1,130 research outputs found
Structural Dynamics of Free Proteins in Diffraction
Among the macromolecular patterns of biological significance, right-handed α-helices are perhaps the most abundant structural motifs. Here, guided by experimental findings, we discuss both ultrafast initial steps and longer-time-scale structural dynamics of helix-coil
transitions induced by a range of temperature jumps in large, isolated macromolecular ensembles of an α-helical protein segment thymosin β_9 (Tβ_9), and elucidate the comprehensive picture of (un)folding. In continuation of an earlier theoretical work from this laboratory that utilized a simplistic structure-scrambling algorithm combined
with a variety of self-avoidance thresholds to approximately model helix-coil transitions in Tβ_9, in the present contribution we focus on the actual dynamics of unfolding as obtained from massively distributed ensemble-convergent MD simulations which provide an unprecedented scope of information on the nature of transient macromolecular structures, and with atomic-scale spatiotemporal resolution. In addition to the use of radial distribution functions of ultrafast electron diffraction (UED) simulations in gaining an insight into the elementary steps of conformational interconversions, we also investigate the structural dynamics of the protein via
the native (α-helical) hydrogen bonding contact metric which is an intuitive coarse graining approach. Importantly, the decay of α-helical motifs and the (globular) conformational annealing in Tβ_9 occur consecutively or competitively, depending on the
magnitude of temperature jump
Frustration in Biomolecules
Biomolecules are the prime information processing elements of living matter.
Most of these inanimate systems are polymers that compute their structures and
dynamics using as input seemingly random character strings of their sequence,
following which they coalesce and perform integrated cellular functions. In
large computational systems with a finite interaction-codes, the appearance of
conflicting goals is inevitable. Simple conflicting forces can lead to quite
complex structures and behaviors, leading to the concept of "frustration" in
condensed matter. We present here some basic ideas about frustration in
biomolecules and how the frustration concept leads to a better appreciation of
many aspects of the architecture of biomolecules, and how structure connects to
function. These ideas are simultaneously both seductively simple and perilously
subtle to grasp completely. The energy landscape theory of protein folding
provides a framework for quantifying frustration in large systems and has been
implemented at many levels of description. We first review the notion of
frustration from the areas of abstract logic and its uses in simple condensed
matter systems. We discuss then how the frustration concept applies
specifically to heteropolymers, testing folding landscape theory in computer
simulations of protein models and in experimentally accessible systems.
Studying the aspects of frustration averaged over many proteins provides ways
to infer energy functions useful for reliable structure prediction. We discuss
how frustration affects folding, how a large part of the biological functions
of proteins are related to subtle local frustration effects and how frustration
influences the appearance of metastable states, the nature of binding
processes, catalysis and allosteric transitions. We hope to illustrate how
Frustration is a fundamental concept in relating function to structural
biology.Comment: 97 pages, 30 figure
Stochastic and statistical analyses for investigating protein folding kinetics
Tesis doctoral inédita leída en la Universidad Autónoma de Madrid, Facultad de Ciencias, Departamento de Biología Molecular. Fecha de lectura: 12-01-2015Understanding
how
proteins
are
able
to
perform
the
multiple
roles
and
activities
they
normally
do
is
very
important
for
our
understanding
of
life.
How
or
Why
proteins
adopt
particular
conformational
states
that
facilitate
their
functionality
is
still
an
open-‐ended
question.
We
have
made
enormous
strides
of
progress
towards
figuring
out
the
physico-‐chemical
basis
of
this
process
and
in
general
with
our
understanding
of
proteins.
Continuous
efforts
in
experimental,
computational
and
theoretical
approaches
have
enabled
us
to
decipher
the
properties
and
behavior
of
this
class
of
biomolecules
considered
to
be
the
hardest
nut
to
crack
in
the
puzzle
that
is
life.
Now,
we
are
in
a
firm
footing
with
a
solid
theoretical
framework
in
the
form
of
the
Energy
Landscape
Theory
that
offers
the
foundation
on
which
to
build
scaffolds
for
the
excavation
of
the
mysteries
of
proteins.
Computer
Simulations
have
reached
sufficient
speeds
and
resolutions
enabling
us
to
come
at
this
problem
from
a
totally
different
side.
Experimental
approaches
to
study
protein
folding
has
arrived
to
the
arenas
of
capturing
single
molecules
in
action
as
well
as
characterizing
the
crucial
processes
with
ultrafast
time
resolution
techniques.
Convergence
of
these
different
approaches
is
at
the
forefront
now
with
efforts
toward
iterative
verification
of
computational
results
with
experiments
and
replication
of
experimental
results
with
simulations
and
a
resultant
net
mutual
learning.
Towards
this
convergence,
new
methods
and
approaches
of
analysis
are
being
developed
that
enables
quantitative
understanding
of
the
data
be
it
experimental
or
simulated,
offering
and
incorporating
simple
yet
fundamental
views
of
the
underlying
physical
processes.
In
this
thesis,
I
present
two
such
efforts
that
connect
theory,
simulations
and
experimental
results.
Proteins
being
inherently
subjected
to
stochastic
forces
and
motions,
I
combine
stochastic
kinetic
simulations
with
very
simple
models
to
elucidate
and
unravel
their
behavior
and
dynamics
as
tuned
by
their
energetics
and
kinetic
barriers.
How
the
presence
or
absence
of
a
barrier
(even
~
1RT)
marks
a
fundamental
difference
in
the
properties
of
proteins
are
clearly
elucidated
by
analyzing
the
stochastic
trajectories
of
single
molecules.
Firstly,
I
apply
these
simulations
to
study
elementary
helix-‐coil
kinetics
followed
by
the
studies
of
barrier
effects
on
protein
folding.
Simple
stochastic
kinetic
simulations
open
a
window
to
peer
into
the
dynamics
and
behaviors
of
protein
molecules
and
serves
as
a
bridge
between
simple
theoretical
models
and
experiments
and
simulations.
Later,
I
build
a
rigorous
procedure
based
on
maximum
likelihood
analysis
to
extract
conformation
dynamics
from
single
molecule
experiments
on
proteins.
The
method
offers
a
quantitative
way
to
analyze
the
measurements
from
time-‐
resolved
single
molecule
FRET
experiments
that
are
a
leading
tool
in
our
arsenal
to
understand
protein
folding.
By
enabling
to
distinguish
protein
thermodynamics
as
well
as
simultaneously
characterizing
the
dynamics
of
the
underlying
process,
the
method
offers
a
robust
and
powerful
approach
to
interpret
time-‐stamped
photon
trajectory
data
and
identify
the
right
protein
folding
scenario
that
results
in
such
data.
ii
The
second
effort
is
a
statistical
approach
to
making
connections
between
thermodynamics
and
protein
structure.
By
utilizing
the
treasure
trove
of
structural
data
from
numerous
X-‐ray
crystallographic
and
NMR
experiments
available
in
the
Protein
Data
Bank,
we
develop
a
method
for
extracting
entropic
costs
of
protein
folding.
We
first
develop
a
novel
clustering
methodology
for
partitioning
the
torsional
angle
space
of
protein
backbones
that
is
based
on
the
statistics
of
backbone
dihedral
angles
and
reflects
the
natural
preferences
of
individual
amino
acids
to
populate
these
particular
regions.
We
introduce
the
side
chain
contributions
based
on
rotameric
distributions.
Using
a
simple
approach
based
on
statistical
thermodynamics,
we
then
calculate
the
entropy
cost
of
protein
folding
while
calibrating
and
benchmarking
it
extensively
with
experimental
data.
We
obtain
a
high
correlation
(R
=
0.98)
for
the
predicted
and
experimentally
measured
total
entropic
costs
of
folding.
Comparisons
of
per
residue
entropy
costs
obtained
after
eliminating
the
well-‐known
size
scaling
effects
in
protein
folding
establishes
the
high
level
of
signal
in
our
predictions.
Using
this
approach,
we
make
connections
between
a
protein
structure
and
its
thermodynamics
of
folding.
The
structure
based
protein
entropies
are
then
introduced
into
a
model
of
protein
folding
to
improve
its
predictive
capabilities.
These
efforts
combined,
advance
the
recent
attempts
to
build
a
convergence
in
the
application
of
computational
and
experimental
methods
in
expanding
our
understanding
of
protein
folding.La
comprensión
de
cómo
las
proteínas
son
capaces
de
abarcar
los
múltiples
roles
y
actividades
que
desarrollan
es
muy
importante
para
conocer
el
funcionamiento
a
nivel
molecular
de
la
vida.
El
cómo
o
el
por
qué
las
proteínas
adoptan
los
estados
conformacionales
específicos
que
permiten
su
funcionalidad
es
una
cuestión
aún
abierta.
Se
han
logrado
enormes
avances
para
la
resolución
de
las
bases
físico-‐químicas
del
proceso
y
hacia
el
entendimiento
general
de
las
proteínas.
Los
constantes
esfuerzos
experimentales,
computacionales
y
teóricos
han
permitido
descifrar
las
propiedades
y
el
comportamiento
de
este
tipo
de
biomoléculas,
consideradas
como
la
pieza
más
complicada
de
resolver
en
el
puzle
de
la
vida.
Hoy
en
día,
se
han
conseguido
establecer
bases
sólidas
en
el
marco
teórico
a
través
de
la
Teoría
de
los
Paisajes
Energéticos
que
ofrece
un
punto
de
partida
sobre
la
cual
construir
andamiajes
para
alcanzar
el
conocimiento
de
los
misterios
de
las
proteínas.
Las
Simulaciones
Computacionales
han
conseguido
suficiente
velocidad
y
resolución
para
permitirnos
abordar
el
tema
desde
un
punto
de
vista
totalmente
diferente.
Los
abordajes
experimentales
para
estudiar
el
plegamiento
de
proteínas
han
logrado
avanzar
hasta
alcanzar
el
seguimiento
de
moléculas
únicas
en
acción,
así
como
caracterizar
procesos
cruciales
mediante
técnicas
con
tiempos
de
resolución
ultrarrápidos.
Actualmente,
la
convergencia
de
estos
diferentes
abordajes
constituye
la
vanguardia
de
este
área
investigadora,
con
esfuerzos
dirigidos
hacia
la
verificación
iterativa
de
resultados
computacionales
con
experimentos
y
replicación
de
los
resultados
experimentales
con
simulaciones,
con
la
consiguiente
red
mutua
de
aprendizaje.
Hacia
esta
convergencia
están
siendo
enfocados
los
nuevos
métodos
y
abordajes
de
análisis
en
desarrollo.
Estos
permiten
la
comprensión
cuantitativa
de
los
datos
experimentales
o
simulados,
ofreciendo
e
incorporando
visiones
fundamentales
de
los
procesos
físicos
subyacentes.
En
esta
tesis,
presentaré
dos
de
tales
esfuerzos
que
conectan
la
teoría,
las
simulaciones
y
los
resultados
experimentales.
Estando
las
proteínas
sometidas
de
forma
inherente
a
fuerzas
y
movimientos
estocásticos,
he
combinado
simulaciones
de
cinética
estocástica
con
modelos
muy
simples
para
elucidar
y
resolver,
mediante
el
análisis
de
su
energética
y
de
sus
barreras
energéticas,
el
comportamiento
y
la
dinámica
que
presentan.
La
presencia
o
ausencia
de
una
barrera
energética
(incluso
del
orden
de
1
kT)
marca
una
diferencia
fundamental
en
las
propiedades
de
las
proteínas,
hecho
que
es
claramente
elucidado
mediante
el
análisis
de
trayectorias
estocásticas
de
moléculas
únicas.
Primero,
he
aplicado
estas
simulaciones
al
estudio
cinético
de
la
transición
elemental
hélice-‐ovillo,
seguido
por
la
aplicación
al
estudio
del
efecto
de
cambios
de
la
barrera
energética
en
el
plegamiento
de
proteínas.
Las
simulaciones
de
cinética
estocástica
simples
abren
la
posibilidad
de
mirar
de
cerca
la
dinámica
y
el
comportamiento
de
moléculas
proteicas
y
sirven
de
puente
entre
modelos
teóricos
simples
y
datos
procedentes
de
experimentos
o
de
simulaciones.
Posteriormente,
he
creado
un
procedimiento
riguroso
basado
en
un
análisis
de
máxima
probabilidad
para
extraer
información
de
la
dinámica
conformacional
a
partir
de
experimentos
de
molécula
única
de
proteínas.
El
método
ofrece
un
medio
cuantitativo
de
analizar
las
medidas
de
experimentos
de
FRET
de
molécula
única,
técnica
que
se
ha
convertido
en
una
herramienta
puntera
en
nuestro
arsenal
para
entender
el
plegamiento
de
las
proteínas.
Gracias
a
la
posibilidad
de
caracterizar
la
termodinámica
de
las
proteínas
así
como
la
dinámica
del
proceso
subyacente,
el
método
ofrece
una
aproximación
robusta
y
poderosa
para
interpretar
los
datos
de
trayectorias
de
fotones
con
precisión
temporal
generadas
por
una
molécula
proteica
única
e
identificar
el
correcto
escenario
de
plegamiento
proteico
que
produce
esos
datos.
El
segundo
esfuerzo
engloba
la
realización
de
una
aproximación
estadística
para
hacer
conexiones
entre
la
termodinámica
y
la
estructura
de
una
proteína.
Mediante
el
uso
de
la
inapreciable
colección
de
datos
estructurales
procedentes
de
numerosos
experimentos
de
cristalografía
de
rayos
X
y
de
RMN
disponibles
en
el
banco
de
datos
de
proteínas
(PDB),
hemos
desarrollado
un
método
para
extraer
el
coste
entrópico
que
supone
el
plegamiento
de
una
proteína.
En
un
primer
paso,
hemos
desarrollado
una
nueva
metodología
de
agrupamiento
para
dividir
el
rango
de
valores
de
ángulos
de
torsión
de
la
cadena
principal
que
está
basada
en
estadísticas
de
los
ángulos
diedros
de
la
cadena
principal
de
proteínas
con
estructura
conocida
y
que
refleja
las
preferencias
naturales
de
aminoácidos
individuales
para
ocupar
dichas
divisiones.
Hemos
añadido
la
contribución
de
las
cadenas
laterales
de
los
aminoácidos
basándonos
en
la
distribución
de
rotámeros.
Mediante
el
uso
de
aproximaciones
simples,
basadas
en
termodinámica
estadística,
hemos
calculado
el
coste
entrópico
del
plegamiento
de
proteínas,
para
posteriormente
calibrar
y
evaluar
estos
valores
con
datos
experimentales.
Hemos
obtenido
una
correlación
alta
(R
=
0.98)
para
los
costes
entrópicos
totales
del
plegamiento
predichos
y
medidos
experimentalmente.
La
comparación
con
datos
previamente
publicados
del
coste
entrópico
por
residuo
obtenido
tras
eliminar
los
efectos
bien
conocidos
de
escalado
por
tamaño
en
el
plegamiento
de
proteínas
establece
el
alto
nivel
de
señal
en
nuestras
predicciones.
Utilizando
esta
aproximación,
hemos
realizado
conexiones
entre
la
estructura
de
una
proteína
y
su
termodinámica
de
plegamiento.
La
entropía
de
una
proteína
basada
en
su
estructura
ha
sido
posteriormente
introducida
en
un
modelo
de
plegamiento
para
mejorar
su
capacidad
de
predicción.
Estos
esfuerzos
combinados
suponen
un
avance
dentro
de
los
recientes
intentos
de
construir
una
convergencia
entre
métodos
computacionales
y
experimentales
para
expandir
nuestro
conocimiento
sobre
el
plegamiento
de
proteínas
Structure Function Relationship in Hexacoordinate Heme Proteins: Mechanism of Globin X Interactions with Exogenous Ligands and Ligand Accessiblity in Cytoglobin and Neuroglobin
Cytoglobin (Cygb), neuroglobin (Ngb), and globin X (GbX) belongs to recently discovered members of the vertebrate globin family, they carry a heme prosthetic group that can reversibly bind exogenous ligands such as CO, NO and O2. Although the physiological functions of Cygb, Ngb and GbX are still under debate, several possible physiological functions for these proteins were proposed. Cytoglobin was reported to participate in lipid-based signaling and to stabilize the tumor suppressor p53 upon DNA damage, which imply its anti-cancer role. Neuroglobin was shown to interact with α-subunit of the heterotrimeric G protein as well as cytochrome c which indicates a role in cell apoptosis. Both proteins were also proposed to participate in NO metabolism. Compared to the well-known vertebrate globin, hemoglobin and myoglobin, the new members have several distinct structural characteristics. First, unlike Hb and Mb, the distal histidine coordinates with the heme iron at the sixth axial position in Cygb, Ngb and GbX, forming a hexa-coordinated heme iron and thus regulating kinetics and equilibrium constants for exogenous ligand binding to heme. Second, an oxidation/reduction of an intramolecular disulfide bridge which is found in all three hexa-coordinated globins, also modulates affinity for diatomic ligands such as O2 and CO. Additionally, both Cygb and GbX are found to have extended N- and C- terminals with unclear function, although the N-terminal in GbX proposed to be involved in the protein binding to the membrane. The work presented in this dissertation focuses on investigation of the role of internal ligand (distal histidine) and disulfide bridge on structure-function relationships in GbX, in terms of regulating affinity and kinetics for small diatomic ligands. Indeed, we shown a very weak ligand binding to heme iron in GbX, suggesting its district role among heaxa-coordiante vertebrate globins. In addition, the study of conformation dynamics that affect the heme cavity accessibility of Cygb and Ngb by incorporate heme fluorescent analogy ZnPPIX into the protein is also performed. These data shown a high conformational heterogeneity of the distal pocket in hexa-coordiante globins as well as increased accessibility of the heme pocket in Ngb
Unfolding Simulations of Holomyoglobin from Four Mammals: Identification of Intermediates and β-Sheet Formation from Partially Unfolded States
Myoglobin (Mb) is a centrally important, widely studied mammalian protein. While much work has investigated multi-step unfolding of apoMb using acid or denaturant, holomyoglobin unfolding is poorly understood despite its biological relevance. We present here the first systematic unfolding simulations of holoMb and the first comparative study of unfolding of protein orthologs from different species (sperm whale, pig, horse, and harbor seal). We also provide new interpretations of experimental mean molecular ellipticities of myoglobin intermediates, notably correcting for random coil and number of helices in intermediates. The simulated holoproteins at 310 K displayed structures and dynamics in agreement with crystal structures (R g ~1.48-1.51 nm, helicity ~75%). At 400 K, heme was not lost, but some helix loss was observed in pig and horse, suggesting that these helices are less stable in terrestrial species. At 500 K, heme was lost within 1.0-3.7 ns. All four proteins displayed exponentially decaying helix structure within 20 ns. The C- and F-helices were lost quickly in all cases. Heme delayed helix loss, and sperm whale myoglobin exhibited highest retention of heme and D/E helices. Persistence of conformation (RMSD), secondary structure, and ellipticity between 2-11 ns was interpreted as intermediates of holoMb unfolding in all four species. The intermediates resemble those of apoMb notably in A and H helices, but differ substantially in the D-, E- and F-helices, which interact with heme. The identified mechanisms cast light on the role of metal/cofactor in poorly understood holoMb unfolding. We also observed β-sheet formation of several myoglobins at 500 K as seen experimentally, occurring after disruption of helices to a partially unfolded, globally disordered state; heme reduced this tendency and sperm-whale did not display any sheet propensity during the simulations
Phosphorylation of Thr9 Affects the Folding Landscape of the N-Terminal Segment of Human AGT Enhancing Protein Aggregation of Disease-Causing Mutants
The mutations G170R and I244T are the most common disease cause in primary hyperoxaluria
type I (PH1). These mutations cause the misfolding of the AGT protein in the minor allele
AGT-LM that contains the P11L polymorphism, which may affect the folding of the N-terminal
segment (NTT-AGT). The NTT-AGT is phosphorylated at T9, although the role of this event in PH1
is unknown. In this work, phosphorylation of T9 was mimicked by introducing the T9E mutation
in the NTT-AGT peptide and the full-length protein. The NTT-AGT conformational landscape was
studied by circular dichroism, NMR, and statistical mechanical methods. Functional and stability
effects on the full-length AGT protein were characterized by spectroscopic methods. The T9E and
P11L mutations together reshaped the conformational landscape of the isolated NTT-AGT peptide
by stabilizing ordered conformations. In the context of the full-length AGT protein, the T9E mutation
had no effect on the overall AGT function or conformation, but enhanced aggregation of
the minor allele (LM) protein and synergized with the mutations G170R and I244T. Our findings
indicate that phosphorylation of T9 may affect the conformation of the NTT-AGT and synergize with
PH1-causing mutations to promote aggregation in a genotype-specific manner. Phosphorylation
should be considered a novel regulatory mechanism in PH1 pathogenesis.Comunidad Valenciana CIAICO/2021/135
AULA FUNCANIS-UGRERDF/Spanish Ministry of Science, Innovation, and Universities-State Research Agency RTI2018-096246-B-I00Junta de Andalucia P18-RT-2413
ERDF/ Counseling of Economic transformation, Industry, Knowledge, and Universities B-BIO-84-UGR2
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