Kaihsu Tai

The selectivity of K+ ion channels: testing the hypotheses.

How K(+) channels are able to conduct certain cations yet not others remains an important but unresolved question. The recent elucidation of the structure of NaK, an ion channel that conducts both Na(+) and K(+) ions, offers an opportunity to test the various hypotheses that have been put forward to explain the selectivity of K(+) ion channels. We test the snug-fit, field-strength, and over-coordination hypotheses by comparing their predictions to the results of classical molecular dynamics simulations of the K(+) selective channel KcsA and the less selective channel NaK embedded in lipid bilayers. Our results are incompatible with the so-called strong variant of the snug-fit hypothesis but are consistent with the over-coordination hypothesis and neither confirm nor refute the field-strength hypothesis. We also find that the ions and waters in the NaK selectivity filter unexpectedly move to a new conformation in seven K(+) simulations: the two K(+) ions rapidly move from site S4 to S2 and from the cavity to S4. At the same time, the selectivity filter narrows around sites S1 and S2 and the carbonyl oxygen atoms rotate 20 degrees -40 degrees inwards toward the ion. These motions diminish the large structural differences between the crystallographic structures of the selectivity filters of NaK and KcsA and appear to allow the binding of ions to S2 of NaK at physiological temperature.

BioSimGrid: grid-enabled biomolecular simulation data storage and analysis

In computational biomolecular research, large amounts of simulation data are generated to capture the motion of proteins. These massive simulation data can be analysed in a number of ways to reveal the biochemical properties of the proteins. However, the legacy way of storing these data (usually in the laboratory where the simulations have been run) often hinders a wider sharing and easier cross-comparison of simulation results. The data is commonly encoded in a way specific to the simulation package that produced the data and can only be analysed with tools developed specifically for that simulation package. The BioSimGrid platform seeks to provide a solution to these challenges by exploiting the potential of the Grid in facilitating data sharing. By using BioSimGrid either in a scripting or web environment, users can deposit their data and reuse it for analysis. BioSimGrid tools manage the multiple storage locations transparently to the users and provide a set of retrieval and analysis tools for processing the data in a convenient and efficient manner. This paper details the usage and implementation of BioSimGrid using a combination of commercial databases, the Storage Resource Broker and Python scripts, gluing the building blocks together. It introduces a case study of how BioSimGrid can be used for better storage, retrieval and analysis of biomolecular simulation data.

The α7 nicotinic acetylcholine receptor: Molecular modelling, electrostatics, and energetics

The structure of a homopentameric α7 nicotinic acetylcholine receptor is modelled by combining structural information from two sources: the X-ray structure of a water soluble acetylcholine binding protein from Lymnea stagnalis, and the electron microscopy derived structure of the transmembrane domain of the Torpedo nicotinic receptor. The α7 nicotinic receptor model is generated by simultaneously optimising: (i) chain connectivity, (ii) avoidance of stereochemically unfavourable contacts, and (iii) contact between the β1–β2 and M2–M3 loops that have been suggested to be involved in transmission of conformational change between the extracellular and transmembrane domains. A Gaussian network model was used to predict patterns of residue mobility in the α7 model. The results of these calculations suggested a flexibility gradient along the transmembrane domain, with the extracellular end of the domain more flexible that the intracellular end. Poisson-Boltzmann (PB) energy calculations and atomistic (molecular dynamics) simulations were used to estimate the free energy profile of a Na+ ion as a function of position along the axis of the pore-lining M2 helix bundle of the transmembrane domain. Both types of calculation suggested a significant energy barrier to exist in the centre of the (closed) pore, consistent with a ‘hydrophobic gating’ model. Estimations of the PB energy profile as a function of ionic strength suggest a role of the extracellular domain in determining the cation selectivity of the α7 nicotinic receptor. These studies illustrate how molecular models of members of the nicotinic receptor superfamily of channels may be used to study structure-function relationships.

Grid computing and biomolecular simulation

Biomolecular computer simulations are now widely used not only in an academic setting to understand the fundamental role of molecular dynamics on biological function, but also in the industrial context to assist in drug design. In this paper, two applications of Grid computing to this area will be outlined. The first, involving the coupling of distributed computing resources to dedicated Beowulf clusters, is targeted at simulating protein conformational change using the Replica Exchange methodology. In the second, the rationale and design of a database of biomolecular simulation trajectories is described. Both applications illustrate the increasingly important role modern computational methods are playing in the life sciences.

Chapter 12 Molecular Modeling and Simulation Studies of Ion Channel Structures, Dynamics and Mechanisms

Ion channels are integral membrane proteins that enable selected ions to flow passively across membranes. Channel proteins have been the focus of computational approaches to relate their three-dimensional (3D) structure to their physiological function. We describe a number of computational tools to model ion channels. Homology modeling may be used to construct structural models of channels based on available X-ray structures. Electrostatics calculations enable an approximate evaluation of the energy profile of an ion passing through a channel. Molecular dynamics simulations and free-energy calculations provide information on the thermodynamics and kinetics of channel function.

Quality assurance for biomolecular simulations

Contemporary structural biology has an increased emphasis on high-throughput methods. Biomolecular simulations can add value to structural biology via the provision of dynamic information. However, at present there are no agreed measures for the quality of biomolecular simulation data. In this Letter, we suggest suitable measures for the quality assurance of molecular dynamics simulations of biomolecules. These measures are designed to be simple, fast, and general. Reporting of these measures in simulation papers should become an expected practice, analogous to the reporting of comparable quality measures in protein crystallography. We wish to solicit views and suggestions from the simulation community on methods to obtain reliability measures from molecular-dynamics trajectories. In a database which provides access to previously obtained simulations [Formula: see text] for example BioSimGrid ( http://www.biosimgrid.org/ ) [Formula: see text] the user needs to be confident that the simulation trajectory is suitable for further investigation. This can be provided by the simulation quality measures which a user would examine prior to more extensive analyses.

A Web/grid portal implementation of BioSimGrid: a biomolecular simulation database

The overall aim of the BioSimGrid project (www.biosimgrid.org) is to exploit the grid infrastructure to enable comparative analysis of the results of biomolecular simulations. In particular, we present the implementation of current BioSimGrid Web portal. The portal has a SOA (service oriented architecture) framework built on the layer of OGSA (open grid service architecture) and OGSA-DAI (open grid service architecture database access and integration) middleware. The PortalLib has been developed to allow RAD (rapid application development) of portal applications. The portal also integrates PKI (public key infrastructure) and supports two levels of distributed SSO (single sign on): grid certificate-based SSO for high security, and user/pass based SSO for maximal flexibility.

Ion-Blocking Sites of the Kir2.1 Channel Revealed by Multiscale Modeling

The Kir2.1 potassium channel owes its inward-rectifying behavior to blocking by multivalent ions, e.g., magnesium and spermine, which access the channel from the cytoplasm and are thought to bind within the pore. To investigate the pathway followed by these ions from the cytoplasm through the pore, we have used multiscale modeling (via continuum electrostatics calculations, docking, and molecular dynamics simulations) to identify possible binding sites en route. On its way to eventually binding in the cavity, magnesium interacts extensively with Glu299, which lines the pore in the center of the intracellular domain. Interaction sites for spermine are formed by Asp255, Glu299, and Glu224. Entropic factors seem to favor interactions of spermine within the center of the cytoplasmic domain.