PNNL-13501 - Pacific Northwest National Laboratory

Modeling Ras:Ras-Effector Complexes: Key Components of Stress-Signal Transmission
Study Control Number: PN00067/1474
John H. Miller, Tjerk P. Straatsma
Stress responses play a central role in the potential health effects of low-level exposure to radiation and toxic chemicals.
This project addresses a fundamental aspect of cellular stress response, the transmission of signals through lowmolecular-weight
guanosine triphosphate (GTP)-binding proteins and will demonstrate the capability to model molecular
processes that are important for understanding health effects from environmental stress.
Project Description
Environmental health issues involve the transmission of
and response to stress signals at the cellular level. Lowmolecular-weight
GTP-binding proteins play a key
intermediate role in transferring the signals to a
complicated phosphorylation cascade involving the
protein kinase family. The transduction of the signal
involves the interaction of GTP-binding proteins, of
which p21Ras is the most extensively studied, with their
effectors such as the signal generators Raf-1 and PI3K or
the negative regulator GTPase activating protein (GAP).
This project focuses on the computational study of
Ras:Ras-Effector complexes using all atom molecular
dynamics simulations. During the past year, various
molecular dynamics simulations were performed for the
p21Ras and p21Ras:p120GAP complex bound by GTP.
These simulations have shown for the first time that the
GTP binding site of Ras:RasGAP complex may actually
have a configuration different than what is observed in the
x-ray diffraction experiments. Conclusions drawn from
this newly observed configuration agree with and can
explain several key experimental results. The similarity
between p21Ras and the Gα components of
heterotrimeric guanine nucleotide binding proteins
extends the relevance of our project to the much broader
area of signaling through G-protein coupled receptors.
Introduction
A multitude of chemical and physical stimuli regulate the
functions of cells by controlling the activities of a
relatively small number of core signaling units that have
been duplicated and adapted to achieve the necessary
diversity. The G-protein coupled receptor (GPCR) is the
most common of these units discovered so far. The
prevalence of GPCRs makes the heterotrimeric guanine
nucleotide binding proteins (G-proteins) the largest class
of signaling proteins. The signaling mechanism of low
molecular weight GTP binding proteins (p21Ras) is
similar to that of G-proteins in that guanine nucleotide
exchange activates the signal and GTPase activity turns it
off. Like Ras, the Gα subunit exhibits affinity for
downstream signaling proteins only when it binds GTP.
The Gα subunit has a weak GTPase activity that
determines duration of the active state when bound to
downstream effectors. The GTPase activity of Gα is
controlled by the regulators of G-protein signaling (RGS)
that are analogous to RasGAP in their function.
Interaction with RGS proteins greatly enhances the
GTPase activity. The catalytic mechanisms responsible
for the GTPase activities of p21Ras and Gα in the
absence and presence of GAP and RGS, and the GTPase
activity difference between p21Ras and Gα are poorly
understood. In the so-called arginine finger hypothesis, it
has been proposed that the arginine residue (Arg178 in
Gαi1 and Arg789 in RasGAP) that resides in the catalytic
site and points to GTP is the main contributor to the
increase in the GTPase activity. This project investigates
the structural properties of p21Ras and p21Ras:RasGAP
complex using molecular dynamics simulations aiming to
determine the structural factors effecting the GTPase
activity. Such studies allow us to make comparisons with
the Gα system and help to understand the reasons behind
the observed GTPase activity differences.
Approach
Classical molecular dynamics simulations and the
protonation state (pKa shift) calculations were the main
computational approaches used during the past year. The
molecular dynamics simulations used all atom molecular
models. Large unit box sizes were used to better
represent the solvation effects. The necessary software to
pursue the project is available in the NWChem
computational chemistry package developed at the
Laboratory. The relatively large size of the system
requires that the supercomputer facility resources to be
used. NWChem is a massively parallelized code well
suited for using the supercomputation resources at the
Molecular Sciences Computing Facility (MSCF) located
Computational Science and Engineering 141