Chemistry Reference
In-Depth Information
Fig. 9.2
Visualization of bovine recoverin surface (PDB code 1REC) using Chimera software and
two coloring possibilities: (
a
) by atom (carbon in
grey
, nitrogen in
blue
and oxygen in
red
) and (
b
)
Coulombic Surface Coloring from
−
10 (
red
)to
+
10 (
blue
)
Numerous computational tools have been developed for protein structures and
surfaces visualization and analysis. Usually, they allow surface representation and
visualization, comparison of aligned protein surfaces, calculation of geometrical
(area) and physicochemical (electrostatic potential and hydrophobicity) properties
of surfaces and/or emphasizing PPIs. They also provide calculation of the geometri-
cal properties of the entire protein, such as its volume and surface area. The protein
volume computation informs about protein packing efficiency and small changes
in packing efficiency due to ligand binding are significant and notifies about pro-
tein interactions (Tsai et al.
1999
). Also, surface descriptors are provided: surface
residues, surface patches, surface curvature (Albou et al.
2009
). A few examples
of such computational tools are: PyMol (DeLano
2002
), Chimera (Pettersen et al.
2004
), SURFACE (Ferre et al.
2004
) and 3D-SURFER (Li et al.
2008
).
Graphical surface representation and visualization allows a quick understanding
and interpretation of protein shape, charge distribution and polarity, correlated to
the protein possible interactions. All this information is useful in many areas of
molecular modeling. A short illustration of the use of mentioned tools for protein
surface analysis and characterization is provided further.
The specificity of protein-ligand, protein-DNA and PPIs is usually due to elec-
trostatic and/or hydrophobic interactions. Qualitative analysis of the electro-static
properties of the protein surface provides information on the local charge density. It
reveals how positive, negative or neutral a region of the protein surface is relative to
the rest of the protein. The local charge density may influence how and where various
ligands bind. If these ligands are also charged, the binding might be significantly in-
creased. Figure
9.2
depict the surface of bovine recover-in visualized using Chimera
software (Pettersen et al.
2004
): the surface is colored by atom type (Fig.
9.2
a, the
carbon is grey, nitrogen is blue and oxygen is red) and also using Coulombic Surface
Coloring (Fig.
9.2
b). Chimera software also allows calculation of the protein volume
