Advances in medical technologies and clinical practice book series,
Год журнала:
2024,
Номер
unknown, С. 217 - 246
Опубликована: Окт. 25, 2024
The
chapter
explores
the
integration
of
fragment-based
drug
design
(FBDD)
and
diffusion-based
models,
exemplified
by
ProteinReDiff,
in
advancing
ligand-centric
approaches
to
discovery.
FBDD
provides
a
strategic
framework
for
identifying
potential
candidates,
while
ProteinReDiff
streamlines
redesign
process
through
innovative
computational
techniques.
discusses
effectiveness
both
methodologies
optimizing
ligand
binding
affinity
enhancing
efficacy,
as
evidenced
experimental
validations.
It
highlights
paradigm
shift
brought
about
models
like
which
depart
from
traditional
reliance
on
structural
data,
making
more
accessible
efficient.
abstract
emphasizes
promise
accelerating
therapeutic
development
driving
innovation
biomedical
research,
with
focus
transparency
credibility
scientific
endeavors.
Journal of Chemical Theory and Computation,
Год журнала:
2025,
Номер
unknown
Опубликована: Янв. 2, 2025
Fragment-based
quantum
chemistry
methods
offer
a
means
to
sidestep
the
steep
nonlinear
scaling
of
electronic
structure
calculations
so
that
large
molecular
systems
can
be
investigated
using
high-level
methods.
Here,
we
use
fragmentation
compute
protein-ligand
interaction
energies
in
with
several
thousand
atoms,
new
software
platform
for
managing
fragment-based
implements
screened
many-body
expansion.
Convergence
tests
minimal-basis
semiempirical
method
(HF-3c)
indicate
two-body
calculations,
single-residue
fragments
and
simple
hydrogen
caps,
are
sufficient
reproduce
obtained
conventional
supramolecular
within
1
kcal/mol
at
about
1%
computational
cost.
We
also
demonstrate
HF-3c
results
illustrative
trends
density
functional
theory
basis
sets
up
augmented
quadruple-ζ
quality.
Strategic
deployment
facilitates
converged
biomolecular
model
alongside
high-quality
sets,
bringing
Journal of Chemical Theory and Computation,
Год журнала:
2023,
Номер
19(21), С. 7478 - 7495
Опубликована: Окт. 26, 2023
Modern
therapeutic
development
often
involves
several
stages
that
are
interconnected,
and
multiple
iterations
usually
required
to
bring
a
new
drug
the
market.
Computational
approaches
have
increasingly
become
an
indispensable
part
of
helping
reduce
time
cost
research
drugs.
In
this
Perspective,
we
summarize
our
recent
efforts
on
integrating
molecular
modeling
machine
learning
develop
computational
tools
for
modulator
design,
including
pocket-guided
rational
design
approach
based
AlphaSpace
target
protein-protein
interactions,
delta
scoring
functions
protein-ligand
docking
as
well
virtual
screening,
state-of-the-art
deep
models
predict
calculated
experimental
properties
mechanics
optimized
geometries.
Meanwhile,
discuss
remaining
challenges
promising
directions
further
use
retrospective
example
FDA
approved
kinase
inhibitor
Erlotinib
demonstrate
these
newly
developed
tools.
Artificial Intelligence Chemistry,
Год журнала:
2024,
Номер
2(2), С. 100075 - 100075
Опубликована: Июль 27, 2024
The
beginning
and
ripening
of
digital
chemistry
is
analyzed
focusing
on
the
role
artificial
intelligence
(AI)
in
an
expected
leap
chemical
sciences
to
bring
this
area
next
evolutionary
level.
analytic
description
selects
highlights
top
20
AI-based
technologies
7
broader
themes
that
are
reshaping
field.
It
underscores
integration
tools
such
as
machine
learning,
big
data,
twins,
Internet
Things
(IoT),
robotic
platforms,
smart
control
processes,
virtual
reality
blockchain,
among
many
others,
enhancing
research
methods,
educational
approaches,
industrial
practices
chemistry.
significance
study
lies
its
focused
overview
how
these
innovations
foster
a
more
efficient,
sustainable,
innovative
future
sciences.
This
article
not
only
illustrates
transformative
impact
but
also
draws
new
pathways
chemistry,
offering
broad
appeal
researchers,
educators,
industry
professionals
embrace
advancements
for
addressing
contemporary
challenges
