Poultry Science,
Journal Year:
2025,
Volume and Issue:
unknown, P. 104956 - 104956
Published: March 1, 2025
Infectious
bronchitis
virus
(IBV)
is
a
major
pathogen
that
causes
significant
economic
losses
in
the
global
poultry
industry.
Current
vaccination
strategies
provide
only
partial
protection,
highlighting
need
for
more
effective
prevention
and
treatment
methods.
This
study
aimed
to
develop
novel
compound
throat
anti-viral
(CTA)
from
natural
plants
using
data
Traditional
Chinese
Medicine
Inheritance
System
identification
through
liquid
chromatography-mass
spectrometry.
CTA
demonstrated
substantial
anti-IBV
effects
both
vitro
vivo
studies.
In
vitro,
significantly
inhibited
IBV
multiplication
alleviated
pathological
lesions
chicken
embryonic
kidney
cells,
tracheal
rings,
embryos.
vivo,
seven-day
with
obtained
much
milder
clinical
signs,
enhanced
growth
performance,
better
immune
organ
indices
infected
chickens.
Additionally,
reduced
levels
trachea
lungs
increased
specific
antibody
titers.
also
maintained
body
homeostasis,
exhibiting
strong
antioxidant
anti-inflammatory
properties
mitigated
respiratory
tract
damage.
Metabolomics
network
pharmacology
analyses,
revealed
CTA's
antiviral
are
mediated
FoxO
signaling
pathway.
successfully
developed
an
prescription
database
based
on
validated
efficacy
of
comprehensive
experiments.
The
findings
elucidated
mechanisms
action,
particularly
pathway,
highlighted
its
potential
application
as
Frontiers in Pharmacology,
Journal Year:
2024,
Volume and Issue:
14
Published: Jan. 9, 2024
Over
the
past
two
decades,
Next-Generation
Sequencing
(NGS)
has
revolutionized
approach
to
cancer
research.
Applications
of
NGS
include
identification
tumor
specific
alterations
that
can
influence
pathobiology
and
also
impact
diagnosis,
prognosis
therapeutic
options.
Pharmacogenomics
(PGx)
studies
role
inheritance
individual
genetic
patterns
in
drug
response
taken
advantage
technology
as
it
provides
access
high-throughput
data
can,
however,
be
difficult
manage.
Machine
learning
(ML)
recently
been
used
life
sciences
discover
hidden
from
complex
solve
various
PGx
problems.
In
this
review,
we
provide
a
comprehensive
overview
approaches
employed
different
implicating
use
data.
We
an
excursus
ML
algorithms
exert
fundamental
strategies
field
improve
personalized
medicine
cancer.
Journal of Biomolecular Structure and Dynamics,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 17
Published: Jan. 29, 2024
Alzheimer's
disease
(AD)
ranks
as
the
most
prevalent
neurodegenerative
disorder
with
dementia
and
it
accounts
for
more
than
70%
of
all
cases.
Despite
extensive
reporting
on
experimental
investigation
Datura
innoxia
(DI)
its
phytochemical
components
in
treatment
AD,
urgent
need
elucidation
principle
multi-mechanism
multi-level
AD
remains.
In
this
research,
molecular
docking
network
pharmacology
were
used
to
evaluate
active
compounds
targets
DI
AD.
The
obtained
from
Indian
Medicinal
Plants,
Phytochemistry,
Therapeutics
(IMPPAT)
well
Traditional
Chinese
Medicine
System
Pharmacology
(TCMSP)
databases.
screening
includes
28
abundant
Swiss
Target
Prediction
database
was
predict
these
compounds.
GeneCards
collect
AD-related
genes.
Both
imported
into
a
Venn
diagram,
overlapped
genes
identified
potential
anti-AD
targets.
results
showed
that
Dinoxin
B,
Meteloidine,
Scopoline,
Tropic
acid
had
no
effect
Furthermore,
GO
enrichment
analysis
indicates
influences
functions
biological
processes
such
learning
or
memory
modulation
chemical
synaptic
transmission
membrane
raft
microdomain.
KEGG
pathway
revealed
key
pathways
implicated
DI's
actions
include
serotonergic
synapse,
IL-17
signaling
pathway,
AGE-RAGE
diabetic
complications.
Based
STRING
Cytoscape
network-analysis
platforms,
top
ten
core
APP,
CASP3,
IL6,
BACE1,
IL1B,
ACE,
PSEN1,
GAPDH,
GSK3B
ACHE.
dynamic
simulation
two
molecules
against
three
target
proteins
confirmed
strong
binding
affinity
stability
at
docked
site.
Overall,
our
findings
pave
path
further
research
development
optimization
agents
DI.
Frontiers in Chemistry,
Journal Year:
2024,
Volume and Issue:
12
Published: May 31, 2024
Artificial
intelligence
(AI)
has
recently
emerged
as
a
unique
developmental
influence
that
is
playing
an
important
role
in
the
development
of
medicine.
The
AI
medium
showing
potential
unprecedented
advancements
truth
and
efficiency.
intersection
to
revolutionize
drug
discovery.
However,
also
limitations
experts
should
be
aware
these
data
access
ethical
issues.
use
techniques
for
discovery
applications
increased
considerably
over
past
few
years,
including
combinatorial
QSAR
QSPR,
virtual
screening,
Chemical Science,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Jan. 1, 2024
AI-powered
analysis
of
TCM
chemical
data
enhances
component
identification,
drug
discovery,
personalized
treatment,
and
pharmacological
action
elucidation,
driving
the
modernization
sustainable
development
TCM.
Scientific Reports,
Journal Year:
2024,
Volume and Issue:
14(1)
Published: Nov. 16, 2024
In
the
race
to
combat
ever-evolving
diseases,
drug
discovery
process
often
faces
hurdles
of
high-cost
and
time-consuming
procedures.
To
tackle
these
challenges
enhance
efficiency
identifying
new
therapeutic
agents,
we
introduce
VirtuDockDL,
which
is
a
streamlined
Python-based
web
platform
utilizing
deep
learning
for
discovery.
This
pipeline
employs
Graph
Neural
Network
analyze
predict
effectiveness
various
compounds
as
potential
candidates.
During
validation
phase,
VirtuDockDL
was
instrumental
in
non-covalent
inhibitors
against
VP35
protein
Marburg
virus,
critical
target
given
virus's
high
fatality
rate
limited
treatment
options.
Further,
benchmarking,
achieved
99%
accuracy,
an
F1
score
0.992,
AUC
0.99
on
HER2
dataset,
surpassing
DeepChem
(89%
accuracy)
AutoDock
Vina
(82%
accuracy).
Compared
RosettaVS,
MzDOCK,
PyRMD,
outperformed
them
by
combining
both
ligand-
structure-based
screening
with
learning.
While
RosettaVS
excels
accurate
docking
but
lacks
high-throughput
screening,
PyRMD
focuses
ligand-based
methods
without
AI
integration,
offers
superior
predictive
accuracy
full
automation
large-scale
datasets,
making
it
ideal
comprehensive
workflows.
These
results
underscore
tool's
capability
identify
high-affinity
accurately
across
targets,
including
cancer
therapy,
TEM-1
beta-lactamase
bacterial
infections,
CYP51
enzyme
fungal
infections
like
Candidiasis.
sum
up,
combines
user-friendly
interface
design
powerful
computational
capabilities
facilitate
rapid,
cost-effective
development.
The
integration
could
potentially
transform
landscape
pharmaceutical
research,
providing
faster
responses
global
health
challenges.
available
at
https://github.com/FatimaNoor74/VirtuDockDL
.
Research Square (Research Square),
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 9, 2025
AbstractObjective
Exploring
the
preventive
and
therapeutic
effects
of
dapagliflozin
(DAPA)
on
gouty
arthritis
(GA)
in
rats,
revealing
its
potential
mechanism
action.
Methods
Potential
targets
DAPA
were
identified
from
DrugBank,
Swiss
Target
Prediction,
CTD,
PharmMapper
databases.
Targets
associated
with
retrieved
Gene
Cards,
DisGeNET,
NCBI
By
taking
intersection
these
two
sets,
common
GA
determined.
These
then
subjected
to
Ontology
(GO)
functional
annotation
Kyoto
Encyclopedia
Genes
Genomes
(KEGG)
pathway
enrichment
analysis.
Use
CB-DOCK2
online
molecular
docking
platform
dock
core
target
perform
visual
Thirty-two
SPF-grade
male
SD
rats
randomly
divided
into
four
groups,
eight
each:
a
blank
control
group,
model
20
mg/kg
40
group.
Rats
received
daily
gavage
administration
corresponding
medication
for
consecutive
days.
On
fifth
day,
monosodium
urate
(MSU)
crystal
suspension
was
injected
left
ankle
joint
establish
an
acute
model.
Samples
collected
one
hour
after
final
gavage.
The
swelling
joints
recorded
at
various
time
points.
Hematoxylin
eosin
(HE)
staining
used
observe
pathological
changes
synovial
tissue
joints.
Enzyme-linked
immunosorbent
assay
(ELISA)
conducted
measure
levels
inflammatory
cytokines
interleukin-1β
(IL-1β)
tumor
necrosis
factor-α
(TNF-α)
peripheral
blood
rats.
Western
blotting
performed
detect
expression
signaling
proteins
Results
Based
network
pharmacology
analysis
docking,
it
found
that
significantly
enriched
nucleotide
binding
oligomerization
domain
(NOD)-like
receptor
(NLR)
pathway,
energies
between
related
all
<-7.0
kcal/mol.
In
animal
experiments,
regarding
swelling:
compared
group
showed
significant
reduction
72
hours
post-modeling
(p<0.05),
exhibited
reductions
both
48
(p<0.01).
For
HE
staining:
DAPA-treated
groups
varying
degrees
attenuation
damage,
including
cell
infiltration,
proliferation,
vascular
proliferation
Peripheral
ELISA
results:
IL-1β
TNF-α
lower
than
those
(p<0.05).
As
protein
NOD-like
thermal
domain-associated
3
(NLRP3)
cysteinyl
aspartate-specific
proteinase-1
(Caspase-1)
synovium:
NLRP3
Caspase-1
reduced
Conclusion
DAPA
may
alleviate
response
by
inhibiting
NLRP3/Caspase-1
pathway.
International Journal of Applied Pharmaceutics,
Journal Year:
2025,
Volume and Issue:
unknown, P. 51 - 60
Published: Feb. 24, 2025
Objective:
Cancer
involves
uncontrolled
cell
growth
and
spreading
to
other
body
parts.
Lung
cancer
is
the
most
common
deadliest
worldwide,
with
treatments
often
causing
significant
side
effects.
This
research
aims
predict
potential
of
compounds
in
mangosteen
(Garcinia
mangostana
L.)
as
a
candidate
for
lung
therapy.
Methods:
The
methods
used
this
are
network
pharmacology
analysis
using
string
cytoscape,
molecular
docking
deep
learning,
dynamics
simulations.
Results:
Eleven
have
been
identified
Garcinia
L.,
including
catechin,
gartanin,
alpha-mangostin,
norathyriol,
maclurin,
8-deoxygartanin,
beta-mangostin,
gamma-mangostin,
garcinone
A,
B,
D.
Based
on
ADMET
analysis,
these
exhibit
varying
degrees
absorption,
distribution,
metabolism,
excretion,
toxicity
profiles,
which
can
provide
valuable
insights
into
their
therapeutic
applications
safety
profiles.
It
has
protein
targets
AURKA,
PLK1,
CCNA2,
KIF11,
AURKA
chosen
Molecular
revealed
D
binding
energy-10.30
kcal/mol
gamma-Mangostin-10.28
had
better
affinity
than
native
ligand
adenosine-5'-diphosphate-9.00
kcal/mol.
simulations
indicated
that
gamma-Mangostin
were
less
stable
over
100
ns
simulation.
Conclusion:
compounds,
D,
target
cancer-related
demonstrate
affect
key
biological
pathways
such
cycle
motor
proteins.
Deep
learning
shows
gamma-mangostin
high
affinity,
while
confirm
stability
ns.
Mathematics,
Journal Year:
2025,
Volume and Issue:
13(6), P. 961 - 961
Published: March 14, 2025
Complex
dynamics
and
nonlinear
systems
play
a
critical
role
in
industrial
processes,
where
complex
interactions,
high
uncertainty,
external
disturbances
can
significantly
impact
efficiency,
stability,
safety.
In
sectors
such
as
mining,
manufacturing,
energy
networks,
even
small
perturbations
lead
to
unexpected
system
behaviors,
operational
inefficiencies,
or
cascading
failures.
Understanding
controlling
these
is
essential
for
developing
robust,
adaptive,
resilient
systems.
This
study
conducts
systematic
literature
review
covering
2015–2025
Scopus
Web
of
Science,
initially
retrieving
2628
(Scopus)
343
(WoS)
articles.
After
automated
filtering
(Python)
applying
inclusion/exclusion
criteria,
refined
dataset
2900
references
was
obtained,
from
which
89
highly
relevant
studies
were
selected.
The
categorized
into
six
key
areas:
(i)
heat
transfer
with
magnetized
fluids,
(ii)
control,
(iii)
big-data-driven
optimization,
(iv)
transition
via
SOEC,
(v)
fault
detection
control
valves,
(vi)
stochastic
modeling
semi-Markov
switching.
Findings
highlight
the
convergence
robust
machine
learning,
IoT,
Industry
4.0
methodologies
tackling
challenges.
Cybersecurity
sustainability
also
emerge
factors
models,
alongside
barriers
limited
data
availability,
platform
heterogeneity,
interoperability
gaps.
Future
research
should
integrate
multiscale
analysis,
deterministic
chaos,
deep
learning
enhance
adaptability,
security,
efficiency
operations
high-complexity
environments.
