bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2024,
Номер
unknown
Опубликована: Дек. 7, 2024
ABSTRACT
Protein
structure
prediction
via
artificial
intelligence/machine
learning
(AI/ML)
approaches
has
sparked
substantial
research
interest
in
structural
biology
and
adjacent
disciplines.
More
recently,
AlphaFold2
(AF2)
been
adapted
for
the
of
multiple
conformations—beyond
original
scope
predicting
single-state
structures.
This
is
accomplished
by
using
random
seeds
subsampling
sequence
alignment
(MSA).
Research
this
novel
approach
focused
on
proteins
(typically
50
residues
length
or
greater),
while
multi-conformation
shorter
peptides
not
yet
explored
context.
Here,
we
report
AF2-based
conformation
a
total
557
(ranging
from
10
to
40
residues)
benchmark
dataset
with
corresponding
nuclear
magnetic
resonance
(NMR)-determined
conformational
ensembles.
De
novo
predictions
were
accompanied
comparison
analyses
assess
accuracy.
We
found
that
ensembles
AF2
varied
accuracy
versus
NMR
data,
average
root-mean-square
deviation
(RMSD)
among
structured
regions
under
2.5
Å
fluctuation
(RMSF)
differences
1.5
entire
set
peptides.
Our
results
reveal
notable
capabilities
but
also
highlight
considerable
limitations,
underscoring
necessity
interpretation
discretion
need
improved
ensemble
approaches.
Current Opinion in Structural Biology,
Год журнала:
2025,
Номер
90, С. 102980 - 102980
Опубликована: Янв. 15, 2025
Protein-protein
associations
are
often
mediated
by
an
intrinsically
disordered
protein
region
interacting
with
a
folded
domain
in
coupled
binding
and
folding
reaction.
Classic
physical
organic
chemistry
approaches
together
structural
biology
have
shed
light
on
mechanistic
aspects
of
such
reactions.
Further
insight
into
general
principles
may
be
obtained
interpreting
the
results
through
evolutionary
lens.
This
review
attempts
to
provide
overview
how
analysis
reactions
can
benefit
from
approach,
is
aimed
at
scientists
without
background
evolution.
Evolution
constantly
reshapes
existing
proteins
sampling
more
or
less
fit
variants.
Most
new
variants
weeded
out
as
generations
species
come
go
over
hundreds
millions
years.
The
huge
ongoing
genome
sequencing
efforts
provided
us
snapshot
adapted
fit-for-purpose
homologs
thousands
different
organisms.
Comparison
present-day
orthologs
paralogs
highlights
evolution
demonstrate
great
potential
for
operate
regions
modulate
affinity
specificity
interactions.
Molecules,
Год журнала:
2025,
Номер
30(2), С. 242 - 242
Опубликована: Янв. 9, 2025
In
the
field
of
chemical
biology,
DNA
origami
has
been
actively
researched.
This
technique,
which
involves
folding
strands
like
to
assemble
them
into
desired
shapes,
made
it
possible
create
complex
nanometer-sized
structures,
marking
a
major
breakthrough
in
nanotechnology.
On
other
hand,
controlling
mechanisms
and
folded
structures
proteins
or
shorter
peptides
challenging.
However,
recent
advances
techniques
such
as
protein
origami,
peptide
de
novo
design
have
construct
various
nanoscale
functional
molecules.
These
approaches
suggest
emergence
new
molecular
principles,
can
be
termed
"molecular
origami".
this
review,
we
provide
an
overview
research
trends
protein/peptide
DNA/RNA
explore
potential
future
applications
technologies
electrochemical
biosensors.
Ecotoxicology and Environmental Safety,
Год журнала:
2025,
Номер
292, С. 117925 - 117925
Опубликована: Март 1, 2025
This
study
employed
computational
biology
approaches
to
investigate
the
interactions
between
per-
and
polyfluoroalkyl
substances
(PFAS)
key
colorectal
cancer
(CRC)
proteins.
The
results
indicate
that
PFAS
may
influence
CRC
progression
by
modulating
multiple
proteins,
particularly
glutathione
S-transferase
A1
(GSTA1).
Computational
analysis
revealed
14
exhibits
high
binding
affinity
for
GSTA1,
occupying
its
glutathione-binding
site.
Further
simulations
confirmed
stable
of
across
different
environments,
forming
persistent
hydrogen
bonds
water
bridges,
suggesting
a
potential
inhibitory
effect
on
GSTA1.GSTA1,
member
family,
plays
critical
role
in
detoxification
catalyzing
conjugation
electrophilic
compounds.
Dysregulation
GSTA1
has
been
implicated
chemoresistance.
In
CRC,
altered
expression
affect
tumor
metabolism
drug
response,
making
it
therapeutic
target.This
identifies
as
target
interactions,
environmental
exposure
interfering
with
mechanisms.
competitive
inhibition
impact
cell
survival
progression.
Future
research
should
integrate
experimental
validation
assess
phenotypic
effects
evaluate
inhibitor.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2025,
Номер
unknown
Опубликована: Апрель 20, 2025
Abstract
The
GPCR
Dock
competitions
are
a
series
of
community-wide
assessments
computational
structural
modeling
and
ligand
docking
for
G
protein-coupled
receptors,
central
class
drug
targets
in
the
human
proteome.
designed
to
provide
an
unbiased
overview
progress
pinpoint
areas
need
refinement,
thus
shaping
directing
development
methodologies
GPCRs.
In
footsteps
2008,
2010,
2013
assessments,
4
th
round
(GPCR
2021)
featured
five
diverse
challenging
prediction
coincided
with
emergence
AlphaFold,
revolutionary
Artificial
Intelligence
(AI)
technology
protein
structure
from
amino
acid
sequences.
This
report
summarizes
assessment
results
challenges
context
convergent
evolution
experimental
determination
techniques
We
demonstrate
that
thanks
breakthroughs
AI-powered
modeling,
accuracy
modern
models
complexes
peptides
can
not
only
approach
but
also
exceed
low-resolution
structures.
However,
our
highlight
unwavering
high-resolution
determination,
especially
small
molecule
chemicals,
concurrent
application
physics-based
expert-guided
methods.
