Drug-like screening, molecular docking, molecular dynamics simulations, and binding free energies on the interaction of pyrazole derivatives as inhibitors of lysosomal storage disorders and anticancer activity
Discover Chemistry.,
Год журнала:
2024,
Номер
1(1)
Опубликована: Окт. 2, 2024
Язык: Английский
Design of some potent non-toxic autoimmune disorder inhibitors based on 2D-QSAR, CoMFA, molecular docking, and molecular dynamics investigations
Intelligent Pharmacy,
Год журнала:
2024,
Номер
2(5), С. 688 - 706
Опубликована: Янв. 1, 2024
Current
clinical
research
suggests
that
inhibitors
of
protein
arginine
deiminase
4
(PAD4),
major
histocompatibility
complex
(MHC)
class
II
HLA-DQ-ALPHA
chain,
and
thyrotropin
receptor
(or
TSH
receptor)
which
are
biological
therapeutic
interest,
may
show
potential
in
treating
rheumatoid
arthritis,
type
1
diabetes,
Graves'
disease
other
autoimmune
disorder.
In
the
present
study,
a
comprehensive
analysis
was
conducted
on
collection
32
compounds
concerning
their
anti-rheumatoid
arthritis
activity
as
PAD4.
This
represents
first
instance
these
were
computationally
examined,
employing
an
in-silico
approach
considered
2D-3D
QSAR
modeling,
molecular
docking
further
validated
through
dynamics
ADMET
properties
assessment.
A
credible
2D
(Q_LOOˆ2
=
0.6611
Rˆ2
0.7535)
model
constructed
verified
using
external
validation
test
set,
Y-randomization,
variance
inflation
factor
(VIF),
mean
effect
(MF),
William's
plot
applicability
domain
(AD).
Ligand-based
alignment
implemented
3D-QSAR
examination.
The
outcomes
demonstrated
CoMFA
(uvepls)
(Q2LOO
0.5877;
R2
0.9983)
possess
remarkable
stability
foresight.
internal
indicated
MIFs
display
superior
predictive
capability
compared
to
COMFA
(ffdsel).
Structural
criteria
determined
by
contour
maps
simulations
strategically
employed
develop
10
new,
non-toxic
with
increased
efficacy.
Docking
tests
done
newly
developed
illustrate
binding
mechanism
identify
critical
interaction
residues
inside
active
region
(PDB
id:
3BLU).
addition,
results
selected
designed
sites
diabetes
(6DFX),
(4QT5)
3BLU)
selectivity.
simulation
free
energy
calculations
MM/GBSA
technique
confirmed
proposed
compound
D4
(3BLU)
site.
summary,
our
investigation
might
give
considerable
insight
into
future
design
development
new
inhibitors.
Язык: Английский
Ligand-Based Design of Novel Quinoline Derivatives as Potential Anticancer Agents: An In-Silico Virtual Screening Approach
Molecules,
Год журнала:
2024,
Номер
29(2), С. 426 - 426
Опубликована: Янв. 15, 2024
In
this
study,
using
the
Comparative
Molecular
Field
Analysis
(CoMFA)
approach,
structure-activity
relationship
of
33
small
quinoline-based
compounds
with
biological
anti-gastric
cancer
activity
in
vitro
was
analyzed
3D
space.
Once
geometric
and
energy
structure
target
chemical
library
has
been
optimized
their
steric
electrostatic
molecular
field
descriptions
computed,
ideal
3D-QSAR
model
is
generated
matched
Partial
Least
Squares
regression
(PLS)
algorithm.
The
accuracy,
statistical
precision,
predictive
power
developed
were
confirmed
by
a
range
internal
external
validations,
which
interpreted
robust
correlation
coefficients
(RTrain2=0.931;
Qcv2=0.625;
RTest2=0.875).
After
carefully
analyzing
contour
maps
produced
trained
model,
it
discovered
that
certain
structural
characteristics
are
beneficial
for
enhancing
properties
Quinoline
derivatives.
Based
on
information,
total
five
new
quinoline
developed,
improved
drug-like
bioavailability
measured
POM
calculations.
To
further
explore
potential
these
compounds,
docking
dynamics
simulations
performed
an
aqueous
environment
100
nanoseconds,
specifically
targeting
serine/threonine
protein
kinase.
Overall,
findings
study
can
serve
as
starting
point
experiments
view
to
identification
design
next-generation
drug
therapy
against
cancer.
Язык: Английский
DFT and molecular simulation validation of the binding activity of PDEδ inhibitors for repression of oncogenic k-Ras
PLoS ONE,
Год журнала:
2024,
Номер
19(3), С. e0300035 - e0300035
Опубликована: Март 8, 2024
The
development
of
effective
drugs
targeting
the
K-Ras
oncogene
product
is
a
significant
focus
in
anticancer
drug
development.
Despite
lack
successful
Ras
signaling
inhibitors,
recent
research
has
identified
PDEδ,
KRAS
transporter,
as
potential
target
for
inhibiting
oncogenic
pathway.
This
study
aims
to
investigate
interactions
between
eight
inhibitors
(deltarazine,
deltaflexin
1
and
2,
its
analogues)
PDEδ
understand
their
binding
modes.
will
utilize
computational
techniques
such
density
functional
theory
(DFT)
molecular
electrostatic
surface
(MESP),
docking,
site
analyses,
dynamic
(MD)
simulations,
electronic
structure
computations,
predictions
free
energy.
Molecular
simulations
be
used
predict
conformations
pharmacophoric
features
active
examined
structures.
energies
determined
using
MMPB(GB)SA
method
compared
with
observed
potency
values
tested
compounds.
approach
enhance
understanding
selective
mechanism,
which
could
contribute
novel
signaling.
Язык: Английский
QSAR and machine learning-driven proposition of novel 1,3,4-oxadiazoles and structure-based studies of their antibacterial activities against Xanthomonas oryzae
Theoretical Chemistry Accounts,
Год журнала:
2025,
Номер
144(2)
Опубликована: Фев. 1, 2025
Язык: Английский
Can Kisqali® (Ribociclib) effectively target triple-negative breast cancer? A computational insight on potential mechanisms and therapeutic strategies
Discover Chemistry.,
Год журнала:
2025,
Номер
2(1)
Опубликована: Май 9, 2025
Язык: Английский
Computational design and molecular insights into acetylcholinesterase inhibitors from Aristolochia indica for Alzheimer’s disease therapy
Discover Chemistry.,
Год журнала:
2025,
Номер
2(1)
Опубликована: Май 24, 2025
Язык: Английский
QSAR aided design of potent c‐Met inhibitors using molecular docking, molecular dynamics simulation and binding free energy calculation
Chemistry & Biodiversity,
Год журнала:
2024,
Номер
unknown
Опубликована: Авг. 30, 2024
Abstract
The
mesenchymal‐epithelial
transition
factor
(c‐Met)
is
a
tyrosine
kinase
receptor
protein,
and
excessive
cell
transformation
can
lead
to
cancer.
Therefore,
there
an
urgent
need
develop
novel
inhibitors
by
inhibiting
the
activity
of
c‐Met
protein.
In
this
study,
41
compounds
are
selected
from
reported
literature,
interactions
between
phenoxy
pyridine
derivatives
tumor‐associated
proteins
systematically
investigated
using
series
computer‐assisted
drug
design
(CADD)
methods,
aiming
predict
potential
with
high
activity.
Topomer
CoMFA
(q
2
=0.620,
R
=0.837)
HQSAR
=0.684,
=0.877)
models
demonstrate
level
robustness.
Further
internal
external
validation
assessments
show
applicability
accuracy.
Based
on
results
model,
structural
fragments
higher
contribution
values
identified
randomly
combined
fragment
splice
technique,
result
in
total
20
predicted
activities
than
template
molecules.
Molecular
docking
that
these
have
good
van
der
Waals
forces
target
proteins.
molecular
dynamics
ADMET
predictions
indicate
Y4,
Y5,
Y14
as
inhibitors.
Among
them,
compound
exhibits
superior
stability
binding
free
energy
−165.18
KJ/mol.
These
studies
provide
reference
for
future
development
inhibitory
Язык: Английский
Leveraging class-balancing techniques for predicting c-MET Inhibitors: Descriptor Calculation, Selection, and QSAR Model Optimization using Machine Learning
Research Square (Research Square),
Год журнала:
2024,
Номер
unknown
Опубликована: Сен. 11, 2024
Abstract
The
rapid
emergence
of
resistance
in
cancer
chemotherapy
is
a
major
challenge
the
drug
discovery
cancer,
restricting
action
various
important
classes
inhibitors
against
EGFR,
VEGF,
BRAF,
alkylating
agents,
and
DNA
damaging
agents.
c-MET
plays
an
role
development
to
cancer.
Identifying
potent
inhibitor
can
improve
therapeutic
access
existing
anti-cancer
In
current
study,
we
propose
novel
technique
for
prediction
activity
class
by
using
balancing
ML
classifiers.
This
study
utilizes
3091
molecules
with
inhibitory
concentration
value
(IC
50)
publicly
available
from
ChEMBL
Database.
Using
14
descriptors
random
oversampling
balancing,
investigated
seven
classical
models,
i.e.,
decision
tree
(DT),
Adaboost
(ABDT),
K-nearest
neighbors
(K-NN),
support
vector
machine
(SVM),
Bernoulli
Naïve
Bayes
(BNB),
forest
(RF),
linear
logistic
regression
(LLR)
c-MET.
Of
which
SVM,
LR,
RF
were
top
three
models
providing
high
predictability
after
applying
techniques
performing
rigorous.hyperparameter
tuning.
Even
though
showed
exemplary
performance
terms
ROC-AUC
recall
metrics,
their
validation
on
FDA-approved
drugs
demonstrated
susceptibility
false
negatives.
Owing
this,
developed
consensus
mechanism
based
these
models.
work
large,
diverse
database
screen
potential
inhibitors,
prioritizing
molecule
be
considered
further
experimental
testing.
model
proved
beneficial
as
design
algorithm
development.
Язык: Английский
Synergistic activity of nootropic herbs as potent therapeutics for Alzheimer's disease: A cheminformatics, pharmacokinetics, and system pharmacology approach
Journal of Alzheimer s Disease Reports,
Год журнала:
2024,
Номер
8(1), С. 1745 - 1762
Опубликована: Март 1, 2024
Alzheimer's
disease
(AD)
is
a
progressive
neurodegenerative
disorder,
which
subdues
over
55
million
people
and
finding
cure,
still
remains
disenchanting.
Indian
medicinal
herbs
notably,
Withania
somnifera,
Bacopa
monnieri,
Curcuma
longa,
Clitoria
ternatea
are
traditionally
utilized
for
their
memory-enhancing
properties.
We
computationally
investigated
the
therapeutic
potential
of
four
nootropic
by
uncovering
molecular
mechanisms
underlying
treatment
AD.
Cheminformatics,
pharmacokinetics,
system
pharmacology
studies
were
carried
out
to
predict
phytocompounds
drug-like
properties,
protein
targets,
targets
functional
association
enrichment
analysis.
A
comparative
study
was
performed
with
FDA-approved
drugs.
Investigation
on
expression
in
hippocampus
entorhinal
cortex
AD
brain
performed.
Network
constructed
depict
interaction
between
phytocompounds,
drugs,
targets.
Through
analysis,
we
found
that
shared
common
both
FDA
drugs
under
clinical
trials.
identified
active
compounds
Withaferin
A,
Withanolide-D,
Withanolide-E,
Withanolide-G,
Humulene
epoxide
II,
can
combat
Interestingly,
enzyme
inhibition
scores
much
higher
than
In
addition,
regulatory
proteins
such
as
AβPP,
acetylcholinesterase,
BACE1,
PTPN1
8,
16,
9,
22
respectively.
Nonetheless,
AR
CYP19A,
primary
most
phytocompounds.
Herbal
medicines
synergistically
stimulate
multiple
rendering
holistic
integrative
treatment,
encouraging
promising
avenue
treat
Язык: Английский