Multiple Alignments of Protein Families with Weak Sequence Similarity Within the Family
Symmetry,
Год журнала:
2025,
Номер
17(3), С. 408 - 408
Опубликована: Март 9, 2025
Statistically
significant
multiple
sequence
alignment
construction
is
an
important
task
that
has
many
biological
applications.
We
applied
the
method
for
alignments
of
highly
divergent
sequences
(MAHDS)
to
construct
(MSAs)
490
protein
families
with
less
than
20%
identity
between
family
members.
The
uses
random
symmetric
position–weight
matrices
(PWMs)
and
a
genetic
algorithm
alignment.
PWM
symmetry
essential
because
it
makes
PWMs
comparable
recoverable
at
all
steps
MAHDS
algorithm,
which
reduces
optimal
MSA
search
optimization
task.
A
Monte
Carlo
assess
statistical
significance
resulting
alignments.
constructed
MSAs
was
compared
obtained
using
T-Coffee
MUSCLE
algorithms.
results
showed
476
families,
created
much
more
statistically
MUSCLE,
whereas
138
only
could
MSAs.
These
findings
indicate
calculate
in
cases
when
other
methods
create
purely
are,
therefore,
most
appropriate
proteins
weak
similarities
amino
acid
annotation.
Язык: Английский
Revolutionizing Molecular Design for Innovative Therapeutic Applications through Artificial Intelligence
Molecules,
Год журнала:
2024,
Номер
29(19), С. 4626 - 4626
Опубликована: Сен. 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.
Язык: Английский
An Algorithm for Local Alignment of DNA and Protein Sequences
Lecture notes in computer science,
Год журнала:
2024,
Номер
unknown, С. 73 - 86
Опубликована: Янв. 1, 2024
Язык: Английский
Kill Chain Catalyst for Autonomous Red Team Operations in Dynamic Attack Scenarios
Опубликована: Сен. 16, 2024
From
the
perspective
of
real-world
cyber
attacks,
executing
actions
with
minimal
failures
and
steps
is
crucial
to
reducing
likelihood
exposure.
Although
research
on
autonomous
attacks
predominantly
employs
Reinforcement
Learning
(RL),
this
approach
has
gaps
in
scenarios
such
as
limited
training
data
low
resilience
dynamic
environments.
Therefore,
Kill
Chain
Catalyst
(KCC)
been
introduced:
an
RL
algorithm
that
decision
tree
logic,
inspired
by
genetic
alignment,
prioritizing
experiences.
Experiments
reveal
significant
improvements
failures,
well
increased
rewards
when
using
KCC
compared
other
algorithms.
Язык: Английский