Pharmaceutical Fronts,
Journal Year:
2024,
Volume and Issue:
06(03), P. e252 - e264
Published: Sept. 1, 2024
Abstract
Biocatalysis
has
been
widely
used
to
prepare
drug
leads
and
intermediates.
Enzymatic
synthesis
advantages,
mainly
in
terms
of
strict
chirality
regional
selectivity
compared
with
chemical
methods.
However,
the
enzymatic
properties
wild-type
enzymes
may
or
not
meet
requirements
for
biopharmaceutical
applications.
Therefore,
protein
engineering
is
required
improve
their
catalytic
activities.
Thanks
advances
algorithmic
models
accumulation
immense
biological
data,
artificial
intelligence
can
provide
novel
approaches
functional
evolution
enzymes.
Deep
learning
advantage
functions
that
predict
previously
unknown
sequences.
learning-based
computational
algorithms
intelligently
navigate
sequence
space
reduce
screening
burden
during
evolution.
Thus,
intelligent
design
combined
laboratory
a
powerful
potentially
versatile
strategy
developing
functions.
Herein,
we
introduce
summarize
deep-learning-assisted
enzyme
adaptive
strategies
based
on
recent
studies
application
deep
Altogether,
developments
technology
data
characterization
functions,
become
tool
future.
Biophysics and Physicobiology,
Journal Year:
2024,
Volume and Issue:
21(3), P. n/a - n/a
Published: Jan. 1, 2024
Chemical
tongues
are
emerging
powerful
bioanalytical
tools
that
mimic
the
mechanism
of
human
taste
system
to
recognize
comprehensive
characteristics
complex
biological
samples.
By
using
an
array
chromogenic
or
fluorogenic
probes
interact
non-specifically
with
various
components
in
samples,
this
tool
generates
unique
colorimetric
fluorescence
patterns
reflect
composition
a
sample.
These
then
analyzed
multivariate
analysis
machine
learning
distinguish
and
classify
This
review
focuses
on
our
efforts
provide
overview
fundamental
principles
chemical
tongues,
probe
design,
their
applications
as
versatile
for
analyzing
proteins,
cells,
bacteria
Compared
conventional
methods
rely
specific
targeting
(e.g.,
antibodies
enzymes)
omics
analyses,
offer
advantages
terms
cost
ability
analyze
samples
without
need
biomarkers.
The
complementary
use
is
expected
enable
more
detailed
understanding
lead
elucidation
new
phenomena.
Current Opinion in Electrochemistry,
Journal Year:
2024,
Volume and Issue:
47, P. 101565 - 101565
Published: June 28, 2024
The
study
of
single
redox
enzymes
by
electrochemistry
is
well-established,
using
both
mediated
and
direct
electron
exchange
between
the
enzyme
electrode.
Moving
beyond
enzymes,
electrochemically
driven
multienzyme
cascades
can
achieve
more
complex
transformations,
in
this
review,
we
highlight
recent
advances.
Electrochemical
control
multiple
discussed,
with
examples
including,
electrode
surface
modification
engineering
to
facilitate
electrode,
new
developments
made
entrapment
a
highly
porous
called
electrochemical
leaf.
Examples
that
harness
power
potential
ability
monitor
cascade
activity
as
electrical
current,
include
synthesis,
deracemization,
measurement
drug
binding
kinetics.
Redox
cofactors
(e.g.
NADP(H))
be
regenerated
variety
but
non-redox
are
less
amenable
regeneration,
for
adenosine
triphosphate
(ATP)
regeneration
designed
an
step
generate
required
phosphate
donor.
Finally,
cover
approaches
model
cascades,
which
predicted
local
environments
pH)
difficult
measure
directly
yielded
guidelines
rational
design
immobilized
electrodes.
Pharmaceutical Fronts,
Journal Year:
2024,
Volume and Issue:
06(03), P. e252 - e264
Published: Sept. 1, 2024
Abstract
Biocatalysis
has
been
widely
used
to
prepare
drug
leads
and
intermediates.
Enzymatic
synthesis
advantages,
mainly
in
terms
of
strict
chirality
regional
selectivity
compared
with
chemical
methods.
However,
the
enzymatic
properties
wild-type
enzymes
may
or
not
meet
requirements
for
biopharmaceutical
applications.
Therefore,
protein
engineering
is
required
improve
their
catalytic
activities.
Thanks
advances
algorithmic
models
accumulation
immense
biological
data,
artificial
intelligence
can
provide
novel
approaches
functional
evolution
enzymes.
Deep
learning
advantage
functions
that
predict
previously
unknown
sequences.
learning-based
computational
algorithms
intelligently
navigate
sequence
space
reduce
screening
burden
during
evolution.
Thus,
intelligent
design
combined
laboratory
a
powerful
potentially
versatile
strategy
developing
functions.
Herein,
we
introduce
summarize
deep-learning-assisted
enzyme
adaptive
strategies
based
on
recent
studies
application
deep
Altogether,
developments
technology
data
characterization
functions,
become
tool
future.
