176 research outputs found
A new polymorphic material? Structural degeneracy of ZrMn_2
Based on density functional calculations, we propose that ZrMn_2 is a
polymorphic material. We predict that at low temperatures the cubic C15, and
the hexagonal C14 and C36 structures of the Laves phase compound ZrMn_2 are
nearly equally stable within 0.3 kJmol^{-1} or 30 K. This degeneracy occurs
when the Mn atoms magnetize spontaneously in a ferromagnetic arrangement
forming the states of lowest energy. From the temperature dependent free
energies at T approx 160K we predict a transition from the most stable C15 to
the C14 structure, which is the experimentally observed structure at elevated
temperatures.Comment: 4 pages, 3 figure
Protonation States of Remote Residues Affect Binding-Release Dynamics of the Ligand but not the Conformation of apo Ferric Binding Protein
We have studied the apo (Fe3+ free) form of periplasmic ferric binding
protein (FbpA) under different conditions and we have monitored the changes in
the binding and release dynamics of H2PO4- that acts as a synergistic anion in
the presence of Fe3+. Our simulations predict a dissociation constant of
2.20.2 mM which is in remarkable agreement with the experimentally
measured value of 2.30.3 mM under the same ionization strength and pH
conditions. We apply perturbations relevant for changes in environmental
conditions as (i) different values of ionic strength (IS), and (ii) protonation
of a group of residues to mimic a different pH environment. Local perturbations
are also studied by protonation or mutation of a site distal to the binding
region that is known to mechanically manipulate the hinge-like motions of FbpA.
We find that while the average conformation of the protein is intact in all
simulations, the H2PO4- dynamics may be substantially altered by the changing
conditions. In particular, the bound fraction which is 20 for the wild type
system is increased to 50 with a D52A mutation/protonation and further to
over 90 at the protonation conditions mimicking those at pH 5.5. The change
in the dynamics is traced to the altered electrostatic distribution on the
surface of the protein which in turn affects hydrogen bonding patterns at the
active site. The observations are quantified by rigorous free energy
calculations. Our results lend clues as to how the environment versus single
residue perturbations may be utilized for regulation of binding modes in hFbpA
systems in the absence of conformational changes.Comment: 26 pages, 4 figure
Protecting High Energy Barriers: A New Equation to Regulate Boost Energy in Accelerated Molecular Dynamics Simulations
Molecular dynamics (MD) is one of the most common tools in computational chemistry. Recently, our group has employed accelerated molecular dynamics (aMD) to improve the conformational sampling over conventional molecular dynamics techniques. In the original aMD implementation, sampling is greatly improved by raising energy wells below a predefined energy level. Recently, our group presented an alternative aMD implementation where simulations are accelerated by lowering energy barriers of the potential energy surface. When coupled with thermodynamic integration simulations, this implementation showed very promising results. However, when applied to large systems, such as proteins, the simulation tends to be biased to high energy regions of the potential landscape. The reason for this behavior lies in the boost equation used since the highest energy barriers are dramatically more affected than the lower ones. To address this issue, in this work, we present a new boost equation that prevents oversampling of unfavorable high energy conformational states. The new boost potential provides not only better recovery of statistics throughout the simulation but also enhanced sampling of statistically relevant regions in explicit solvent MD simulations
Computational Approaches and Analysis for a Spatio-Structural-Temporal Invasive Carcinoma Model
Spatio-temporal models have long been used to describe biological systems of cancer, but it has not been until very recently that increased attention has been paid to structural dynamics of the interaction between cancer populations and the molecular mechanisms associated with local invasion. One system that is of particular interest is that of the urokinase plasminogen activator (uPA) wherein uPA binds uPA receptors on the cancer cell surface, allowing plasminogen to be cleaved into plasmin, which degrades the extracellular matrix and this way leads to enhanced cancer cell migration. In this paper, we develop a novel numerical approach and associated analysis for spatio-structuro-temporal modelling of the uPA system for up to two-spatial and two-structural dimensions. This is accompanied by analytical exploration of the numerical techniques used in simulating this system, with special consideration being given to the proof of stability within numerical regimes encapsulating a central differences approach to approximating numerical gradients. The stability analysis performed here reveals instabilities induced by the coupling of the structural binding and proliferative processes. The numerical results expound how the uPA system aids the tumour in invading the local stroma, whilst the inhibitor to this system may impede this behaviour and encourage a more sporadic pattern of invasion.PostprintPeer reviewe
Changes in Dynamics upon Oligomerization Regulate Substrate Binding and Allostery in Amino Acid Kinase Family Members
Oligomerization is a functional requirement for many proteins. The interfacial interactions and the overall packing geometry of the individual monomers are viewed as important determinants of the thermodynamic stability and allosteric regulation of oligomers. The present study focuses on the role of the interfacial interactions and overall contact topology in the dynamic features acquired in the oligomeric state. To this aim, the collective dynamics of enzymes belonging to the amino acid kinase family both in dimeric and hexameric forms are examined by means of an elastic network model, and the softest collective motions (i.e., lowest frequency or global modes of motions) favored by the overall architecture are analyzed. Notably, the lowest-frequency modes accessible to the individual subunits in the absence of multimerization are conserved to a large extent in the oligomer, suggesting that the oligomer takes advantage of the intrinsic dynamics of the individual monomers. At the same time, oligomerization stiffens the interfacial regions of the monomers and confers new cooperative modes that exploit the rigid-body translational and rotational degrees of freedom of the intact monomers. The present study sheds light on the mechanism of cooperative inhibition of hexameric N-acetyl-L-glutamate kinase by arginine and on the allosteric regulation of UMP kinases. It also highlights the significance of the particular quaternary design in selectively determining the oligomer dynamics congruent with required ligand-binding and allosteric activities
Structured models of cell migration incorporating molecular binding processes
The dynamic interplay between collective cell movement and the various
molecules involved in the accompanying cell signalling mechanisms plays a
crucial role in many biological processes including normal tissue development
and pathological scenarios such as wound healing and cancer. Information about
the various structures embedded within these processes allows a detailed
exploration of the binding of molecular species to cell-surface receptors
within the evolving cell population. In this paper we establish a general
spatio-temporal-structural framework that enables the description of molecular
binding to cell membranes coupled with the cell population dynamics. We first
provide a general theoretical description for this approach and then illustrate
it with two examples arising from cancer invasion
Application of parallel liquid chromatography/mass spectrometry for high throughput microsomal stability screening of compound libraries
Forecasting Chinese GDP Growth with Mixed Frequency Data: Which Indicators to Look at?
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