Undergraduate Research Journal

Molecular Analysis of the Interaction Between Staphylococcus aureus Protein Sbi and Immune System Protein C3d
Wilson Rodriguez
in terms of their electrostatic interactions. AESOP as a
computational tool serves to provide researchers with a
theoretical insight to protein physicochemical properties.
The analysis can also be used in the design of proteins
with desired functions, if these functions depend on the
physicochemical properties under consideration (in our
case electrostatic potentials). Molecular visualization and
analysis outside AESOP was performed using the programs
Chimera 10 and VMD. 11
Figure 2. Thermodynamic cycle for Poisson-Boltzmann free
energy calculations. Electrostatic potential is represented by
isopotential contours. Red and blue contours have values of +1
and -1, respectively. Proteins A, B, AB are shown in the figure
as c3d, sbi and c3d-sbi, respectively. The top horizontal process
represents protein association in reference state of uniform
dielectric and no ions present. The bottom horizontal process
represents the same association with protein dielectric of 20,
solvent dielectric of 78.54 and ion concentration of 150mM.
Solvation process is represented by the three vertical processes. 5-7
In order to simultaneously account for both solvation and
association the ∆∆G solvation association free energy (Fig. 2) was
calculated which is equal to the difference of the horizontal
and vertical processes according to
(3)
∆∆G solvation was then used in the comparison of mutants and
their complex interactions. In order to cluster the mutants
based on their electrostatic similarity distances (ESD), the
Average Normalized Distance (AND) measurement was
employed
AND a,b
= 1 ! a
(i, j, k)!! b
(i, j, k)
" (4)
N
i, j,k
max(! a
(i, j, k) , ! b
(i, j, k) )'
and represented in a hierarchical clustering dendrogram. 5
In equation (4) φ a
and φ b
are the electrostatic potentials of
proteins A and B, respectively, at grid points (i,j,k) and N is
the number of grid points.
Theoretically, the mutants that have similar spatial
distributions of electrostatic potentials will cluster, or
group, together and are expected to behave similarly
RESULTS
We generated two pairs of dendrograms, one for each
complex site of Fig. 1. The dendrograms represent alanine
scan mutations and are shown in Fig. 3. The mutant
name scheme is as follows: residue number according to
sequence, single letter code of residue and end-mutated
residue alanine. The dendrogram is analyzed according
to the length of the branches and connections to other
“clusters” in the overall family tree of mutants, i.e. two
residues next to each other share similarity in terms of
electrostatic potential and that cluster is related to mutants
next to it as well as other clusters next to it; the shorter the
length of the branches, the more similar the clusters (and
proteins within the clusters) are. According to equation (4),
an AND value of zero denotes identity and as the value
deviates from zero denotes increasing dissimilarity (up to a
value of 2 for most dissimilar).
In general, mutations of similarly charged residues will
cluster together, i.e. mutations of acidic residues form
the cluster colored in red in Fig. 3, whereas mutations of
basic residues form the cluster colored in blue in Fig. 3.
The parent protein and mutations of the neutral histidines
also form a distinct cluster, colored in black in Fig. 3.
While the dendrograms provide insightful information
on similar electrostatic character and function, they do
not provide analytical information on the favorability of
the interaction. We then use the association free energy of
solvation to assess the predicted gain or loss of binding.
The free energies indicate the effect the mutation had on
the complex where negative energies indicate a favorable
interaction and mutations converging toward positive free
energies indicate the mutation was unfavorable. In the
case of Complex 1, mutations of acidic negatively charged
2 6 U C R U n d e r g r a d u a t e R e s e a r c h J o u r n a l