Journal of Biomedical Science,
Год журнала:
2025,
Номер
32(1)
Опубликована: Фев. 7, 2025
Abstract
Artificial
intelligence
(AI)
has
emerged
as
a
transformative
force
in
precision
medicine,
revolutionizing
the
integration
and
analysis
of
health
records,
genetics,
immunology
data.
This
comprehensive
review
explores
clinical
applications
AI-driven
analytics
unlocking
personalized
insights
for
patients
with
autoimmune
rheumatic
diseases.
Through
synergistic
approach
integrating
AI
across
diverse
data
sets,
clinicians
gain
holistic
view
patient
potential
risks.
Machine
learning
models
excel
at
identifying
high-risk
patients,
predicting
disease
activity,
optimizing
therapeutic
strategies
based
on
clinical,
genomic,
immunological
profiles.
Deep
techniques
have
significantly
advanced
variant
calling,
pathogenicity
prediction,
splicing
analysis,
MHC-peptide
binding
predictions
genetics.
AI-enabled
including
dimensionality
reduction,
cell
population
identification,
sample
classification,
provides
unprecedented
into
complex
immune
responses.
The
highlights
real-world
examples
medicine
platforms
decision
support
tools
rheumatology.
Evaluation
outcomes
demonstrates
benefits
impact
these
approaches
care.
However,
challenges
such
quality,
privacy,
clinician
trust
must
be
navigated
successful
implementation.
future
lies
continued
research,
development,
to
unlock
care
drive
innovation
PLoS ONE,
Год журнала:
2024,
Номер
19(1), С. e0297560 - e0297560
Опубликована: Янв. 25, 2024
Variants
in
the
cystic
fibrosis
transmembrane
conductance
regulator
gene
(CFTR)
result
fibrosis-a
lethal
autosomal
recessive
disorder.
Missense
variants
that
alter
a
single
amino
acid
CFTR
protein
are
among
most
common
variants,
yet
tools
for
accurately
predicting
molecular
consequences
of
missense
have
been
limited
to
date.
AlphaMissense
(AM)
is
new
technology
predicts
pathogenicity
based
on
dual
learned
structure
and
evolutionary
features.
Here,
we
evaluated
ability
AM
predict
variants.
predicted
high
residues
overall,
resulting
false
positive
rate
fair
classification
performance
CF
from
CFTR2.org
database.
score
correlated
modestly
with
metrics
persons
including
sweat
chloride
level,
pancreatic
insufficiency
rate,
Pseudomonas
aeruginosa
infection
rate.
Correlation
was
also
modest
trafficking
folding
competency
vitro.
By
contrast,
well
channel
function
vitro-demonstrating
training
approach
learns
important
functional
information
despite
lacking
such
data
during
training.
Different
across
indicated
may
determine
if
polymorphisms
cannot
differentiate
mechanistic
effects
or
nature
pathophysiology.
Finally,
predictions
offered
utility
inform
pharmacological
response
i.e.,
theratype.
Development
approaches
biochemical
properties
therefore
still
needed
refine
targeting
emerging
precision
therapeutics.
Nucleic Acids Research,
Год журнала:
2024,
Номер
53(D1), С. D948 - D957
Опубликована: Дек. 4, 2024
Ensembl
(www.ensembl.org)
is
an
open
platform
integrating
publicly
available
genomics
data
across
the
tree
of
life
with
a
focus
on
eukaryotic
species
related
to
human
health,
agriculture
and
biodiversity.
This
year
has
seen
continued
expansion
in
number
represented,
>4800
>31
300
prokaryotic
genomes
available.
The
new
site,
currently
beta,
develop,
holding
>2700
genome
assemblies.
site
provides
genome,
gene,
transcript,
homology
variation
views,
will
replace
current
Rapid
Release
site;
this
represents
key
step
towards
provision
single
integrated
site.
Additional
activities
have
included
developing
improved
regulatory
annotation
for
human,
mouse
agricultural
species,
expanding
Variant
Effect
Predictor
tool.
To
learn
more
about
Ensembl,
help
documentation
are
along
extensive
training
program
that
can
be
accessed
via
our
pages.
Abstract
Single
amino
acid
substitutions
can
profoundly
affect
protein
folding,
dynamics,
and
function.
The
ability
to
discern
between
benign
pathogenic
is
pivotal
for
therapeutic
interventions
research
directions.
Given
the
limitations
in
experimental
examination
of
these
variants,
AlphaMissense
has
emerged
as
a
promising
predictor
pathogenicity
missense
variants.
Since
heterogenous
performance
on
different
types
proteins
be
expected,
we
assessed
efficacy
across
several
groups
(e.g.
soluble,
transmembrane,
mitochondrial
proteins)
regions
intramembrane,
membrane
interacting,
high
confidence
AlphaFold
segments)
using
ClinVar
data
validation.
Our
comprehensive
evaluation
showed
that
delivers
outstanding
performance,
with
MCC
scores
predominantly
0.6
0.74.
We
observed
low
disordered
datasets
related
CFTR
ABC
protein.
However,
superior
was
shown
when
benchmarked
against
quality
CFTR2
database.
results
emphasizes
AlphaMissense’s
potential
pinpointing
functional
hot
spots,
its
likely
surpassing
benchmarks
calculated
from
ProteinGym
datasets.
Nature Communications,
Год журнала:
2024,
Номер
15(1)
Опубликована: Июль 29, 2024
Abstract
The
effective
design
of
combinatorial
libraries
to
balance
fitness
and
diversity
facilitates
the
engineering
useful
enzyme
functions,
particularly
those
that
are
poorly
characterized
or
unknown
in
biology.
We
introduce
MODIFY,
a
machine
learning
(ML)
algorithm
learns
from
natural
protein
sequences
infer
evolutionarily
plausible
mutations
predict
fitness.
MODIFY
co-optimizes
predicted
sequence
starting
libraries,
prioritizing
high-fitness
variants
while
ensuring
broad
coverage.
In
silico
evaluation
shows
outperforms
state-of-the-art
unsupervised
methods
zero-shot
prediction
enables
ML-guided
directed
evolution
with
enhanced
efficiency.
Using
we
engineer
generalist
biocatalysts
derived
thermostable
cytochrome
c
achieve
enantioselective
C-B
C-Si
bond
formation
via
new-to-nature
carbene
transfer
mechanism,
leading
six
away
previously
developed
enzymes
exhibiting
superior
comparable
activities.
These
results
demonstrate
MODIFY’s
potential
solving
challenging
problems
beyond
reach
classic
evolution.
Cell,
Год журнала:
2024,
Номер
187(16), С. 4231 - 4245.e13
Опубликована: Июль 3, 2024
The
human
coronavirus
HKU1
spike
(S)
glycoprotein
engages
host
cell
surface
sialoglycans
and
transmembrane
protease
serine
2
(TMPRSS2)
to
initiate
infection.
molecular
basis
of
binding
TMPRSS2
determinants
receptor
tropism
remain
elusive.
We
designed
an
active
construct
enabling
high-yield
recombinant
production
in
cells
this
key
therapeutic
target.
determined
a
cryo-electron
microscopy
structure
the
RBD
bound
TMPRSS2,
providing
blueprint
interactions
supporting
viral
entry
explaining
specificity
for
among
orthologous
proteases.
identified
orthologs
from
five
mammalian
orders
promoting
S-mediated
into
along
with
residues
governing
usage.
Our
data
show
that
motif
is
site
vulnerability
neutralizing
antibodies
suggest
uses
S
conformational
masking
glycan
shielding
balance
immune
evasion
engagement.
Abstract
Missense
variants
that
change
the
amino
acid
sequences
of
proteins
cause
one-third
human
genetic
diseases
1
.
Tens
millions
missense
exist
in
current
population,
and
vast
majority
these
have
unknown
functional
consequences.
Here
we
present
a
large-scale
experimental
analysis
across
many
different
proteins.
Using
DNA
synthesis
cellular
selection
experiments
quantify
effect
more
than
500,000
on
abundance
500
protein
domains.
This
dataset
reveals
60%
pathogenic
reduce
stability.
The
contribution
stability
to
fitness
varies
is
particularly
important
recessive
disorders.
We
combine
measurements
with
language
models
annotate
sites
Mutational
effects
are
largely
conserved
homologous
domains,
enabling
accurate
prediction
entire
families
using
energy
models.
Our
data
demonstrate
feasibility
assaying
at
scale
provides
large
consistent
reference
for
clinical
variant
interpretation
training
benchmarking
computational
methods.
Genetic
diagnosis
of
rare
diseases
requires
accurate
identification
and
interpretation
genomic
variants.
Clinical
molecular
scientists
from
37
expert
centers
across
Europe
created
the
Solve-Rare
Diseases
Consortium
(Solve-RD)
resource,
encompassing
clinical,
pedigree
rare-disease
data
(94.5%
exomes,
5.5%
genomes),
performed
systematic
reanalysis
for
6,447
individuals
(3,592
male,
2,855
female)
with
previously
undiagnosed
6,004
families.
We
established
a
collaborative,
two-level
review
infrastructure
that
allowed
genetic
in
506
(8.4%)
Of
552
disease-causing
variants
identified,
464
(84.1%)
were
single-nucleotide
or
short
insertions/deletions.
These
either
located
recently
published
novel
disease
genes
(n
=
67),
reclassified
ClinVar
187)
by
consensus
decision
within
Solve-RD
210).
Bespoke
bioinformatics
analyses
identified
remaining
15.9%
causative
88).
Ad
hoc
review,
parallel
to
reanalysis,
diagnosed
249
(4.1%)
additional
families
an
overall
diagnostic
yield
12.6%.
The
collaborative
networks
set
up
can
serve
as
blueprint
future
further
scalable
international
efforts.
resource
is
open
global
community,
allowing
phenotype,
variant
gene
queries,
well
genome-wide
discoveries.
Nature Immunology,
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 10, 2025
The
NLRP3
inflammasome
is
a
multiprotein
complex
that
mediates
caspase-1
activation
and
the
release
of
proinflammatory
cytokines,
including
interleukin
(IL)-1β
IL-18.
Gain-of-function
variants
in
gene
encoding
(also
called
cryopyrin)
lead
to
constitutive
excessive
IL-1β
production
cryopyrin-associated
periodic
syndromes
(CAPS).
Here
we
present
functional
screening
automated
analysis
534
from
international
INFEVERS
registry
ClinVar
database.
This
resource
captures
effect
on
ASC
speck
formation
spontaneously,
at
low
temperature,
after
stimulation
with
specific
inhibitor
MCC950.
Most
notably,
our
facilitated
updated
classification
INFEVERS.
Structural
suggested
multiple
mechanisms
by
which
CAPS
activate
NLRP3,
enhanced
ATP
binding,
stabilizing
active
conformation,
destabilizing
inactive
promoting
oligomerization
pyrin
domain.
Furthermore,
identified
pathogenic
can
hypersensitize
response
nigericin
cold
temperature
exposure.
We
also
found
most
CAPS-related
be
inhibited
MCC950;
however,
changes
proline
affecting
helices
near
binding
site
are
resistant
MCC950,
as
domain,
likely
trigger
directly
domain
ASC.
Our
findings
could
help
stratify
population
for
clinical
trials
methodologies
implemented
molecules
different
mechanism
laboratories
worldwide
interested
adding
new
functionally
validated
resource.
Overall,
study
provides
improved
diagnosis
patients
CAPS,
mechanistic
insight
into
stratification
future
application
targeted
therapeutics.
bioRxiv (Cold Spring Harbor Laboratory),
Год журнала:
2025,
Номер
unknown
Опубликована: Фев. 21, 2025
Abstract
All
of
life
encodes
information
with
DNA.
While
tools
for
sequencing,
synthesis,
and
editing
genomic
code
have
transformed
biological
research,
intelligently
composing
new
systems
would
also
require
a
deep
understanding
the
immense
complexity
encoded
by
genomes.
We
introduce
Evo
2,
foundation
model
trained
on
9.3
trillion
DNA
base
pairs
from
highly
curated
atlas
spanning
all
domains
life.
train
2
7B
40B
parameters
to
an
unprecedented
1
million
token
context
window
single-nucleotide
resolution.
learns
sequence
alone
accurately
predict
functional
impacts
genetic
variation—from
noncoding
pathogenic
mutations
clinically
significant
BRCA1
variants—without
task-specific
finetuning.
Applying
mechanistic
interpretability
analyses,
we
reveal
that
autonomously
breadth
features,
including
exon–intron
boundaries,
transcription
factor
binding
sites,
protein
structural
elements,
prophage
regions.
Beyond
its
predictive
capabilities,
generates
mitochondrial,
prokaryotic,
eukaryotic
sequences
at
genome
scale
greater
naturalness
coherence
than
previous
methods.
Guiding
via
inference-time
search
enables
controllable
generation
epigenomic
structure,
which
demonstrate
first
scaling
results
in
biology.
make
fully
open,
parameters,
training
code,
inference
OpenGenome2
dataset,
accelerate
exploration
design
complexity.
European Journal of Human Genetics,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 13, 2025
Abstract
Artificial
intelligence
(AI)
has
been
growing
more
powerful
and
accessible,
will
increasingly
impact
many
areas,
including
virtually
all
aspects
of
medicine
biomedical
research.
This
review
focuses
on
previous,
current,
especially
emerging
applications
AI
in
clinical
genetics.
Topics
covered
include
a
brief
explanation
different
general
categories
AI,
machine
learning,
deep
generative
AI.
After
introductory
explanations
examples,
the
discusses
genetics
three
main
categories:
diagnostics;
management
therapeutics;
support.
The
concludes
with
short,
medium,
long-term
predictions
about
ways
that
may
affect
field
Overall,
while
precise
speed
at
which
continue
to
change
is
unclear,
as
are
overall
ramifications
for
patients,
families,
clinicians,
researchers,
others,
it
likely
result
dramatic
evolution
It
be
important
those
involved
prepare
accordingly
order
minimize
risks
maximize
benefits
related
use
field.