# Visualizing Electron Density¶

## Problem¶

You want to visualize how a ligand fits into an electron density grid in a 2D molecule diagram (see Figure 1). The electron density grid with various contour levels and the 3D molecule is shown in Table 1.

Figure 1. Example of visualizing ligand electron density fit (PDB: 1ETS)

 contour 1.0 contour 1.5 contour 2.0

## Ingredients¶

 OEChem TK - cheminformatics toolkit OEDepict TK - molecule depiction toolkit Grapheme TK - molecule and property visualization toolkit

## Difficulty Level¶

elecdensity2img.py

## Solution¶

The set_electron_density_contour_overlap function tags an atom if its coordinates inside the grid at the given contour level.

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 def set_electron_density_contour_overlap(mol, edgrid, contour, contour_tag): """ Sets whether atoms are inside the electron density grid at the given contour level. :type mol: oechem.OEMolBase :type edgrid: oegrid.OESkewGrid :type contour: float :type: contour_tag: int """ center = oechem.OEFloatArray(3) extents = oechem.OEFloatArray(3) oechem.OEGetCenterAndExtents(mol, center, extents) subgrid = oegrid.OEScalarGrid() # expand the grid a bit for proper overlaps extents[0] += 2.5 extents[1] += 2.5 extents[2] += 2.5 oegrid.OEMakeRegularSubGrid(subgrid, edgrid, center, extents, 0.5, edgrid.GetReentrant() >= 7) for atom in mol.GetAtoms(oechem.OEIsHeavy()): xyz = mol.GetCoords(atom) val = subgrid.GetValue(xyz[0], xyz[1], xyz[2]) if val > contour: atom.SetData(contour_tag, val) 

The depict_erlectron_density_fit function shows how to project the electron density fit with various contour levels into a 2D molecule diagram. First the image is divided into two image frames since both a molecule and a color gradient will be depicted. Then the set_electron_density_contour_overlap function is called that calculates whether the atoms of the molecule are inside the electron density grid at various contour levels (see lines 21-23). The molecule is then prepared for depiction generating its 2D coordinates by calling the OEPrepareDepictionFrom3D function (lines 27-32). After constructing a color gradient that will assign colors to various contour levels, the function loops over the atoms and draws a circle around them if they are embedded into the electron density grid (> 0.2) with a color and radius that corresponds to the given contour level (lines 42-51). Finally, the molecule along with the color gradient is rendered to the image (lines 55-62). You can see the result in Figure 1.

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 def depict_electron_density_fit(image, mol, edgrid, opts): """ Depicts the molecule with electron density fit. :type image: oedepict.OEImageBase :type mol: oechem.OEMolBase :type edgrid: oegrid.OESkewGrid :type opts: oedepict.OE2DMolDisplayOptions """ # generate image frames width, height = image.GetWidth(), image.GetHeight() mframe = oedepict.OEImageFrame(image, width, height * 0.90, oedepict.OE2DPoint(0.0, 0.0)) lframe = oedepict.OEImageFrame(image, width, height * 0.10, oedepict.OE2DPoint(0.0, height * 0.90)) # calculate fit to electron density at various contours contours = [1.0, 1.5, 2.0] for contour in contours: set_electron_density_contour_overlap(mol, edgrid, contour, get_contour_tag(contour)) # prepare molecule for depiction width, height = mframe.GetWidth(), mframe.GetHeight() opts.SetDimensions(width, height, oedepict.OEScale_AutoScale) oegrapheme.OEPrepareDepictionFrom3D(mol) opts.SetScale(oedepict.OEGetMoleculeScale(mol, opts) * 0.95) disp = oedepict.OE2DMolDisplay(mol, opts) # create color gradient colorg = oechem.OELinearColorGradient() colorg.AddStop(oechem.OEColorStop(min(contours), oechem.OEColor(190, 190, 255))) # light blue colorg.AddStop(oechem.OEColorStop(max(contours), oechem.OEColor(80, 80, 255))) # medium blue # visualize electron density fit layer = disp.GetLayer(oedepict.OELayerPosition_Below) for contour in contours: contour_tag = get_contour_tag(contour) radius = get_contour_radius(contour, contours, disp) color = colorg.GetColorAt(contour) pen = oedepict.OEPen(color, color, oedepict.OEFill_On, 1.0) for atom in mol.GetAtoms(): if atom.HasData(contour_tag): adisp = disp.GetAtomDisplay(atom) layer.DrawCircle(adisp.GetCoords(), radius, pen) # render molecule oedepict.OERenderMolecule(mframe, disp) # draw color gradient copts = oegrapheme.OEColorGradientDisplayOptions() copts.SetColorStopPrecision(1) copts.AddMarkedValues(contours) oegrapheme.OEDrawColorGradient(lframe, colorg, copts) 

## Usage¶

Usage

elecdensity2img.py and supporting data 1eta_sigma.mtz and 1eta_ligand.pdb

prompt > python3 elecdensity2img.py -grid 1eta.mtz -ligand 1eta_ligand.sdf -out 1eta.png


### Command Line Parameters¶

Simple parameter list
-height : Height of output image
-width : Width of output image

molecule display options :
-titleloc : Location of the molecule title

input/output options
-ligand : Input filename of the ligand
-grid : Input filename of electron density map (MTZ)
-out : Output filename of the generated image


## Discussion¶

Visualizing electron density helps to evaluate the quality of protein-ligand structures. The Iridium database divides the protein-ligand structures into three categories:

• Iridium-NT (not trustworthy)
• Iridium-MT (moderately trustworthy)
• Iridium-HT (highly trustworthy)

Not surprisingly the 1ETS complex (Figure 1 is considered “not trustworthy” by the Iridium database. The Table 2 shows examples from the MT and HT categories of the Iridium database

 1COY - Iridium MT 1D3H - Iridium HT

The visualization also helps to compare the “deposited” starting models of the Iridium database with the models that are refined by AFITT. See example in Table 3.

 deposited starting model model after AFITT refinement

### Command Line Parameters¶

Simple parameter list
input/output options
-complex : Input filename of the protein-ligand complex
-out : Output filename of the generated image

residue options
-ignore-isolated : Removes isolated atoms prior to depiction
-ignore-water : Removes water molecule prior to depiction
-max-residues : Controls the maximum number of residues depicted in each
line


API

Theory