% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{Guaitoli:890311,
author = {Guaitoli, Valentina and Alvarez-Ginarte, Yoanna María and
Montero-Cabrera, Luis Alberto and Bencomo-Martínez, Alberto
and Badel, Yoana Pérez and Giorgetti, Alejandro and Suku,
Eda},
title = {{A} computational strategy to understand structure-activity
relationship of 1,3-disubstituted imidazole [1,5-α]
pyrazine derivatives described as {ATP} competitive
inhibitors of the {IGF}-1 receptor related to {E}wing
sarcoma},
journal = {Journal of molecular modeling},
volume = {26},
number = {8},
issn = {0948-5023},
address = {Heidelberg},
publisher = {Springer},
reportid = {FZJ-2021-00884},
pages = {222},
year = {2020},
note = {Unfortunately, the authors do not have a copy of the
submitted version anymore},
abstract = {We followed a comprehensive computational strategy to
understand and eventually predict the structure-activity
relationship ofthirty-three 1,3-disubstituted imidazole
[1,5-α] pyrazine derivatives described as ATP competitive
inhibitors of the IGF-1receptor related to Ewing sarcoma.
The quantitative structure-activity relationship model
showed that the inhibitory potency iscorrelated with the
molar volume, a steric descriptor and the net charge
calculated value on atom C1 (q1) and N4 (q4) of
thepharmacophore, all of them appearing to give a positive
contribution to the inhibitory activity. According to
experimental andcalculated values, the most potent
compoundwould be 3-[4-(azetidin-2-ylmethyl)
cyclohexyl]-1-[3-(benzyloxy) phenyl]
imidazo[1,5-α]pyrazin-8-amine (compound 23). Docking was
used to guess important residues involved in the
ATP-competitive inhibitoryactivity. It was validated by 200
ns of molecular dynamics (MD) simulation using improved
linear interaction energy (LIE)method. MD of previously
preferred structures by docking shows that the most potent
ligand could establish hydrogen bondswith the ATP-binding
site of the receptor, and the Ser979 and Ser1059 residues
contribute favourably to the binding stability ofcompound
23.MDsimulation also gave arguments about the chemical
structure of the compound 23 being able to fit in the
ATPbindingpocket, expecting to remain stable into it during
the entire simulation and allowing us to hint the
significant contributionexpected to be given by
electrostatic and hydrophobic interactions to the
ligand-receptor complex stability. This
computationalcombined strategy here described could
represent a useful and effective prime approach to guide the
identification of tyrosinekinase inhibitors as new lead
compounds.},
cin = {IAS-5 / INM-9},
ddc = {540},
cid = {I:(DE-Juel1)IAS-5-20120330 / I:(DE-Juel1)INM-9-20140121},
pnm = {574 - Theory, modelling and simulation (POF3-574)},
pid = {G:(DE-HGF)POF3-574},
typ = {PUB:(DE-HGF)16},
pubmed = {32748063},
UT = {WOS:000555990300001},
doi = {10.1007/s00894-020-04470-w},
url = {https://juser.fz-juelich.de/record/890311},
}