PLoS ONE,
Journal Year:
2024,
Volume and Issue:
19(1), P. e0294769 - e0294769
Published: Jan. 4, 2024
Severe
Acute
Respiratory
Syndrome
Corona
Virus
(SARS-CoV-2)
is
the
causative
agent
of
COVID-19
pandemic,
which
has
resulted
in
global
fatalities
since
late
December
2019.
Alkaloids
play
a
significant
role
drug
design
for
various
antiviral
diseases,
makes
them
viable
candidates
treating
COVID-19.
To
identify
potential
agents,
102
known
alkaloids
were
subjected
to
docking
studies
against
two
key
targets
SARS-CoV-2,
namely
spike
glycoprotein
and
main
protease.
The
vital
mediating
viral
entry
into
host
cells,
protease
plays
crucial
replication;
therefore,
they
serve
as
compelling
therapeutic
intervention
combating
disease.
From
selection
alkaloids,
top
6
dual
inhibitory
compounds,
liensinine,
neferine,
isoliensinine,
fangchinoline,
emetine,
acrimarine
F,
emerged
lead
compounds
with
favorable
docked
scores.
Interestingly,
most
shared
bisbenzylisoquinoline
alkaloid
framework
belong
Nelumbo
nucifera,
commonly
lotus
plant.
Docking
analysis
was
conducted
by
considering
active
site
residues
selected
proteins.
stability
three
ligands
receptor
proteins
further
validated
through
dynamic
simulation
analysis.
leads
underwent
ADMET
profiling,
bioactivity
score
analysis,
evaluation
drug-likeness
physicochemical
properties.
Neferine
demonstrated
particularly
strong
affinity
binding,
-7.5025
kcal/mol
-10.0245
glycoprotein,
therefore
interaction
both
target
Of
emetine
fangchinoline
lowest
toxicity
high
LD50
values.
These
may
support
body's
defense
reduce
symptoms
their
numerous
biological
potentials,
even
though
some
properties
naturally
point
direct
nature.
findings
demonstrate
promising
anti-COVID-19
six
making
design.
This
study
will
be
beneficial
effective
discovery
negligible
side
effects.
Signal Transduction and Targeted Therapy,
Journal Year:
2023,
Volume and Issue:
8(1)
Published: Dec. 27, 2023
In
2022,
a
global
outbreak
of
Mpox
(formerly
monkeypox)
occurred
in
various
countries
across
Europe
and
America
rapidly
spread
to
more
than
100
regions.
The
World
Health
Organization
declared
the
be
public
health
emergency
international
concern
due
rapid
virus.
Consequently,
nations
intensified
their
efforts
explore
treatment
strategies
aimed
at
combating
infection
its
dissemination.
Nevertheless,
available
therapeutic
options
for
virus
remain
limited.
So
far,
only
few
numbers
antiviral
compounds
have
been
approved
by
regulatory
authorities.
Given
high
mutability
virus,
certain
mutant
strains
shown
resistance
existing
pharmaceutical
interventions.
This
highlights
urgent
need
develop
novel
drugs
that
can
combat
both
drug
potential
threat
bioterrorism.
Currently,
there
is
lack
comprehensive
literature
on
pathophysiology
Mpox.
To
address
this
issue,
we
conducted
review
covering
physiological
pathological
processes
infection,
summarizing
latest
progress
anti-Mpox
drugs.
Our
analysis
encompasses
currently
employed
clinical
settings,
as
well
newly
identified
small-molecule
antibody
displaying
efficacy
against
Furthermore,
gained
valuable
insights
from
process
development,
including
repurposing
drugs,
discovery
targets
driven
artificial
intelligence,
preclinical
development.
purpose
provide
readers
with
overview
current
knowledge
arXiv (Cornell University),
Journal Year:
2023,
Volume and Issue:
unknown
Published: Jan. 1, 2023
This
paper
presents
a
comprehensive
survey
of
ChatGPT-related
(GPT-3.5
and
GPT-4)
research,
state-of-the-art
large
language
models
(LLM)
from
the
GPT
series,
their
prospective
applications
across
diverse
domains.
Indeed,
key
innovations
such
as
large-scale
pre-training
that
captures
knowledge
entire
world
wide
web,
instruction
fine-tuning
Reinforcement
Learning
Human
Feedback
(RLHF)
have
played
significant
roles
in
enhancing
LLMs'
adaptability
performance.
We
performed
an
in-depth
analysis
194
relevant
papers
on
arXiv,
encompassing
trend
analysis,
word
cloud
representation,
distribution
various
application
The
findings
reveal
increasing
interest
predominantly
centered
direct
natural
processing
applications,
while
also
demonstrating
considerable
potential
areas
ranging
education
history
to
mathematics,
medicine,
physics.
study
endeavors
furnish
insights
into
ChatGPT's
capabilities,
implications,
ethical
concerns,
offer
direction
for
future
advancements
this
field.
Global Transitions,
Journal Year:
2023,
Volume and Issue:
5, P. 50 - 54
Published: Jan. 1, 2023
The
advancement
of
deep
learning
and
artificial
intelligence
has
resulted
in
the
development
state-of-the-art
language
models,
such
as
ChatGPT.
This
technology
can
analyze
large
amounts
data,
identify
patterns,
assist
analysis
understanding
risk
factors
for
diseases.
Despite
its
potential,
applications,
challenges,
ethical
considerations
have
not
been
yet
fully
explored
global
health
research.
paper
examines
applications
ChatGPT
research,
assesses
challenges
use,
proposes
mitigation
strategies.
Additionally,
it
describes
around
use
research
suggests
potential
avenues
addressing
these
issues.
summarizes
that
is
crucial
to
understand
capabilities
limitations
this
order
realize
ensure
responsible
integration
into
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.
Drug Discovery Today,
Journal Year:
2024,
Volume and Issue:
29(6), P. 104009 - 104009
Published: April 30, 2024
AI
techniques
are
making
inroads
into
the
field
of
drug
discovery.
As
a
result,
growing
number
drugs
and
vaccines
have
been
discovered
using
AI.
However,
questions
remain
about
success
these
molecules
in
clinical
trials.
To
address
questions,
we
conducted
first
analysis
pipelines
AI-native
Biotech
companies.
In
Phase
I
find
AI-discovered
an
80–90%
rate,
substantially
higher
than
historic
industry
averages.
This
suggests,
argue,
that
is
highly
capable
designing
or
identifying
with
drug-like
properties.
II
rate
∼40%,
albeit
on
limited
sample
size,
comparable
to
Our
findings
highlight
early
signs
potential
for
molecules.
Journal of Translational Medicine,
Journal Year:
2024,
Volume and Issue:
22(1)
Published: April 30, 2024
Abstract
Upon
a
diagnosis,
the
clinical
team
faces
two
main
questions:
what
treatment,
and
at
dose?
Clinical
trials'
results
provide
basis
for
guidance
support
official
protocols
that
clinicians
use
to
base
their
decisions.
However,
individuals
do
not
consistently
demonstrate
reported
response
from
relevant
trials.
The
decision
complexity
increases
with
combination
treatments
where
drugs
administered
together
can
interact
each
other,
which
is
often
case.
Additionally,
individual's
treatment
varies
changes
in
condition.
In
practice,
drug
dose
selection
depend
significantly
on
medical
protocol
team's
experience.
As
such,
are
inherently
varied
suboptimal.
Big
data
Artificial
Intelligence
(AI)
approaches
have
emerged
as
excellent
decision-making
tools,
but
multiple
challenges
limit
application.
AI
rapidly
evolving
dynamic
field
potential
revolutionize
various
aspects
of
human
life.
has
become
increasingly
crucial
discovery
development.
enhances
across
different
disciplines,
such
medicinal
chemistry,
molecular
cell
biology,
pharmacology,
pathology,
practice.
addition
these,
contributes
patient
population
stratification.
need
healthcare
evident
it
aids
enhancing
accuracy
ensuring
quality
care
necessary
effective
treatment.
pivotal
improving
success
rates
increasing
significance
discovery,
development,
trials
underscored
by
many
scientific
publications.
Despite
numerous
advantages
AI,
advancing
Precision
Medicine
(PM)
remote
monitoring,
unlocking
its
full
requires
addressing
fundamental
concerns.
These
concerns
include
quality,
lack
well-annotated
large
datasets,
privacy
safety
issues,
biases
algorithms,
legal
ethical
challenges,
obstacles
related
cost
implementation.
Nevertheless,
integrating
medicine
will
improve
diagnostic
outcomes,
contribute
more
efficient
delivery,
reduce
costs,
facilitate
better
experiences,
making
sustainable.
This
article
reviews
applications
development
sustainable,
highlights
limitations
applying
AI.
