Benchmarking
is
an
important
step
in
the
improvement,
assessment,
and
comparison
of
performance
drug
discovery
platforms
technologies.
We
revised
existing
benchmarking
protocols
our
Computational
Analysis
Novel
Drug
Opportunities
(CANDO)
multiscale
therapeutic
platform
to
improve
utility
performance.
optimized
multiple
parameters
used
candidate
prediction
assessment
with
these
updated
protocols.
CANDO
ranked
7.4%
known
drugs
top
10
compounds
for
their
respective
diseases/indications
based
on
drug-indication
associations/mappings
obtained
from
Comparative
Toxicogenomics
Database
(CTD)
using
parameters.
This
increased
12.1%
when
mappings
were
Therapeutic
Targets
Database.
Performance
indication
was
weakly
correlated
(Spearman
correlation
coefficient
_>_0.3)
size
(number
associated
indication)
moderately
(correlation
_>_0.5)
compound
chemical
similarity.
There
also
moderate
between
new
original
assessing
per
each
protocol.
results
dependent
source
mapping
used:
a
higher
proportion
indication-associated
recalled
100
(TTD),
which
only
includes
FDA-approved
associations
(in
contrast
CTD,
drawn
literature).
created
compbench,
publicly
available
head-to-head
protocol
that
allows
consistent
different
platforms.
Using
this
protocol,
we
compared
two
pipelines
repurposing
within
CANDO;
primary
pipeline
outperformed
another
similarity-based
still
development
clusters
signatures
Gene
Ontology
terms.
Our
study
sets
precedent
complete,
comprehensive,
comparable
platforms,
resulting
more
accurate
predictions.
Pharmaceutics,
Journal Year:
2024,
Volume and Issue:
16(10), P. 1328 - 1328
Published: Oct. 14, 2024
Artificial
intelligence
(AI)
encompasses
a
broad
spectrum
of
techniques
that
have
been
utilized
by
pharmaceutical
companies
for
decades,
including
machine
learning,
deep
and
other
advanced
computational
methods.
These
innovations
unlocked
unprecedented
opportunities
the
acceleration
drug
discovery
delivery,
optimization
treatment
regimens,
improvement
patient
outcomes.
AI
is
swiftly
transforming
industry,
revolutionizing
everything
from
development
to
personalized
medicine,
target
identification
validation,
selection
excipients,
prediction
synthetic
route,
supply
chain
optimization,
monitoring
during
continuous
manufacturing
processes,
or
predictive
maintenance,
among
others.
While
integration
promises
enhance
efficiency,
reduce
costs,
improve
both
medicines
health,
it
also
raises
important
questions
regulatory
point
view.
In
this
review
article,
we
will
present
comprehensive
overview
AI's
applications
in
covering
areas
such
as
discovery,
safety,
more.
By
analyzing
current
research
trends
case
studies,
aim
shed
light
on
transformative
impact
industry
its
broader
implications
healthcare.
Life,
Journal Year:
2025,
Volume and Issue:
15(1), P. 110 - 110
Published: Jan. 16, 2025
Chemosensation
and
mechanosensation
are
vital
to
insects’
survival
behavior,
shaping
critical
physiological
processes
such
as
feeding,
metabolism,
mating,
reproduction.
During
insects
rely
on
diverse
chemosensory
mechanosensory
receptors
distinguish
between
nutritious
harmful
substances,
enabling
them
select
suitable
food
sources
while
avoiding
toxins.
These
distributed
across
various
body
parts,
allowing
detect
environmental
cues
about
quality
adjust
their
behaviors
accordingly.
A
deeper
understanding
of
insect
sensory
physiology,
especially
during
not
only
enhances
our
knowledge
biology
but
also
offers
significant
opportunities
for
practical
applications.
This
review
highlights
recent
advancements
in
research
feeding-related
receptors,
covering
a
wide
range
species,
from
the
model
organism
Drosophila
melanogaster
agricultural
human
pests.
Additionally,
this
examines
potential
targeting
precision
pest
control.
Disrupting
feeding
reproduction
emerges
promising
strategy
management.
By
interfering
with
these
essential
behaviors,
we
can
effectively
control
populations
minimizing
impacts
promoting
ecological
balance.
Deleted Journal,
Journal Year:
2025,
Volume and Issue:
7(5)
Published: May 14, 2025
Abstract
The
bioactivity
of
phytochemicals
has
been
widely
reported
in
the
literature,
however,
abundance
phytochemical
resources
and
their
potent
activities
require
laborious
screening
methods
for
feasible
applications.
Owing
to
lack
pharmacologically
safe
therapeutic
options
tackle
emerging
infections
drug
resistance,
there
is
an
increasing
interest
diverse
potential
bioactive
phytochemicals.
However,
consolidated
reports
on
same
are
very
limited.
present
article
provides
overview
exemplary
studies
from
last
decade
application
silico
that
have
guided
fast
efficient
domain
pertains
functional
aspects
phytochemicals,
such
as
antibacterial,
antiviral,
antiparasitic,
antifungal,
antioxidant,
anti-inflammatory,
anticancer
effects.
Based
reviewed
computational
approaches,
a
common
popularly
adopted
pipeline
was
illustrated
utility
A
list
databases
provided
help
researchers
identify
phytocompounds
research.
prospect
generating
high
volume
research
data
can
facilitate
machine
learning
artificial
intelligence-based
future
predictions
during
healthcare
emergencies
disease
outbreaks.
