Utility of binding protein fusions to immunoglobulin heavy chain constant regions from mammalian and avian species
Ningyu Zhu,
No information about this author
Philip M. Smallwood,
No information about this author
John C. Williams
No information about this author
et al.
Journal of Biological Chemistry,
Journal Year:
2025,
Volume and Issue:
unknown, P. 108324 - 108324
Published: Feb. 1, 2025
Language: Английский
CHO-S expression of a novel human recombinant IgG1 of anti-ALD antibody isolated by phage mutation display
Guilin Li,
No information about this author
Jiazhen Liu,
No information about this author
Zhenzhen Guan
No information about this author
et al.
Journal of Immunological Methods,
Journal Year:
2025,
Volume and Issue:
unknown, P. 113843 - 113843
Published: Feb. 1, 2025
Language: Английский
Advances in next-generation sequencing (NGS) applications in drug discovery and development
Huihong Wang,
No information about this author
Jiale Huang,
No information about this author
Xianfu Fang
No information about this author
et al.
Expert Opinion on Drug Discovery,
Journal Year:
2025,
Volume and Issue:
unknown
Published: March 18, 2025
Drug
discovery
is
a
complex
and
multifaceted
process
driven
by
scientific
innovation
advanced
technologies.
Next-Generation
Sequencing
(NGS)
platforms,
encompassing
both
short-read
long-read
technologies,
have
revolutionized
the
field
enabling
high-throughput
cost-effective
analysis
of
DNA
RNA
molecules.
Continuous
advancements
in
NGS-based
technologies
enabled
their
seamless
integration
across
preclinical
clinical
workflows
drug
discovery,
early-stage
target
identification,
candidate
selection,
genetically
stratified
trials,
pharmacogenetic
studies.
This
review
provides
an
overview
current
potential
applications
development
process,
including
roles
novel
screening,
medication
The
based
on
literature
retrieval
from
PubMed
Web
Science
databases
between
2018
2024.
As
advance
rapidly,
NGS
enhances
accuracy
generates
vast
datasets.
These
datasets
are
extensively
integrated
with
other
heterogeneous
data
systems
biology
mined
using
machine
learning
to
extract
significant
insights,
thereby
driving
progress
discovery.
Language: Английский
Enhancing Enzyme Commission Number Prediction With Contrastive Learning and Agent Attention
Wendi Zhao,
No information about this author
Qiaoling Han,
No information about this author
Fan Yang
No information about this author
et al.
Proteins Structure Function and Bioinformatics,
Journal Year:
2025,
Volume and Issue:
unknown
Published: April 2, 2025
The
accurate
prediction
of
enzyme
function
is
crucial
for
elucidating
disease
mechanisms
and
identifying
drug
targets.
Nevertheless,
existing
commission
(EC)
number
methods
are
limited
by
database
coverage
the
depth
sequence
information
mining,
hindering
efficiency
precision
annotation.
Therefore,
this
study
introduces
ProteEC-CLA
(Protein
EC
model
with
Contrastive
Learning
Agent
Attention).
utilizes
contrastive
learning
to
construct
positive
negative
sample
pairs,
which
not
only
enhances
feature
extraction
but
also
improves
utilization
unlabeled
data.
This
process
helps
learn
differences
in
features,
thereby
enhancing
its
ability
predict
function.
Integrating
pre-trained
protein
language
ESM2,
generates
informative
embeddings
deep
functional
correlation
analysis,
significantly
accuracy.
With
incorporation
Attention
mechanism,
ProteEC-CLA's
comprehensively
capture
local
details
global
features
enhanced,
ensuring
high-accuracy
predictions
on
complex
sequences.
results
demonstrate
that
performs
exceptionally
well
two
independent
representative
datasets.
In
standard
dataset,
it
achieves
98.92%
accuracy
at
EC4
level.
more
challenging
clustered
split
93.34%
an
F1-score
94.72%.
sequences
as
input,
can
accurately
numbers
up
fourth
level,
annotation
accuracy,
makes
a
highly
efficient
precise
tool
enzymology
research
applications.
Language: Английский
Phage-displayed synthetic library and screening platform for nanobody discovery
Published: April 15, 2025
Nanobodies,
single-domain
antibodies
derived
from
camelid
heavy-chain
antibodies,
are
known
for
their
high
affinity,
stability,
and
small
size,
which
make
them
useful
in
biological
research
therapeutic
applications.
However,
traditional
nanobody
generation
methods
rely
on
immunization,
can
be
costly
time-
consuming,
restricting
practical
feasibility.
In
this
study,
we
present
a
phage-
displayed
synthetic
library
discovery.
To
validate
approach,
screened
nanobodies
targeting
various
Drosophila
secreted
proteins.
The
identified
were
suitable
applications
such
as
immunostaining
immunoblotting,
supporting
the
phage-displayed
versatile
platform
development.
address
challenge
of
limited
accessibility
to
high-quality
libraries,
will
openly
available
non-profit
use.
Language: Английский
Phage-displayed synthetic library and screening platform for nanobody discovery
Published: April 15, 2025
Nanobodies,
single-domain
antibodies
derived
from
camelid
heavy-chain
antibodies,
are
known
for
their
high
affinity,
stability,
and
small
size,
which
make
them
useful
in
biological
research
therapeutic
applications.
However,
traditional
nanobody
generation
methods
rely
on
immunization,
can
be
costly
time-
consuming,
restricting
practical
feasibility.
In
this
study,
we
present
a
phage-
displayed
synthetic
library
discovery.
To
validate
approach,
screened
nanobodies
targeting
various
Drosophila
secreted
proteins.
The
identified
were
suitable
applications
such
as
immunostaining
immunoblotting,
supporting
the
phage-displayed
versatile
platform
development.
address
challenge
of
limited
accessibility
to
high-quality
libraries,
will
openly
available
non-profit
use.
Language: Английский