BioMedInformatics,
Journal Year:
2023,
Volume and Issue:
3(1), P. 54 - 72
Published: Jan. 11, 2023
Protein
three-dimensional
structural
analysis
using
artificial
intelligence
is
attracting
attention
in
various
fields,
such
as
the
estimation
of
vaccine
structure
and
stability.
In
particular,
when
spike
protein
vaccines,
major
issues
construction
SARS-CoV-2
vaccines
are
their
weak
abilities
to
attack
virus
elicit
immunity
for
a
short
period.
Structural
information
about
new
viruses
essential
understanding
properties
creating
effective
vaccines.
However,
determining
through
experiments
lengthy
laborious
process.
Therefore,
computational
approach
accelerated
elucidation
process
made
predictions
more
accurate.
Using
advanced
machine
learning
technology
called
deep
neural
networks,
it
has
become
possible
predict
structures
directly
from
gene
sequences.
We
summarize
advances
antiviral
therapy
with
extracellular
vesicles
via
analysis.
Soil
microbiota
plays
crucial
roles
in
maintaining
the
health,
productivity,
and
nutrient
cycling
of
terrestrial
ecosystems.
The
persistence
prevalence
heterocyclic
compounds
soil
pose
significant
risks
to
health.
However,
understanding
links
between
microbial
responses
remains
challenging
due
complexity
communities
their
various
chemical
structures.
This
study
developed
a
machine-learning
approach
that
integrates
properties
structures
with
diversity
bacteria
functions
predict
impact
on
community
improve
design
eco-friendly
compounds.
We
screened
key
compounds─particularly
those
topological
polar
surface
areas
(<74.2
Å2
or
111.3–154.1
Å2),
carboxyl
groups,
dissociation
constant,
which
maintained
high
bacterial
functions,
revealing
threshold
effects
where
specific
structural
parameters
dictated
responses.
These
stabilize
increase
beneficial
carbon
nitrogen
cycle
functions.
By
applying
these
parameters,
we
quantitatively
assessed
eco-friendliness
scores
811
compounds,
providing
robust
foundation
for
guiding
future
applications.
Our
disentangles
critical
structure-related
influence
establishes
computational
framework
designing
ecological
benefits
from
an
perspective.
Chemical Biology & Drug Design,
Journal Year:
2022,
Volume and Issue:
100(5), P. 699 - 721
Published: Aug. 25, 2022
Application
of
materials
capable
energy
harvesting
to
increase
the
efficiency
and
environmental
adaptability
is
sometimes
reflected
in
ability
discovery
some
traces
an
environment-either
experimentally
or
computationally-to
enlarge
practical
application
window.
The
emergence
computational
methods,
particularly
computer-aided
drug
(CADD),
provides
ample
opportunities
for
rapid
development
unprecedented
drugs.
expensive
time-consuming
process
traditional
no
longer
feasible,
nowadays
identification
potential
candidates
much
easier
therapeutic
targets
through
elaborate
silico
approaches,
allowing
prediction
toxicity
drugs,
such
as
repositioning
(DR)
chemical
genomics
(chemogenomics).
Coronaviruses
(CoVs)
are
cross-species
viruses
that
able
spread
expeditiously
from
into
new
host
species,
which
turn
cause
epidemic
diseases.
In
this
sense,
review
furnishes
outline
strategies
their
applications
discovery.
A
special
focus
placed
on
chemogenomics
DR
unique
emerging
system-based
disciplines
CoV
target
model
protein
networks
against
a
library
compounds.
Furthermore,
demonstrate
advantages
CADD
methods
rapidly
finding
deadly
virus,
numerous
examples
recent
achievements
grounded
molecular
docking,
chemogenomics,
reported,
analyzed,
interpreted
detail.
It
believed
outcome
assists
developers
systems
detection
future
unexpected
kinds
CoVs
other
variants.
Pharmaceuticals,
Journal Year:
2023,
Volume and Issue:
16(4), P. 604 - 604
Published: April 17, 2023
Hyperpigmentation
can
occur
in
abnormal
skin
conditions
such
as
melanomas,
well
including
melasma,
freckles,
age
spots,
seborrheic
keratosis,
and
café-au-lait
spots
(flat
brown
spots).
Thus,
there
is
an
increasing
need
for
the
development
of
depigmenting
agents.
We
aimed
to
repurpose
anticoagulant
drug
effective
ingredient
against
hyperpigmentation
apply
cosmeceutical
In
present
study,
anti-melanogenic
effects
two
drugs,
acenocoumarol
warfarin,
were
investigated.
The
results
showed
that
both
warfarin
did
not
cause
any
cytotoxicity
resulted
a
significant
reduction
intracellular
tyrosinase
activity
melanin
content
B16F10
melanoma
cells.
Additionally,
inhibits
expression
melanogenic
enzymes
tyrosinase,
tyrosinase-related
protein
(TRP)-1,
TRP-2,
suppressing
synthesis
through
cAMP-dependent,
kinase
(PKA)-dependent
downregulation
microphthalmia-associated
transcription
factor
(MITF),
master
melanogenesis.
Furthermore,
exerted
by
p38
JNK
signaling
pathway
upregulation
extracellular
signal-regulated
(ERK)
phosphatidylinositol
3
(PI3K)/protein
B
(Akt)/glycogen
kinase-3β
(GSK-3β)
cascades.
addition,
β-catenin
cell
cytoplasm
nucleus
was
increased
phosphorylated
(p-β-catenin
content).
Finally,
we
tested
potential
topical
applications
conducting
primary
human
irritation
tests.
Acenocoumarol
induce
adverse
reactions
during
these
Based
on
results,
it
be
concluded
regulates
melanogenesis
various
pathways
PKA,
MAPKs,
PI3K/Akt/GSK-3β,
β-catenin.
These
findings
suggest
has
repurposed
treating
symptoms
could
provide
new
insights
into
therapeutic
approaches
disorders.
Journal of Hazardous Materials,
Journal Year:
2024,
Volume and Issue:
466, P. 133470 - 133470
Published: Jan. 10, 2024
Quaternary
ammonium
compounds
(QACs)
are
commonly
used
as
disinfectants
for
industrial,
medical,
and
residential
applications.
However,
adverse
health
outcomes
have
been
reported.
Therefore,
biocompatible
must
be
developed
to
reduce
these
effects.
In
this
context,
QACs
with
various
alkyl
chain
lengths
(C12–C18)
were
synthesized
by
reacting
the
counterion
silane.
The
antimicrobial
activities
of
novel
against
four
strains
microorganisms
assessed.
Several
in
vivo
assays
conducted
on
Drosophila
melanogaster
determine
toxicological
Si-QACs,
followed
computational
analyses
(molecular
docking,
simulation,
prediction
skin
sensitization).
results
combined
using
a
cheminformatics
approach
understand
descriptors
responsible
safety
Si-QAC.
Si-QAC-2
was
active
all
tested
bacteria,
minimal
inhibitory
concentrations
ranging
from
13.65
436.74
ppm.
exposed
moderate-to-low
outcomes.
molecular
weight,
hydrophobicity/lipophilicity,
electron
diffraction
properties
identified
crucial
ensuring
Si-QACs.
Furthermore,
exhibited
good
stability
notable
antiviral
potential
no
signs
sensitization.
Overall,
(C14)
has
disinfectant.
Journal of Biomolecular Structure and Dynamics,
Journal Year:
2024,
Volume and Issue:
unknown, P. 1 - 29
Published: Jan. 29, 2024
The
emergence
of
new
SARS-CoV-2
variants
has
raised
concerns
about
the
effectiveness
COVID-19
vaccines.
To
address
this
challenge,
small-molecule
antivirals
have
been
proposed
as
a
crucial
therapeutic
option.
Among
potential
targets
for
anti-COVID-19
therapy,
main
protease
(Mpro)
is
important
due
to
its
essential
role
in
virus's
life
cycle
and
high
conservation.
substrate-binding
region
core
proteases
various
coronaviruses,
including
SARS-CoV-2,
SARS-CoV,
Middle
East
respiratory
syndrome
coronavirus
(MERS-CoV),
could
be
used
generation
inhibitors.
Various
drug
discovery
methods
employed
diverse
range
strategies,
targeting
both
monomeric
dimeric
forms,
repurposing,
integrating
virtual
screening
with
high-throughput
(HTS),
structure-based
design,
each
demonstrating
varying
levels
efficiency.
Covalent
inhibitors,
such
Nirmatrelvir
MG-101,
showcase
robust
high-affinity
binding
Mpro,
exhibiting
stable
interactions
confirmed
by
molecular
docking
studies.
Development
effective
antiviral
drugs
imperative
pandemic
situations.
This
review
explores
recent
advances
search
Mpro
inhibitors
application
artificial
intelligence
(AI)
design.
AI
leverages
vast
datasets
advanced
algorithms
streamline
design
identification
promising
AI-driven
methods,
docking,
predictive
modeling,
are
at
forefront
identifying
candidates
therapy.
In
time
when
potentially
threat
global
health,
quest
potent
solutions
critical
inhibiting
virus.
