KNIME Workflows for Chemoinformatic Characterization of Chemical Databases
Carlos D. Ramírez‐Márquez,
No information about this author
José L. Medina‐Franco
No information about this author
Molecular Informatics,
Journal Year:
2025,
Volume and Issue:
44(2)
Published: Feb. 1, 2025
Abstract
In
chemoinformatics,
chemical
databases
have
great
importance
since
their
main
objective
is
to
store
and
organize
the
structures
of
molecules
properties,
from
basic
information
such
as
structure
more
complex
like
molecular
fingerprints
or
other
types
calculated
experimental
descriptors
biological
activity.
However,
this
data
can
only
be
utilized
in
projects
identify
novel
therapeutic
fields
through
correct
characterization
analysis.
Application
Note,
we
compiled
five
workflows
within
open‐source
analytics
visualization
platform
KNIME
that
implemented
for
chemoinformatic
databases.
To
illustrate
application
workflows,
used
BIOFACQUIM,
a
compound
database
natural
products
isolated
characterized
Mexico
[1].
Language: Английский
Chemoinformatic characterization of NAPROC-13: A database for natural product 13C-RMN dereplication
Published: May 7, 2024
Natural
products
(NPs)
are
secondary
metabolites
of
natural
origin
with
broad
applications
across
various
human
activities,
particularly
discovering
bioactive
compounds.
Structural
elucidation
new
NPs
entails
significant
cost
and
effort.
On
the
other
hand,
dereplication
known
compounds
is
crucial
for
early
exclusion
irrelevant
in
contemporary
pharmaceutical
research.
NAPROC-13
stands
out
as
a
publicly
accessible
database,
providing
structural
13C
NMR
spectroscopic
information
over
25,000
compounds,
rendering
it
pivotal
resource
product
(NP)
research,
favoring
open
science.
This
study
seeks
to
quantitatively
analyze
chemical
content,
diversity,
space
coverage
within
NAPROC-13,
compared
FDA-approved
drugs
very
diverse
subset
NPs,
UNPD-A.
Findings
indicated
that
exhibit
comparable
properties
those
UNPD-A,
albeit
showcasing
notably
array
scaffolds,
ring
systems
interest,
molecular
fragments.
covers
specific
region
multiverse
regarding
physicochemical
UNPD-A
terms
features
represented
by
fingerprints.
Language: Английский
Quimioinformática, Inteligencia Artificial y la Química de Alimentos
Deleted Journal,
Journal Year:
2024,
Volume and Issue:
27
Published: June 12, 2024
La
Quimioinformática
y
la
Inteligencia
Artificial
(IA)
son
disciplinas
con
métodos
que,
actualmente,
contribuyen
al
desarrollo
de
varias
áreas
del
conocimiento
Química,
por
medio
almacenamiento,
organización,
búsqueda
datos
químicos,
el
procesamiento
modelado,
para
generar
información
a
nivel
molecular
las
relaciones
estructura-propiedad
los
compuestos
químicos
existentes
determinar
propiedades
nuevos,
partir
diseño
base
en
un
perfil
deseado.
Todas
estas
técnicas
se
han
utilizado
Química
Alimentos,
lo
que
objetivo
este
artículo
es
analizar
bases
Quimioinformáticos
IA
su
aplicación
estudio
alimentos.
Chemoinformatic Characterization of NAPROC-13: A Database for Natural Product 13C NMR Dereplication
Journal of Natural Products,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Sept. 13, 2024
Natural
products
(NPs)
are
secondary
metabolites
of
natural
origin
with
broad
applications
across
various
human
activities,
particularly
the
discovery
bioactive
compounds.
Structural
elucidation
new
NPs
entails
significant
cost
and
effort.
On
other
hand,
dereplication
known
compounds
is
crucial
for
early
exclusion
irrelevant
in
contemporary
pharmaceutical
research.
NAPROC-13
stands
out
as
a
publicly
accessible
database,
providing
structural
Language: Английский
Cheminformatics Exploration of Structural Physicochemical Properties, Molecular Fingerprinting, and Diversity of the Chemical Space of Compounds from Betel Nut (Areca catechu L.)
Yubing Li,
No information about this author
Xinyue Wang,
No information about this author
Haixuan Sun
No information about this author
et al.
ACS Omega,
Journal Year:
2024,
Volume and Issue:
10(1), P. 1551 - 1561
Published: Dec. 30, 2024
In
this
work,
the
characterization
and
diversity
of
347
compounds
from
betel
nut
(Areca
catechu
L.)
were
analyzed
for
first
time.
The
dataset
(BNC)
was
compared
to
food.
They
in
terms
physicochemical
properties,
scaffold
diversity,
molecular
fingerprints,
global
diversity.
Approximately
48%
BNC
confirm
Lipinski's
Pfizer's
rules.
pharmacological
toxicological
properties
edible
evaluated
based
on
their
composition.
This
work
applied
research
methods
cheminformatics
food
science,
it
provided
theoretical
support
data
research,
development
nut-related
novel
medication,
healthy
products.
Language: Английский