Map set: Difference between revisions

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[[Image:Map_set_ex.png‎|right|thumb|300px|Map_set created this consensus volume representation of aligned ligands bound to kinases.  See example below.]]
[[Map_set]] provides a number of common operations on and between maps.  For example, with [[Map_set]] you can add two maps together or create a consensus map from a series of maps or even take a difference map.
[[Map_set]] provides a number of common operations on and between maps.  For example, with [[Map_set]] you can add two maps together or create a consensus map from a series of maps or even take a difference map.
   
   
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  <source lang="python">
  <source lang="python">
# add 3 maps
# add 3 maps
map_set my_sum, add, map1 map2 map3
map_set my_sum, sum, map1 map2 map3


# calculate the average map
# calculate the average map
map_set my_avg, average, map1 map2 map3
map_set my_avg, average, map1 map2 map3


</source>  
</source>


= Detailed Example =
= Detailed Example =

Latest revision as of 13:38, 10 February 2011

Map_set created this consensus volume representation of aligned ligands bound to kinases. See example below.

Map_set provides a number of common operations on and between maps. For example, with Map_set you can add two maps together or create a consensus map from a series of maps or even take a difference map.

Usage

map_set name, operator, operands, target_state, source_state

operator may be,

  • average
  • copy
  • difference
  • maximum
  • minimum
  • sum
  • unique

Examples

# add 3 maps
map_set my_sum, sum, map1 map2 map3

# calculate the average map
map_set my_avg, average, map1 map2 map3

Detailed Example

This example shows you how to create a consensus map of the bound ligand in a conserved pocket.

# fetch some similar proteins from the PDB
fetch 1oky 1h1w 1okz 1uu3 1uu7 1uu8 1uu9 1uvr, async=0

# align them all to 1oky; their ligands
# should all now be aligned
alignto 1oky

# highlight the ligands
as sticks, org

# select one of the atoms in the organic small mol
sele /1uu3//A/LY4`1374/NAT

# select entire molecules very near the chosen atom
select bm. all within 1 of (sele)

# remove the proteins; just look at small molecules
remove not (sele)

# create maps for all the ligands
python
for x in cmd.get_names():
  cmd.map_new( "map_" + x, "gaussian", 0.5, x)
python end

# calculate the average map
map_set avgMap, average, map*

# show as transparent surface
set transparency, 0.5

isosurface avgSurface, avgMap, 1.0

orient vis

Notes

source_state = 0 means all states

target_state = -1 means current state

This is an experimental function.


See Also

Map_new