ACS Omega,
Journal Year:
2025,
Volume and Issue:
10(6), P. 5795 - 5808
Published: Feb. 10, 2025
Eukaryotic
initiation
factor
4A-1
(eIF4A1)
is
an
ATP-dependent
RNA
helicase
that
unwinds
5'-UTR
mRNA
secondary
structures
to
facilitate
cap-dependent
translation
initiation.
Rocaglates,
a
class
of
natural
products
typified
by
rocaglamide
A
(RocA),
possess
antineoplastic
and
anti-infectious
activity
mediated
their
interaction
with
eIF4A1.
Rocaglates
inhibit
"clamping"
eIF4A1
onto
polypurine
RNA,
which
impedes
ribosome
scanning.
novel
rocaglate
derivatives,
amidino-rocaglates
(ADRs)
feature
amidine
ring
fused
the
core,
particularly
effective
at
promoting
eIF4A1-RNA-clamping
compared
other
congeners.
Herein,
we
present
X-ray
crystal
structure
ADR
in
complex
eIF4A1,
nonhydrolyzable
ATP
ground-state
mimic
adenylyl-imidodiphosphate
(AMPPNP),
poly
r(AG)5
refined
1.69
Å
resolution.
The
binding
pose
interactions
do
not
differ
substantially
from
those
RocA,
prompting
investigation
basis
for
enhanced
target
engagement.
Computational
modeling
suggests
rigidified
scaffold
inherently
preorganized
eIF4A1-RNA
binding-competent
conformation,
thereby
avoiding
entropic
penalties
associated
RocA
binding.
This
study
illustrates
how
conformational
rigidification
can
be
leveraged
improve
potency
development
rocaglates
as
potential
anticancer
agents.
Pharmaceutics,
Journal Year:
2022,
Volume and Issue:
15(1), P. 49 - 49
Published: Dec. 23, 2022
The
drug
discovery
process
is
a
rocky
path
that
full
of
challenges,
with
the
result
very
few
candidates
progress
from
hit
compound
to
commercially
available
product,
often
due
factors,
such
as
poor
binding
affinity,
off-target
effects,
or
physicochemical
properties,
solubility
stability.
This
further
complicated
by
high
research
and
development
costs
time
requirements.
It
thus
important
optimise
every
step
in
order
maximise
chances
success.
As
recent
advancements
computer
power
technology,
computer-aided
design
(CADD)
has
become
an
integral
part
modern
guide
accelerate
process.
In
this
review,
we
present
overview
CADD
methods
applications,
silico
structure
prediction,
refinement,
modelling
target
validation,
are
commonly
used
area.
Energy & Environmental Science,
Journal Year:
2024,
Volume and Issue:
17(14), P. 4907 - 4928
Published: Jan. 1, 2024
Recent
studies
on
enhancing
charge
carrier
behavior
through
electric
effects
for
efficient
photocatalysis
are
summarized,
evaluating
the
in-depth
function
of
these
effects.
This
provides
unique
perspectives
to
optimize
photocatalytic
processes.
Journal of Materials Chemistry A,
Journal Year:
2023,
Volume and Issue:
11(8), P. 4111 - 4125
Published: Jan. 1, 2023
TTE
(1,1,2,2-tetrafluoroethyl
2,2,3,3-tetrafluoropropyl
ether)
shows
better
performance
than
BTFE
(bis(2,2,2-trifluoroethyl)ether
as
diluent
in
a
localized
highly
concentrated
electrolyte
based
on
lithium
bis(fluorosulfonyl)imide
triethylposphate.
Physical Chemistry Chemical Physics,
Journal Year:
2024,
Volume and Issue:
26(32), P. 21379 - 21394
Published: Jan. 1, 2024
Efficient
dispersion
corrections
are
an
indispensable
component
of
modern
density
functional
theory,
semi-empirical
quantum
mechanical,
and
even
force
field
methods.
In
this
work,
we
extend
the
well
established
D3
D4
London
to
full
actinides
series,
francium,
radium.
To
keep
consistency
with
existing
versions,
original
parameterization
strategy
model
was
only
slightly
modified.
This
includes
improved
reference
Hirshfeld
atomic
partial
charges
at
ωB97M-V/ma-def-TZVP
level
fit
required
electronegativity
equilibration
charge
(EEQ)
model.
context,
developed
a
new
actinide
data
set
called
AcQM,
which
covers
most
common
molecular
compound
space.
Furthermore,
efficient
calculation
dynamic
polarizabilities
that
needed
construct
A
recent
study
suggests
that
Gaussian
basis
sets
in
the
6-311G
family
are
inappropriate
for
thermochemical
calculations
based
on
density
functional
theory,
emphasizing
need
polarization
functions
but
omitting
tests
of
Pople
containing
a
full
complement
thereof.
Here,
we
point
out
certain
category
yield
error
statistics
with
respect
to
benchmark
comparable
def2-TZVP,
at
about
half
cost.
More
elaborate
can
rival
accuracy
def2-QZVPD
5-10%
We
also
clarify
role
integral
thresholds
achieving
robust
convergence
presence
diffuse
functions.
Chemical Science,
Journal Year:
2024,
Volume and Issue:
15(12), P. 4434 - 4451
Published: Jan. 1, 2024
This
study
incorporates
Minnesota
density
functionals
into
the
current
knowledge
of
describing
structural
and
dynamical
properties
liquid
water
through
ab
initio
molecular
dynamics,
with
M06-2X(-D3)
showing
most
promise.
Chemical Science,
Journal Year:
2025,
Volume and Issue:
unknown
Published: Jan. 1, 2025
Active
learning
combined
with
quantum
chemistry
reveals
the
nature
of
functional
monomer
design
across
a
diverse
chemical
space
12M
synthetically
accessible
polymers.
Journal of Chemical Theory and Computation,
Journal Year:
2023,
Volume and Issue:
19(22), P. 8097 - 8107
Published: Nov. 13, 2023
For
ground-
and
excited-state
studies
of
large
molecules,
it
is
the
state
art
to
combine
(time-dependent)
DFT
with
dispersion-corrected
range-separated
hybrid
functionals
(RSHs),
which
ensures
an
asymptotically
correct
description
exchange
effects
London
dispersion.
Specifically
for
studying
excited
states,
common
practice
tune
range-separation
parameter
ω
(optimal
tuning),
can
further
improve
accuracy.
However,
since
optimal
tuning
essentially
changes
functional,
unclear
if
how
much
parameters
used
dispersion
correction
depend
on
chosen
value.
To
answer
this
question,
we
explore
interdependency
by
refitting
DFT-D4
model
six
established
RSHs
over
a
wide
range
values
(0.05-0.45
a0-1)
using
set
noncovalently
bound
molecular
complexes.
The
results
reveal
some
surprising
differences
among
investigated
functionals:
While
PBE-based
ωB97M-D4
generally
exhibit
weak
robust
performance
values,
B88-based
RSHs,
specifically
LC-BLYP,
are
strongly
affected.
these,
even
minor
reduction
from
default
value
manifests
in
strong
systematic
overbinding
poor
typical
optimally
tuned
values.
Finally,
discuss
strategies
mitigate
these
issues
reflect
context
employed
D4
optimization
algorithm
fit
set,
outlining
future
improvements.