Chemosensitization and Molecular Docking Assessment of Dio-NPs on Resistant Breast Cancer Cells to Tamoxifen
Pharmaceuticals,
Journal Year:
2025,
Volume and Issue:
18(4), P. 452 - 452
Published: March 23, 2025
Background:
Diosgenin,
a
powerful
compound
found
in
fenugreek
and
Dioscorea
villosa,
has
diverse
pharmacological
effects.
This
study
examines
the
anticancer
potential
of
diosgenin
nanoparticles
(Dio-NPs)
against
DMBA-induced
breast
cancer
mice
combination
with
tamoxifen.
Methods:
In
current
investigation,
characterization
Dio-NPs
was
performed,
including
their
size,
shape,
zeta
potential,
UV-vis,
FT-IR
spectra.
(120
mg/kg)
tamoxifen
(2
were
given
to
cancer,
either
alone
or
combination,
over
4
weeks.
We
measured
inflammatory
oxidative
stress
markers,
as
well
gene
expressions
related
apoptosis,
using
ELISA
qRT-PCR.
Additionally,
molecular
docking
studies
conducted
assess
binding
affinity
specific
proteins.
Molecular
dynamics
simulations
on
CDK4,
AKT,
CDK6
proteins
GROMACS.
The
systems
solved,
neutralized,
equilibrated
under
NVT
NPT
ensembles.
Simulations
ran
for
100
ns,
trajectories
analyzed
RMSD,
RMSF,
RG,
SASA,
hydrogen
bonds.
Results:
IC50
MCF-7
cells
47.96
±
1.48
µg/mL.
had
−21.8
0.6
mV
size
56.85
3.19
nm
uniform
spherical.
LD50
2400
mg/kg.
DMBA
exposure
increased
WBCs,
stress,
expression
CDK2,
CDK6,
Akt,
while
reducing
Hb%,
RBCs,
PLTs,
GSH,
superoxide
dismutase,
catalase
levels.
tamoxifen,
both
combined,
significantly
reduced
these
treatment
more
effective
than
individual
treatments.
Histological
analyses
supported
findings.
showed
stronger
target
compared
revealed
that
effectively
binds
maintaining
stability
structural
integrity.
consistent
SASA
values,
moderate
flexibility
stable
bonding
patterns,
suggesting
therapeutic
targets.
Conclusions:
Combining
inhibits
progression
DMBA-treated
mice.
is
primarily
due
reduction
Akt
proteins,
which
enhances
sensitivity
resistant
Language: Английский
NAD_MCNN: Combining Protein Language Models and Multiwindow Convolutional Neural Networks for Deacetylase NAD+ Binding Site Prediction
Van‐The Le,
No information about this author
Yuchen Liu,
No information about this author
Yan‐Yun Chang
No information about this author
et al.
Chemical Biology & Drug Design,
Journal Year:
2025,
Volume and Issue:
105(4)
Published: April 1, 2025
Sirtuins,
a
class
of
NAD+
-dependent
deacetylases,
play
key
role
in
aging,
metabolism,
and
longevity.
Their
interaction
with
at
the
catalytic
site
is
crucial
for
function,
but
experimental
methods
to
map
binding
sites
are
time
consuming.
To
address
this,
we
developed
computational
method
integrating
pretrained
protein
language
models
multiwindow
convolutional
neural
networks
(CNNs).
This
captures
sequence
information
diverse
local
patterns,
achieving
state-of-the-art
performance,
AUC
0.9733
human
sirtuin
proteins
0.9701
other
NAD-dependent
deacylation
enzymes.
These
findings
offer
insights
into
sirtuins
aging
their
broader
biological
functions
while
providing
new
path
identifying
therapeutic
targets
aging-related
diseases.
Language: Английский