ACS Macro Letters,
Journal Year:
2023,
Volume and Issue:
12(8), P. 1045 - 1051
Published: July 13, 2023
We
report
the
use
of
l-aspartic
acid
chiral
ionic
hydrogen
bonds
to
drive
liquid-liquid
phase
separation
(LLPS)
and
precision
two-dimensional
electrostatic
self-assembly
in
photo-RAFT
aqueous
polymerization-induced
(photo-PISA).
Homopolymerization
can
yield
salt-resistant,
3
nm
ultrafine
fibril-structured
5
ultrathin
lamellae
via
LLPS,
a
left-to-right-handed
chirality
transition,
droplets-to-lamellae
transition.
Like-charge
block
copolymerization
leads
supercharged
yet
identical
lamellae,
also,
left-to-right
transition
Ultrafine
structures
maintain
intactness
upon
seeded
polymerization
oppositely
charged
monomer.
This
work
demonstrates
that
amino
are
powerful
for
synthesis
salt-resistant
membrane
nanomaterials.
Science Advances,
Journal Year:
2023,
Volume and Issue:
9(29)
Published: July 21, 2023
Affinity-based
biosensing
can
enable
point-of-care
diagnostics
and
continuous
health
monitoring,
which
commonly
follows
bottom-up
approaches
is
inherently
constrained
by
bioprobes'
intrinsic
properties,
batch-to-batch
consistency,
stability
in
biofluids.
We
present
a
biomimetic
top-down
platform
to
circumvent
such
difficulties
combining
"dual-monolayer"
biorecognition
construct
with
graphene-based
field-effect-transistor
arrays.
The
adopts
redesigned
water-soluble
membrane
receptors
as
specific
sensing
units,
positioned
two-dimensional
crystalline
S-layer
proteins
dense
antifouling
linkers
guiding
their
orientations.
Hundreds
of
transistors
provide
statistical
significance
from
transduced
signals.
System
feasibility
was
demonstrated
rSbpA-ZZ/CXCR4QTY-Fc
combination.
Nature-like
interactions
were
achieved
toward
CXCL12
ligand
HIV
coat
glycoprotein
physiologically
relevant
concentrations,
without
notable
sensitivity
loss
100%
human
serum.
regeneratable
acidic
buffer,
allowing
device
reuse
functional
tuning.
modular
generalizable
architecture
behaves
similarly
natural
systems
but
gives
electrical
outputs,
enables
fabrication
multiplex
sensors
tailored
receptor
panels
for
designated
diagnostic
purposes.
bioRxiv (Cold Spring Harbor Laboratory),
Journal Year:
2023,
Volume and Issue:
unknown
Published: May 9, 2023
Abstract
De
novo
design
of
complex
protein
folds
using
solely
computational
means
remains
a
significant
challenge.
Here,
we
use
robust
deep
learning
pipeline
to
and
soluble
analogues
integral
membrane
proteins.
Unique
topologies,
such
as
those
from
GPCRs,
are
not
found
in
the
proteome
demonstrate
that
their
structural
features
can
be
recapitulated
solution.
Biophysical
analyses
reveal
high
thermal
stability
designs
experimental
structures
show
remarkable
accuracy.
The
were
functionalized
with
native
motifs,
standing
proof-of-concept
for
bringing
functions
proteome,
potentially
enabling
new
approaches
drug
discovery.
In
summary,
designed
topologies
enriched
them
functionalities
proteins,
success
rates,
leading
de
facto
expansion
functional
fold
space.
Computational and Structural Biotechnology Journal,
Journal Year:
2024,
Volume and Issue:
23, P. 1214 - 1225
Published: March 15, 2024
Rapid
advancements
in
protein
sequencing
technology
have
resulted
gaps
between
proteins
with
identified
sequences
and
those
mapped
structures.
Although
sequence-based
predictions
offer
insights,
they
can
be
incomplete
due
to
the
absence
of
structural
details.
Conversely,
structure-based
methods
face
challenges
respect
newly
sequenced
proteins.
The
AlphaFold
Multimer
has
remarkable
accuracy
predicting
structure
complexes.
However,
it
cannot
distinguish
whether
input
interact.
Nonetheless,
by
analyzing
information
models
predicted
Multimer,
we
propose
a
highly
accurate
method
for
interactions.
This
study
focuses
on
use
deep
neural
networks,
specifically
analyze
complex
structures
Multimer.
By
transforming
atomic
coordinates
utilizing
sophisticated
image-processing
techniques,
vital
3D
details
were
extracted
from
Recognizing
significance
evaluating
residue
distances
interactions,
this
leveraged
image
recognition
approaches
integrating
Densely
Connected
Convolutional
Networks
(DenseNet)
Deep
Residual
Network
(ResNet)
within
convolutional
networks
analysis.
When
benchmarked
against
leading
protein-protein
interaction
prediction
methods,
such
as
SpeedPPI,
D-script,
DeepTrio,
PEPPI,
our
proposed
method,
named
SpatialPPI,
exhibited
notable
efficacy,
emphasizing
promising
role
spatial
processing
advancing
realm
biology.
SpatialPPI
code
is
available
at:
https://github.com/ohuelab/SpatialPPI.
Proceedings of the National Academy of Sciences,
Journal Year:
2024,
Volume and Issue:
121(14)
Published: March 18, 2024
Heparins
have
been
invaluable
therapeutic
anticoagulant
polysaccharides
for
over
a
century,
whether
used
as
unfractionated
heparin
or
low
molecular
weight
(LMWH)
derivatives.
However,
production
by
extraction
from
animal
tissues
presents
multiple
challenges,
including
the
risk
of
adulteration,
contamination,
prion
and
viral
impurities,
limited
supply,
insecure
supply
chain,
significant
batch-to-batch
variability.
The
use
animal-derived
also
raises
ethical
religious
concerns,
well
carries
transmitting
zoonotic
diseases.
Chemoenzymatic
synthesis
animal-free
products
would
offer
several
advantages,
reliable
scalable
processes,
improved
purity
consistency,
ability
to
produce
with
weight,
structural,
functional
properties
equivalent
those
United
States
Pharmacopeia
(USP)
heparin,
currently
only
sourced
porcine
intestinal
mucosa.
We
report
process
bioengineered
that
is
biologically
compositionally
similar
USP
heparin.
This
relies
on
enzymes
biosynthetic
pathway,
immobilized
an
inert
support
requires
tailored
N
-sulfoheparosan
-sulfo
levels
heparins.
conversion
our
into
LMWH
enoxaparin.
Ultimately,
we
demonstrate
major
advances
provide
potential
clinical
sustainable
alternative
porcine-derived
products.
Journal of Chemical Information and Modeling,
Journal Year:
2024,
Volume and Issue:
64(8), P. 2933 - 2940
Published: March 26, 2024
DeepKa
is
a
deep-learning-based
protein
pKa
predictor
proposed
in
our
previous
work.
In
this
study,
web
server
was
developed
that
enables
online
prediction
driven
by
DeepKa.
The
provides
user-friendly
interface
where
single
step
of
entering
valid
PDB
code
or
uploading
format
file
required
to
submit
job.
Two
case
studies
have
been
attached
order
explain
how
pKa's
calculated
the
could
be
utilized
users.
Finally,
combining
with
post
processing
as
described
studies,
work
suggests
quick
workflow
investigating
relationship
between
structure
and
function
are
pH
dependent.
freely
available
at
http://www.computbiophys.com/DeepKa/main.
ACS Sustainable Chemistry & Engineering,
Journal Year:
2024,
Volume and Issue:
12(27), P. 10118 - 10129
Published: June 25, 2024
Plant
protein-based
nanofibers
generated
by
eco-friendly
waterborne
electrospinning
are
emerging
as
sustainable
and
innovative
materials
with
vast
applications
in
different
biomedical
areas.
In
this
study,
we
fabricated
electrospun
based
on
potato,
pea,
soy
protein
isolates,
achieving
remarkably
high
content
without
the
use
of
organic
solvents,
strong
bases,
or
surfactants.
The
were
characterized
means
quantitative
fluorescence
imaging,
optical
spectroscopy,
dynamic
mechanical
analysis.
Results
indicated
that
intrinsic
nature
proteins
modulated
properties
terms
morphology,
fingerprints,
strength,
stability
aqueous
environments.
Pea
both
rich
β-structure,
led
to
formation
robust
dense
nanofibers,
which
slowly
disintegrated
water.
On
contrary,
less
highly
soluble
from
structurally
more
flexible
potato
isolate,
these
demonstrated
lower
resistance
breakage.
Our
findings
indicate
importance
structural
elements
when
designing
specific
features.
Deciphering
intricate
relationship
between
structure
at
molecular
level
nanofiber
holds
promise
for
development
biomaterials
enhanced
efficacy
diverse
applications.
Frontiers in Molecular Biosciences,
Journal Year:
2023,
Volume and Issue:
10
Published: Aug. 7, 2023
Antibody-based
biotherapeutics
have
emerged
as
a
successful
class
of
pharmaceuticals
despite
significant
challenges
and
risks
to
their
discovery
development.
This
review
discusses
the
most
frequently
encountered
hurdles
in
research
development
(R&D)
antibody-based
proposes
conceptual
framework
called
biopharmaceutical
informatics.
Our
vision
advocates
for
syncretic
use
computation
experimentation
at
every
stage
biologic
drug
discovery,
considering
developability
(manufacturability,
safety,
efficacy,
pharmacology)
potential
candidates
from
earliest
stages
phase.
The
computational
advances
recent
years
allow
more
precise
formulation
disease
concepts,
rapid
identification,
validation
targets
suitable
therapeutic
intervention
that
can
agonize
or
antagonize
them.
Furthermore,
methods
