Chemical Reviews,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 22, 2025
Throughout
history,
we
have
looked
to
nature
discover
and
copy
pharmaceutical
solutions
prevent
heal
diseases.
Due
the
advances
in
metabolic
engineering
production
of
proteins
different
host
cells,
moved
from
mimicking
delicate
cells
proteins.
We
can
now
produce
novel
drug
molecules,
which
are
fusions
small
chemical
drugs
Currently
at
brink
yet
another
step
venture
beyond
nature's
border
with
use
unnatural
amino
acids
manufacturing
without
living
using
cell-free
systems.
In
this
review,
summarize
progress
limitations
last
decades
development
protein
development,
also
discuss
possible
future
directions
field.
RSC Advances,
Journal Year:
2023,
Volume and Issue:
13(51), P. 35947 - 35963
Published: Jan. 1, 2023
Protein-based
therapeutics
have
revolutionized
the
pharmaceutical
industry
and
become
vital
components
in
development
of
future
therapeutics.
They
offer
several
advantages
over
traditional
small
molecule
drugs,
including
high
affinity,
potency
specificity,
while
demonstrating
low
toxicity
minimal
adverse
effects.
However,
manufacturing
processes
protein-based
presents
challenges
related
to
protein
folding,
purification,
stability
immunogenicity
that
should
be
addressed.
These
proteins,
like
other
biological
molecules,
are
prone
chemical
physical
instabilities.
The
drugs
throughout
entire
manufacturing,
storage
delivery
process
is
essential.
occurrence
structural
instability
resulting
from
misfolding,
unfolding,
modifications,
as
well
aggregation,
poses
a
significant
risk
efficacy
these
overshadowing
their
promising
attributes.
Gaining
insight
into
alterations
caused
by
aggregation
impact
on
for
advancement
refinement
Hence,
this
review,
we
discussed
some
features
during
production,
formulation
stabilization
strategies
engineering
computational
methods
prevent
aggregation.
Molecules,
Journal Year:
2024,
Volume and Issue:
29(19), P. 4626 - 4626
Published: Sept. 29, 2024
The
field
of
computational
protein
engineering
has
been
transformed
by
recent
advancements
in
machine
learning,
artificial
intelligence,
and
molecular
modeling,
enabling
the
design
proteins
with
unprecedented
precision
functionality.
Computational
methods
now
play
a
crucial
role
enhancing
stability,
activity,
specificity
for
diverse
applications
biotechnology
medicine.
Techniques
such
as
deep
reinforcement
transfer
learning
have
dramatically
improved
structure
prediction,
optimization
binding
affinities,
enzyme
design.
These
innovations
streamlined
process
allowing
rapid
generation
targeted
libraries,
reducing
experimental
sampling,
rational
tailored
properties.
Furthermore,
integration
approaches
high-throughput
techniques
facilitated
development
multifunctional
novel
therapeutics.
However,
challenges
remain
bridging
gap
between
predictions
validation
addressing
ethical
concerns
related
to
AI-driven
This
review
provides
comprehensive
overview
current
state
future
directions
engineering,
emphasizing
their
transformative
potential
creating
next-generation
biologics
advancing
synthetic
biology.
Engineering Reports,
Journal Year:
2025,
Volume and Issue:
7(2)
Published: Feb. 1, 2025
ABSTRACT
The
field
of
protein
engineering
has
witnessed
transformative
advancements,
with
computational
tools
and
databases
driving
novel
innovations
in
de
novo
design.
This
review
consolidates
critiques
a
comprehensive
range
modern
resources,
offering
unique
focus
on
their
applications
across
diverse
domains,
including
stability
prediction,
posttranslational
modification
analysis,
mutation
effect
evaluation.
Key
contributions
include
detailed
examination
integrating
machine
learning
artificial
intelligence
to
enhance
predictive
accuracy
streamline
workflows.
By
highlighting
underexplored
methodologies,
such
as
advanced
protein–ligand
interaction
predictors
neural
network–based
assessment
models,
this
study
establishes
itself
reference
for
researchers
aiming
develop
tailored
proteins
therapeutic,
industrial,
biomedical
applications.
