Dynamic characterization and substrate binding of cis-2,3dihydrobiphenyl-2,3-diol dehydrogenase, an enzyme used in
bioremediation
Stefano Piccoli1, Francesco Musiani2,3,* and Alejandro Giorgetti1,*
1
Department of Biotechnology, University of Verona (Italy).
Scuola Internazionale Superiore di Studi Avanzati (SISSA/ISAS), Trieste (Italy).
3
Laboratory of Bioinorganic Chemistry, Department of Pharmacy and Biotechnology, University of Bologna
(Italy).
2
SUPPORTING IMFORMATION
S1. BPY conformational analysis
Density functional theory (DFT) computations have been carried out with the program ORCA 3.0.1 [1] using
the B3LYP [2, 3] functional. All atoms have been described by the 6-31G(d) basis set [4]. Frequency
computations have been performed to determine the nature of the various critical points.
The coordinates of BPY co-crystallized with biphenyl dehydrogenase (PDB accession code: 3ZV5) [5] was
used as starting point for the calculations. The hydrogen atoms of the initial model were added using the
program UCSF Chimera [6]. The geometry optimization at the B3LYP/6-31G(d) level resulted in a
conformation characterized by one benzene ring twisted by 40 degrees in relation to the other, as a
consequence of steric crowding of the hydrogen atoms (M1 in Fig. S1). The computation of the vibration
frequencies identified this conformation as a minimum on the potential energy surface. It was also possible
to identify a second conformational minimum corresponding to a benzene rings twisting angle of -40 degrees
(M2 in Fig. S1). Conformations M1 and M2 have the same potential energy. The search for a conformational
transition state along the reaction coordinate defined by the torsion of one benzene ring with respect to the
other resulted in conformation TS1 (Fig. S1). The computation of the vibration frequencies confirmed that
TS1 conformation is a saddle point of the first order (i.e. a transition state) on the potential energy surface. In
the TS1 conformation the molecules is completely planar. The calculated conformational barrier between M1
(or M2) and TS1 is 17.6 kJ mol-1.
Figure S1. Energies of the biphenyl-2,3-diol conformations studied at the B3LYP/6-31G(d) level.
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Table S1. Gibbs free enthalpies derived from the B3LYP/6-31G(d) calculations.
Point
Gibbs free Relative Gibbs free
enthalpy (Eh)
enthalpy (kJ/mol)
M1
-613.5710
0.0
TS1
-613.5643
17.6
M2
-613.5710
0.0
S2. Comparison between the PpBphB crystal structures
The crystal structures of the the apo, binary and holo forms of PpBphB dimers (PDBid: 2Y93, 2Y99, and
3ZV5, respectively) where superimposed using the program UCSF Chimera [6].
Table S2. Cα RMSD (nm) between the apo, binary, and holo forms of PpBphB dimers
RMSD (nm)
Apo
Binary
0.05
Binary
0.12
0.12
Holo
S3. Molecular docking
Figure S2. Haddock score vs. interface-ligand-RMSD (i-l-RMSD) plot [7]. PpBphB-BPY complexes
belonging to the same cluster are reported using dots of the same colour. Cluster average structures are
highlighted using triangle of the same colour of the dots.
Figure S3. Comparison between the BPY binding pose
found in the holo PpBphB crystal structure (PDBid: 3ZV5,
grey) and the best docking pose obtained using Haddock
(red). The experimental electron density of holo PpBphB is
reported in cyan.
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S4. Cluster analysis.
Clustering analysis has been performed using the g_cluster module of Gromacs [8], using the Gromos
algorithm [9]. A 0.15 nm cut-off for the Cα RMSD was used to include structures in the same cluster. Cterminal residues 259-276 from each chain were not considered in the RMSD calculation since they showed
very high mobility during the MD simulations (see Fig. S9 below).
Figure S4. Cluster population (left plot) and cluster number of each frame in the trajectory (right plot) for
the apo form.
Figure S5. Cluster population (left plot) and cluster number of each frame in the trajectory (right plot) for
the binary form.
Figure S6. Cluster population (left plot) and cluster number of each frame in the trajectory (right plot) for
the holo form.
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Figure S7. Structural alignment between the representative
structure of the two most populated clusters (Fig. S4) in
the trajectory of the holo form. The cartoons are reported
in green and cyan for cluster #1 and #2, respectively.
S5. Essential dynamics
The essential vectors are determined by diagonalizing the covariance matrices (cov):
1
𝑐𝑜𝑣𝑖𝑗 = 𝑀 ∑𝑀
𝑘=1[(𝑋𝑖 (𝑘) − ⟨𝑋𝑖 ⟩)(𝑋𝑗 (𝑘) − ⟨𝑋𝑗 ⟩)]
(Eq. 1)
where the sum goes over the M configurations or snapshots from the dynamics, 𝑋𝑖 (𝑘) corresponds to the ith
Cartesian coordinate of the system in snapshot number k, and ⟨𝑋𝑖 ⟩ is the mean value. From the
diagonalization of the covariance matrix, a set of eigenvalues (𝜆𝑖 ) and eigenvectors (𝜐𝑖 ) are obtained. Each
obtained eigenvector corresponds to an essential mode (EM) of the protein. Together, all of the essential
modes describe the motion of the protein along the MD run used to generate the computed matrix. The
eigenvalues obtained represent the relative contribution of each EM to the overall dynamics. The EM are
ranked according their eigenvalues and therefore their relative weight (𝑤𝑖 ), the first EM being the one with
major contribution or larger eigenvalue. The weight of each EM in the trajectory is calculated by:
𝜆𝑖
𝑖 𝜆𝑖
𝑤𝑖 = ∑
(Eq. 2)
C-terminal residues 259-276 from each chain were not considered in the RMSD calculation since they
showed very high mobility during the MD simulations (see Fig. S9 below).
Figure S8. (A-C) Cartoon representation of the structural movement along the first EM eigenvector of apo,
binary and holo forms of PpBphB (A, B, and C panel, respectively). Cartoons are colored with red and blue
structure corresponding to the two extreme structures along the EM. (D) Schematic representation of the
main movement along the first EM eigenvector in the three simulations.
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S6. Root mean square fluctuations
Figure S9. Average Cα RMSF values calculated for the apo (green line), binary (red line) and holo forms of
PpBphB.
Table S3. Average Cα RMSF (<RMSF>) of the residues in the central region of the substrate binding loop
(residues 198-206).
Form
<RMSF> (Chain A) <RMSF> (Chain B)
<RMSF> (A/B)
Holo
0.15
0.19
0.17
Binary
0.14
0.25
0.19
Apo
0.19
0.24
0.22
S7. Selected distances and H-bonds
Figure S10. Distance vs. time plot of BPY from selected residues in the binding pocket of the holo form.
Distances between Ser142(Oγ)-BPY(O2), Asn143(Oδ1)-BPY(O1), and Tyr155(Oη)-BPY(O2) are reported
in the left, central and right panel, respectively. Grey lines represent the effective sampling of the distance
during the simulation, black lines are obtained by applying a Fast Fourier Transform filter in order to cut-off
noise.
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Figure S11. Distance vs. time plot of NAD from selected residues in the binding pocket of the holo form.
Distances between Tyr155(Oη)-NAD(O3D) and Lys159(Nζ)-NAD(O2D) are reported in the left and right
panel, respectively. Grey lines represent the effective sampling of the distance during the simulation, black
lines are obtained by applying a Fast Fourier Transform filter in order to cut-off noise.
Figure S12. Distance vs. time plot of the Ser142(Oγ)-Tyr155(Oη) distance in the apo, binary and holo form
(left, central, and right panel, respectively). Grey lines represent the effective sampling of the distance during
the simulation, black lines are obtained by applying a Fast Fourier Transform filter in order to cut-off noise.
Supplementary Information References
[1] F. Neese (2012) WIREs Comput Mol Sci 2:73-78
[2] C. Lee, W. Yang and R. G. Parr (1988) Phys Rev B 37:785-789
[3] A. D. Becke (1993) J Chem Phys 98:5648-5652
[4] W. J. Hehre, R. Ditchfield and J. A. Pople (1972) J Chem Phys 56:2257-2261
[5] S. Dhindwal, D. N. Patil, M. Mohammadi, M. Sylvestre, S. Tomar and P. Kumar (2011) J Biol Chem
286:37011-37022
[6] E. F. Pettersen, T. D. Goddard, C. C. Huang, G. S. Couch, D. M. Greenblatt, E. C. Meng and T. E. Ferrin
(2004) J Comput Chem 25:1605-1612
[7] J. P. Rodrigues, M. Trellet, C. Schmitz, P. Kastritis, E. Karaca, A. S. Melquiond and A. M. Bonvin
(2012) Proteins 80:1810-1817
[8] D. Van Der Spoel, E. Lindahl, B. Hess, G. Groenhof, A. E. Mark and H. J. Berendsen (2005) J Comput
Chem 26:1701-1718
[9] X. Daura, K. Gademann, B. Jaun, D. Seebach, W. F. van Gunsteren and A. E. Mark (1999) Angew Chem
Int Ed 38:236-240
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