                                cmd.set_dihedral(label+" & name SD",label+" & name CE",label+" & name C3",label+" & name C4",chi5,state=1,quiet=1)
                                                                cmd.create(label+"_clashAtoms", "labelEnvironment_"+label+" within  "+str(cutoff)+" of "+label+"_r1a_head",1,clashStateCounter,1)
                                                                bumps=cmd.count_atoms(label+"_clashAtoms & state "+str(clashStateCounter))
                                                                cmd.delete(label+"_clashAtoms")                               
                                                                if bumps<=maxClash:
                                                                    found+=1
                                                                    if self.clashGuard=="on" and internalClash(self, label):
                                                                        print found,
                                                                        cmd.create(label+"_internal_clash", label, 1, internalClashCounter)
                                                                        internalClashCounter+=1
                                                                    else:
                                                                        cmd.create(label+"_no_clash", label, 1, noClashStateCounter)
                                                                        cmd.select("snugglyFitTest", "labelEnvironment_"+label+" & ("+label+"_r1a_head around 4.5)")
                                                                        snugglyFitAtomCount=cmd.count_atoms("snugglyFitTest")
                                                                        cmd.delete("snugglyFitTest")
                                                                        #make entry in conformationList
                                                                        thisConformation=[chi1,chi2,chi3,chi4,chi5,snugglyFitAtomCount,noClashStateCounter]
                                                                        self.conformationList.append(thisConformation)
                                                                        print found,
                                                                        noClashStateCounter+=1
                                                                else:
                                                                    print ".",
        x+=1
    #carriage return
    print "\n"
    if len(self.conformationList) > 0:
        if self.thoroughness == 'painstaking':
            createSnugglyFitConformations(label,self.conformationList)
        polarPlot(self, label, self.conformationList)
    finalCosmetics(self, label,numberOfLabel,found,thoroughness, maxClash,cutoff)
    print "Done!"
 
 
def createSnugglyFitConformations(label,conformationList): #select conformations with the best fit to the molecular surface, rank them and create an object
    print "Snuggliest fit(s):"
    #calculate average atom count of all conformations
    atomCountSum=0
    snugglyFitList=[]
    bestSnugglyFitAtomCount=0
    for x in range (0,len(conformationList)):
        thisConformation=conformationList[x]
        atomCountSum+=thisConformation[5]
        if thisConformation[5] > bestSnugglyFitAtomCount:
            bestSnugglyFitAtomCount=thisConformation[5]
    averageAtomCount=atomCountSum/len(conformationList)
    #generate snugglyFitList: take only those conformations whose atom count is > 0.75 of top peak and higher than the average
    counter=1
    for x in range (0,len(conformationList)):
        thisConformation=conformationList[x]
        if thisConformation[5] > 0.75 * bestSnugglyFitAtomCount and thisConformation[5] > averageAtomCount:
            snugglyFitList.append({'chi1':thisConformation[0],
                                  'chi2':thisConformation[1],
                                  'chi3':thisConformation[2],
                                  'chi4':thisConformation[3],
                                  'chi5':thisConformation[4],
                                  'vdw':thisConformation[5],
                                  'state':thisConformation[6]})
            cmd.create(label+"_snuggly", label+"_no_clash", thisConformation[6], counter)
            counter+=1
    #sort snugglyFitList so that best fitting conformation is on top 
    snugglyFitList = sorted(snugglyFitList, key=itemgetter('vdw'))
    snugglyFitList.reverse()
    #print out the list
    if len(snugglyFitList)>0:
        for i in range (0,len(snugglyFitList)):
            print "Conformation %i: \t\t%i \t\t\t vdW contacts" %(snugglyFitList[i]['state'],snugglyFitList[i]['vdw'])
    print "Average vdW contacts of all possible conformations: ",averageAtomCount
   
   
   
 
def finalCosmetics(self, label, numberOfLabel, found, thoroughness,maxClash,cutoff): #make everything look nice
    if found >= 1:
        print "Found %i conformations." %found
        #show all conformations and do some coloring
        cmd.set("all_states",1)
        self.toggleStatesCaption='Toggle states: ON'
        cmd.color("blue",label+"_no_clash")
        cmd.color("red", "name O1")
        cmd.disable(label)
        cmd.disable(label+"_internal_clash")
        cmd.show("spheres", "name O1")
        cmd.set("sphere_scale", "0.2")
        identifierLabel="%s|%s|%s|%1.2f|%i|%s" %(label,self.mode, self.rotamers, cutoff, maxClash, thoroughness)
        print identifierLabel
        cmd.pseudoatom(label+"_label", label)
        cmd.label(label+"_label", `identifierLabel`)
        cmd.show("label")
        cmd.group("mtsslWiz_"+str(numberOfLabel), label+"*"+","+"labelEnvironment_"+label)
        #cmd.hide("label")
    else:
        print "Sorry, I did not find anything. Your options are:\n1) Try again or\n2) Try to increase 'thoroughness' (now: "+str(thoroughness)+"), \nincrease'maxClash' (now: "+str(maxClash)+") or \ndecrease cutoff (now: "+str(cutoff)+")."
        cmd.delete(label+"*")
        print label
   
 
def polarPlot(self,label,conformationList): #generate file for polar plot. Use polar_plot.py to plot it.
    if self.writeToFile=='yes':
        chiFile=open(label+"_chiFile.txt", 'w')
        for x in range (0, len(conformationList)):
            thisConformation=conformationList[x]
            chiFile.write("%s %s %s %s %s\n" % (thisConformation[0],thisConformation[1],thisConformation[2],thisConformation[3],thisConformation[4]))
        chiFile.close()
   


==Older versions==
*[https://github.com/Pymol-Scripts/Pymol-script-repo/blob/5935bdad82a480a4e004c8c902ef69dc75389ac8/plugins/mtsslWizard.py Version 1.0]


#calculate distances between all possible conformations
==Contact==
def quick_dist(self, s1, s2, inFile=None):
hagelueken'at' uni-bonn.de
    if self.writeToFile=='yes':
        filename="distances_%s-%s.txt" %(self.picked_object1,self.picked_object2)
        filename.replace(' ', '_')
        f = open(filename, 'w')
    s=""
    s+="DIST\n"
    distanceList=[]
    #find the amount of conformations
    m1States=cmd.count_states(s1)
    m2States=cmd.count_states(s2)
    #do the distance calculation for all states
    for i in range (1,m1States+1):
        print ".",
        for j in range (1,m2States+1):
            m1 = cmd.get_model(s1,i)
            m2 = cmd.get_model(s2,j)
            for c1 in range(len(m1.atom)):
                for c2 in range(len(m2.atom)):
                    #current distance
                    currentDistance=math.sqrt(sum(map(lambda f: (f[0]-f[1])**2, zip(m1.atom[c1].coord,m2.atom[c2].coord))))
                    distanceList.append(currentDistance)
                    #print out table
                    s+="%3.2f\n" % (currentDistance)
   
    cmd.distance(s1,s2)
    #calculate cbeta for comparison
    s1=self.picked_object1+" & name CB"
    s2=self.picked_object2+" & name CB"
    m1 = cmd.get_model(s1,1)
    m2 = cmd.get_model(s2,1)
    for c1 in range(len(m1.atom)):
        for c2 in range(len(m2.atom)):
            cBeta=math.sqrt(sum(map(lambda f: (f[0]-f[1])**2, zip(m1.atom[c1].coord,m2.atom[c2].coord))))
    s+="\n"
    cmd.dist("cB_"+self.picked_object1+"_"+self.picked_object2, self.picked_object1+" & name CB", self.picked_object2+" & name CB")
   
    if self.writeToFile=='yes':
        f.write(s)
        f.close()
    print calculateStatistics(distanceList)
    print "Cbeta distance: %3.1f" %cBeta
   
       
def calculateStatistics(distanceList_strings): #create distance histogram...
    statisticsResult=""
    #easy statistics
    distanceList=sorted([float(x) for x in distanceList_strings])
    average = sum(distanceList)/len(distanceList)
    median = distanceList[len(distanceList)/2]
    longest = distanceList[len(distanceList)-1]
    shortest = distanceList[0]
    #generate histogram
    bins=[]
    bins.append(shortest)
    binSize=(longest-shortest)/10
    for i in range (1, 10, 1):
        bins.append(shortest + i * binSize)
    hist,bin_edges=numpy.histogram(distanceList,bins=bins,normed=True)
    histDict={}
    histZoomFactor=100
    max_freq=0
    #convert histogram to dictionary for easier generation of text histogram
    print
    for i in range(0,len(hist),1):
        histDict[i]=int(round(hist[i]*histZoomFactor))
        #print histDict[i]
        if histDict[i] > max_freq:
            max_freq = histDict[i]
    #print out stuff
    statisticsResult+="Distance histogram:\n"
    for i in range(max_freq, -1, -1):
        for bin in sorted(histDict.keys()):
            if histDict[bin] >= i:
                statisticsResult+='#'
            else:
                statisticsResult+=" "
        statisticsResult+="\n"
    statisticsResult+= "Average distance: %3.2f\n" %average
    statisticsResult+= "Median of distribution: %3.2f\n" %median
    statisticsResult+= "Shortest distance: %3.2f\n" % shortest
    statisticsResult+= "Longest distance: %3.2f" %longest
    return statisticsResult


def generateMtssl(numberOfLabel): #create a mtssl label object.
==Acknowledgement==
    cmd.read_pdbstr("""HEADER    MTSSL\n
Thanks to Jason Vertrees and Thomas Holder for some programming tips.
COMPND    coordinates of R1A      from program: libcheck\n                       
CRYST1  100.000  100.000  100.000  90.00  90.00  90.00 P 1\n                     
SCALE1      0.010000  0.000000  0.000000        0.00000\n                       
SCALE2      0.000000  0.010000  0.000000        0.00000\n                       
SCALE3      0.000000  0.000000  0.010000        0.00000\n                       
ATOM      1 N    R1A A  1      0.201  -0.038  -0.149  1.00 20.00          N\n
ATOM      2 CA  R1A A  1      1.258  1.007  -0.271  1.00 20.00          C\n
ATOM      4 CB  R1A A  1      2.056  0.796  -1.554  1.00 20.00          C\n
ATOM      7 SG  R1A A  1      3.667  1.492  -1.387  1.00 20.00          S\n
ATOM      8 SD  R1A A  1      4.546  1.587  -3.180  1.00 20.00          S\n
ATOM      9 CE  R1A A  1      5.573  3.020  -3.244  1.00 20.00          C\n
ATOM    12 C3  R1A A  1      6.644  3.007  -4.321  1.00 20.00          C\n
ATOM    13 C4  R1A A  1      7.349  4.109  -4.593  1.00 20.00          C\n
ATOM    15 C5  R1A A  1      8.361  3.885  -5.680  1.00 20.00          C\n
ATOM    16 C7  R1A A  1      9.758  4.118  -5.119  1.00 20.00          C\n
ATOM    20 C6  R1A A  1      8.092  4.808  -6.859  1.00 20.00          C\n
ATOM    24 N1  R1A A  1      8.144  2.482  -5.989  1.00 20.00          N\n
ATOM    25 O1  R1A A  1      8.792  1.889  -6.835  1.00 20.00          O\n
ATOM    26 C2  R1A A  1      7.092  1.857  -5.197  1.00 20.00          C\n
ATOM    27 C8  R1A A  1      7.642  0.712  -4.360  1.00 20.00          C\n
ATOM    31 C9  R1A A  1      5.961  1.403  -6.123  1.00 20.00          C\n
ATOM    35 C    R1A A  1      0.670  2.388  -0.261  1.00 20.00          C\n
ATOM    36 O    R1A A  1      -0.298  2.670  -0.967  1.00 20.00          O\n""","mtssl_"+ str(numberOfLabel))
</source>

Latest revision as of 14:00, 21 May 2020

Type PyMOL Plugin
Download plugins/mtsslWizard.py
Author(s) Gregor Hagelueken
License -
This code has been put under version control in the project Pymol-script-repo

mtsslWizard

mtsslWizard is a PyMOL wizard for in silico spin labeling of proteins.

News

2020-05-21

  • If you are having trouble with installation give this a try

2017-01-17:

2015-07-27:

  • uploaded a new version (1.3) to repository. Includes some new spin labels and a distance map feature. Plots can be viewed with mtsslPlotter.

2014-03-04:

  • uploaded a new version (1.12) to repository. Fixes a bug that occurred on some machines. Thanks to C. Engelhard for noticing!

2013-07-05:

  • added two new labels: DOTA and K1 (pAcPhe based)

2013-01-31:

Version 1.1 in script repository.

Some new features of v1.1:

  • Much faster. The algorithm was optimized and the speed of the program is now almost independent off the size of the molecule. Due to this, 'thorough search' is now set as default and the 'copy and move' mode has been dropped.
  • New spin labels. The program now contains MTSSL, PROXYL and two labels for nucleic acids. Additional spin labels can be added upon request.
  • Distances and histogram are directly copied to the clipboard or written out to a file as before. The result file contains 4 columns: 1-distances, 2-bins for histogram, 3-histogram frequencies, 4-histogram frequencies with highest value normalized to 1.0 for comparisons
  • Improved interface. Amongst other things, the clash control settings were simplified: There are now only two settings for vdW restraints: 'tight' and 'loose'. Also, only the average and c-Beta distances are displayed in the PyMOL viewer to avoid screen clutter (see screenshot).

The new version was thoroughly tested. If you encounter any bugs or problems, please use the contact address below.

Version 1.0 is still available here.

Program features

Spin labels can be attached to any position of a protein or nucleic acid just by pointing and clicking. The program then searches the conformational space of the label and determines which conformations of the label do not clash with the macromolecule. In "distance mode", distances between label ensembles can be determined and exported. In "distance map" mode, the program quickly estimates the inter-label distances between all possible spin pairs in a protein molecule. The result is saved as a color coded distance map. It is also possible to calculate difference distance maps between two conformations of a protein.

Please reference:

MtsslWizard: In Silico Spin-Labeling and Generation of Distance Distributions in PyMOL, Gregor Hagelueken, Richard Ward, James H. Naismith and Olav Schiemann, DOI: 10.1007/s00723-012-0314-0

Screen shot

MtsslWizardv1-1.jpg

Installation

Install the program by copying the code from the link above into an empty text file (e.g. "mtsslWizard.py") located in the \Pymol\modules\pmg_tk\startup directory. After PyMOL has been started, the program can be launched from the WIZARDS menu. Alternatively install the wizard via the plugins menu.


mtsslWizard has been tested with PyMOL 1.7. It does not work with PyMOL 1.3. Here are manuals on how to install it on Mac or Windows.

Additional requirements:

  • SciPy has to be installed
  • Pyperclip or xerox have to be installed for the clipboard support.

How people got it to run...

  • On a Mac it is easiest to install Pymol, Numpy, WxPython, Scipy and Matplotlib via fink.

"I installed Pymol 1.5 via MacPorts. After putting pyperclip in the python 2.6 library folder, I then downloaded mtsslWizard and used the plugin installer to incorporate it. This was very simple and trouble-free."

Usage

Labeling

  1. Open a structure in PyMOL and remove any unwanted solvent molecules or ligands.
  2. Start the mtsslWizard via Wizards>mtsslWizard
  3. If needed, vary the search parameters: "Speed" and "vdW restraints". 'Speed' determines how many conformations of the label will be generated and checked for clashes. The 'vdW restraints' parameter determines how stringent conformations are checked for clashes with the macromolecular surface.
  4. Click "Search conformers!" to start the calculation.

Distance calculation

  1. change "Mode" to "Distance"
  2. click the first and second ensemble
  3. The program will now calculate all possible distances between the conformations in the two ensembles. If both ensembles have many conformations, this can take a couple of seconds!
  4. The calculated distributions can be viewed with mtsslPlotter.

Distances and a histogram are directly copied to the clipboard or written out to a file. The result file contains 4 columns:

  1. distances
  2. bins for histogram
  3. histogram frequencies
  4. histogram frequencies with highest value normalized to 1.0 for comparisons


Distance maps

  1. change "Mode" to "Distance map"
  2. For a simple distance map: click twice on the protein of interest
  3. For a difference distance map between two conformations of a protein: click once on each of the two conformations. For this feature to work properly, both conformations should have the same number of residues. This can be easily achieved using standard PyMOL commands.
  4. The maps can be viewed with mtsslPlotter

Reference

If you find this program useful, please cite this paper:

Hagelueken G, Ward R, Naismith JH, Schiemann O (2012) MtsslWizard: In silico Spin-Labeling and Generation of Distance Distributions in PyMOL. Appl. Magn. Res. accepted for publication

It also contains detailed informations about the program, examples and a discussion of limitations of the approach.

Older versions

Contact

hagelueken'at' uni-bonn.de

Acknowledgement

Thanks to Jason Vertrees and Thomas Holder for some programming tips.

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