Pharmaceuticals,
Journal Year:
2024,
Volume and Issue:
17(10), P. 1283 - 1283
Published: Sept. 27, 2024
As
a
primary
source
of
mortality
and
disability,
bacterial
infections
continue
to
develop
severe
threat
humanity.
Nuclear
medicine
imaging
(NMI)
is
known
for
its
promising
potential
diagnose
deep-seated
infections.
This
work
aims
new
technetium-99m
(
Chemistry & Biodiversity,
Journal Year:
2023,
Volume and Issue:
20(8)
Published: June 29, 2023
In
this
study,
twenty
new
anthranilic
acid
hydrazones
6-9
(a-e)
were
synthesized
and
their
structures
characterized
by
Fourier-transform
Infrared
(FT-IR),
Nuclear
Magnetic
Resonance
(1
H-NMR
-
13
C-NMR),
High-resolution
Mass
Spectroscopy
(HR-MS).
The
inhibitory
effects
of
the
compounds
against
COX-II
evaluated.
IC50
values
found
in
range
>200-0.32
μM
6e,
8d,
8e,
9b,
9c,
9e
determined
to
be
most
effective
inhibitors.
Cytotoxic
potent
investigated
human
hepatoblastoma
(Hep-G2)
healthy
embryonic
kidney
(Hek-293)
cell
lines.
Doxorubicin
(IC50
:
8.68±0.16
for
Hep-G2,
55.29±0.56
Hek-293)
was
used
as
standard.
8e
is
active
compound,
with
low
Hep-G2
(4.80±0.04
μM),
high
Hek-293
(159.30±3.12),
selectivity
(33.15).
Finally,
molecular
docking
dynamics
studies
performed
understand
ligand-protein
interactions
between
COX
II,
Epidermal
Growth
Factor
Receptor
(EGFR),
Transforming
beta
II
(TGF-βII).
scores
calculated
-10.609--6.705
kcal/mol
COX-II,
-8.652--7.743
EGFR,
-10.708--8.596
TGF-βII.
Frontiers in Pharmacology,
Journal Year:
2023,
Volume and Issue:
14
Published: June 21, 2023
Background:Sarcocephalus
pobeguinii
(Hua
ex
Pobég)
is
used
in
folk
medicine
to
treat
oxidative-stress
related
diseases,
thereby
warranting
the
investigation
of
its
anticancer
and
anti-inflammatory
properties.
In
our
previous
study,
leaf
extract
S.
induced
significant
cytotoxic
effect
against
several
cancerous
cells
with
high
selectivity
indexes
towards
non-cancerous
cells.
Aim:
The
current
study
aims
isolate
natural
compounds
from
pobeguinii,
evaluate
their
cytotoxicity,
effects
as
well
searching
for
potential
target
proteins
bioactive
compounds.
Methods:
Natural
were
isolated
leaf,
fruit
bark
extracts
chemical
structures
elucidated
using
appropriate
spectroscopic
methods.
antiproliferative
was
determined
on
four
human
(MCF-7,
HepG2,
Caco-2
A549
cells)
Vero
Additionally,
activity
these
by
evaluating
nitric
oxide
(NO)
production
inhibitory
15-lipoxygenase
(15-LOX)
activity.
Furthermore,
molecular
docking
studies
carried
out
six
putative
found
common
signaling
pathways
inflammation
cancer.
Results:
Hederagenin
(2),
quinovic
acid
3-O-[α-D-quinovopyranoside]
(6)
3-O-[β-D-quinovopyranoside]
(9)
exhibited
all
cells,
they
apoptosis
MCF-7
increasing
caspase-3/-7
showed
highest
efficacy
poor
(except
cells;
while
(2)
safety
a
chemotherapeutic
agent.
Moreover,
significantly
inhibited
NO
LPS-stimulated
RAW
264.7
which
could
mainly
be
attributed
effect.
Besides,
mixture
nauclealatifoline
G
naucleofficine
D
(1),
hederagenin
chletric
(3)
active
15-LOX
compared
quercetin.
Docking
results
that
JAK2
COX-2,
binding
scores,
are
targets
involved
Conclusion:
Overall,
selectively
killed
cancer
additional
effect,
most
prominent
lead
compound
may
further
investigated
drug
candidate
tackle
progression.
Advances in computational intelligence and robotics book series,
Journal Year:
2025,
Volume and Issue:
unknown, P. 141 - 168
Published: March 7, 2025
The
pharmaceutical
industry
has
seen
a
create
powerful
in
data
digitization
past
few
years.
However,
challenge
of
gathering,
evaluating,
and
utilizing
knowledge
to
solve
complicated.
Pharmaceutical
problems
arises
with
digitalization.
This
encourages
the
usage
AI,
which
can
handle
vast
amounts
for
drug
target
interactions
greater
efficiency.
Artificial
intelligence
(AI)
is
technology-based
system
that
uses
variety
advanced
tools
networks
simulate
Drug
Discovery
Design.
At
same
time,
it
does
not
pose
complete
threats
human
physical
presence.
chapter
emphasizes
importance
artificial
sector,
including
research
development,
medication
repurposing,
enhancing
productivity,
clinical
trials
its
current
future
applications
discovery
development.
To
address
these
problems,
deep
learning
be
used
generate
new
compounds
by
selecting
molecules
from
known
distribution
then
designing
fundamental