10 Applications of Molecular Dynamics Simulations …
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to the optimized 13 AFP-complexes. Before the 60 ns production run, the AFPcomplexes were minimized, equilibrated, and heated. During the simulations, the
atomic coordinates of the AFP-complexes were saved in the trajectory file every
10 ps.
The RMSD plot for the protein and ligand was the basis for system dynamic
stability estimation, and the four representative structures are plotted in Fig. 10.7.
The AFP complexes with 2,3,4,5 tetrachloro-4’-biphenylol, DES, and flavanone were
stabilized at the last 10 ns. Binding of α-zearalanol and weak binders (chalcone and
diethyl phthalate) had considerable fluctuations in last 5 ns.
The diethyl phthalate came out of the binding pocket of AFP at 10 ns, indicating
low binding effect. In support of this MD simulation result, Hong et al. experimentally
proved that the diethyl phthalate has a weak binding affinity for AFP [71]. RMSD
analysis of the AFP complexes trajectory files revealed multiple rotatable bonds in
the ligands induced a remarkable conformational change on AFP compared to a rigid
ligand. The ligand binding-induced conformational changes in AFP’s active site were
observed in the last frame of the trajectory files, indicating that MD simulations can
capture ligand binding protein structural changes.
10.6.3 Ligand Binding Interactions of Human α7 Nicotinic
Acetylcholine Receptor
Despite the highly publicized adverse health effects caused by tobacco use, the addiction associated with tobacco product nicotine has led to difficulty in quitting among
users. The neuronal nAChRs play a key role in tobacco addiction. The α7 subtype of
nAChRs is a key receptor in addiction mediation. Worryingly, it is unknown whether
other tobacco constituents (>8000 exist) are addictive or not. Experimentally determining the binding affinity of ~8000 tobacco constituents would be too expensive
and time-consuming to be practical. Instead, in silico methods evaluated the addiction potential of ~8000 tobacco constituents. Due to the absence of an experimental
crystal structure, homology modeling was leveraged to build the 3D structure of the
human α7 nAChR ligand binding domain. The α7 nAChR chimera (PDB ID:3SQ6)
was the template to model human α7 nAChR. When undergoing such modeling, it
is essential to consider the flexibility of the protein in the presence of the ligand
as the target protein can undergo ligand binding driven structural changes which
impact function. Most software packages permit only partial protein flexibility during small molecule docking. Here, a competitive docking model (CDM) overcame
this drawback of rigid protein docking and found the poses of compounds when binding to the homology modeled human α7 nAChR. Compounds experimentally tested
against human α7 nAChR were used to evaluate the ability of the CDM. The model’s
predictions of compound binding in the active site of the human α7 nAChR were
thus experimentally validated. MD simulation was used to investigate the residues
involved in the critical compound interactions. Building on the elucidated key inter-
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to the optimized 13 AFP-complexes. Before the 60 ns production run, the AFPcomplexes were minimized, equilibrated, and heated. During the simulations, the
atomic coordinates of the AFP-complexes were saved in the trajectory file every
10 ps.
The RMSD plot for the protein and ligand was the basis for system dynamic
stability estimation, and the four representative structures are plotted in Fig. 10.7.
The AFP complexes with 2,3,4,5 tetrachloro-4’-biphenylol, DES, and flavanone were
stabilized at the last 10 ns. Binding of α-zearalanol and weak binders (chalcone and
diethyl phthalate) had considerable fluctuations in last 5 ns.
The diethyl phthalate came out of the binding pocket of AFP at 10 ns, indicating
low binding effect. In support of this MD simulation result, Hong et al. experimentally
proved that the diethyl phthalate has a weak binding affinity for AFP [71]. RMSD
analysis of the AFP complexes trajectory files revealed multiple rotatable bonds in
the ligands induced a remarkable conformational change on AFP compared to a rigid
ligand. The ligand binding-induced conformational changes in AFP’s active site were
observed in the last frame of the trajectory files, indicating that MD simulations can
capture ligand binding protein structural changes.
10.6.3 Ligand Binding Interactions of Human α7 Nicotinic
Acetylcholine Receptor
Despite the highly publicized adverse health effects caused by tobacco use, the addiction associated with tobacco product nicotine has led to difficulty in quitting among
users. The neuronal nAChRs play a key role in tobacco addiction. The α7 subtype of
nAChRs is a key receptor in addiction mediation. Worryingly, it is unknown whether
other tobacco constituents (>8000 exist) are addictive or not. Experimentally determining the binding affinity of ~8000 tobacco constituents would be too expensive
and time-consuming to be practical. Instead, in silico methods evaluated the addiction potential of ~8000 tobacco constituents. Due to the absence of an experimental
crystal structure, homology modeling was leveraged to build the 3D structure of the
human α7 nAChR ligand binding domain. The α7 nAChR chimera (PDB ID:3SQ6)
was the template to model human α7 nAChR. When undergoing such modeling, it
is essential to consider the flexibility of the protein in the presence of the ligand
as the target protein can undergo ligand binding driven structural changes which
impact function. Most software packages permit only partial protein flexibility during small molecule docking. Here, a competitive docking model (CDM) overcame
this drawback of rigid protein docking and found the poses of compounds when binding to the homology modeled human α7 nAChR. Compounds experimentally tested
against human α7 nAChR were used to evaluate the ability of the CDM. The model’s
predictions of compound binding in the active site of the human α7 nAChR were
thus experimentally validated. MD simulation was used to investigate the residues
involved in the critical compound interactions. Building on the elucidated key inter-