Using XML, XPATH and X3D to render protein ribbon models
by Scooter Willis
This presentation will provide an overview of creating ribbon models of
proteins using the XML version of PDB data derived from X-Ray
crystallography or NMR. Numerous open source programs exist to render and
display 3D representations of proteins and are the primary source for
visualization. Traditionally PDB data has been available in complex
legacy flat files which has forced a dependency on a few of these
mainstream programs to work with the 3D structures. For the researcher
who wants to annotate or work with the protein 3D models they have
limited options to modify the models or create their own. The PDB data
has been released in an XML format which allows the use of XPATH to
easily query the appropriate data and build a 3D representation of the
protein. An overview will be provided of key data points in a protein
structure to render 3D models.
X3D is the XML version of VRML which makes it very easy to create complex
3D objects. The techniques required to take protein 3D data to create a
3D ribbon model will be reviewed in detail.
Which 2-D underconstrained mechanisms have a configuration space
that is linear polytope?
by Heping Gao, CISE, UF
In Geometric Constraint Problem, the input is a set of geometric
objects (points, lines, faces and etc.) and constraints (distance,
angles and etc.) between these geometry objects while the ouput is the
existence and/or description of real solutions. Here, our discussion
is restricted to 2-D distance underconstrained systems in which the
only type of constraints are distances between points. By 2-D distance
underconstrained system, we mean a 2-D distance constraint system
whose constrained graph G= satisfies:
(1). |E| < 2*|V|-3;
(2). For any subgraph G'= of G, |E'|<=2*|V|-3.
A 2-D distance underconstrained system may have infinitely many
different 2-D realizations modulo transmission and rotation, so our
task is to decide whether the system has real solutions and describe
the solution or configuration space if there is any. One way to do
that is to add some edges (we call Completion Edge) to the
underconstrained graph to get a wellconstrained graph, and find all
the possible values of the completion edges which makes the input
system have at least one real embedding.
We ask the question, for what type of graphs we can describe the
possible values of the completion edges by a fixed set of linear
equations/inequalities(LD) in terms of the given distance values.
Here, by ``fixed'', we mean depending only on the graph and the
chosen completion.
In our talk, we will give the characterization of this type of graphs.
If time permits, we will also show that they turn out to be equivalent
to a well-studied class of graphs arising in other apparently
unrelated situations (partial 2-trees, series-parallel graphs). Our
proof yields an alternative proof of another known result about these
graphs - showing they are exactly the so-called 2-realizable graphs.
We also study alternative descriptions of the configuration space and
show that loosening the description of the configuration space does
not give a larger class of graphs.
Finally, we give other nice properties of graphs that have this type
of configuration space description - for example, the set of *given*
distance values for which a solution exists is also a linear polytope.
Tracking three-dimensional motion in
the heart using zHARP
by Jerry L. Prince, Johns Hopkins
Three-dimensional imaging and quantification of heart muscle function
are essential steps in the evaluation of heart disease. Tagged
magnetic resonance imaging noninvasively places a pattern of
magnetization in the body that facilitates tracking the heart muscle
using postprocessing algorithms. zHARP uses both tag and phase encode
pulses in order to encode the motion of all the points in an image
slice; images are then acquired in no more time than it takes to
acquire a standard CSPAMM image sequence. Postprocessing
unambiguously tracks the three-dimensional motion of every point in an
image plane through an entire image sequence. Tracked points do not
experience errors due to phase inhomogeneities in the receiver coils
and have minimal artifacts from tag pattern spectral peak
interference. Experimental results will be shown, including a phantom
validation experiment comparing zHARP to phase contrast imaging and an
in vivo study of a normal human volunteer. These results demonstrate
that the simultaneous extraction of both in- and through-plane
displacements from tagged images is feasible.
Intuitive Methods for 3D Shape Deformation
by Scott Schaefer
Rice University
Deformation is a key component in many applications including virtual surgical simulation and the animation of digital characters in the movie industry. Previous deformation methods have led to non-intuitive ways of specifying the deformation or have been too expensive to compute in real-time. This talk will focus on three methods we have developed for creating intuitive deformations of 3D shapes. The first method is a new, smooth volumetric subdivision scheme that allows the user to specify deformations using conforming collections of tetrahedra, which generalizes the widely used Free-Form Deformation method. The next technique extends a fundamental interpolant in Computer Graphics called Barycentric Coordinates and lets the user manipulate low-resolution polygon meshes to control deformations of high-resolution shapes. Finally, the talk will conclude with some of our recent work on creating deformations described by collections of points using a technique called Moving Least Squares.
Biomolecular Motors: Engines for Nanotechnology
by Henry Hess, Dep. of Materials Science and Eng, UF
Active, energy-consuming transport processes on the micro- and nanoscale are
widely used by nature in biological nanofluidics and the self-assembly of
geometrically complex subcellular structures and materials.
Biomolecular motors, such as
the motor proteins kinesin and myosin, play a central role in many of these
transport and assembly processes, since they are able to efficiently convert
chemical energy into mechanical work using ATP as fuel.
Mimicking these biological active transport processes can lead to major
advances in nanotechnology by enabling a variety of new approaches to sensor
design and materials assembly. However, critical components, such as
molecular motors with high functionality, cannot be synthesized at this
point. We have chosen to circumvent this roadblock by building hybrid
devices, which integrate nanomachines of biological origin into synthetic
environments.
For example, we designed "molecular shuttles", a nanoscale
transport system integrating kinesin motor proteins as engines and
filamentous microtubules as cargo-carrying units. Critical advances have
been made in guiding these shuttles along microfabricated tracks,
controlling their geometry, speed, and selectively loading them with
cargo, and we will describe our progress regarding these technical
including geometric aspects.
These advances allow us to tackle a number of new applications, most notably
the bottom-up assembly of new nanostructures and the integration of
molecular-scale transport into biosensing. With regard to assembly, the
combination of reversible cross-linkers and directed force generation leads
to the formation of geometrically highly regular mesoscopic
structures.
H. Hess, G. D. Bachand, and V. Vogel. 2004. Powering Nanodevices with
Biomolecular Motors. Chemistry - A European Journal, 10:2110-2116.
On Low Dimensional Core-sets
by Sariel Har-Peled University of Illinois at Urbana-Champaign (UIUC)
In this talk we will review some low-dimension geometric
approximation algorithms that work by extracting a small subset of the
input, and performing the computation on this small subset. Such subsets,
referred to as coresets, had emerged as a powerful tool, and we will
survey some of the resulting algorithms and future challenges associated
with coresets.
Modeling macromolecular flexibility and plasticity
by Holger Gohlke, Dept. of Biological Sciences, J. W. Goethe University, Frankfurt, Germany
Protein flexibility is important for a wide range of biological phenomena, such as enzymatic reaction
and control. In the case of protein-protein or protein-ligand complex formation, flexibility of the binding
partners provides the origin for their plasticity, enabling them to conformationally adapt to each other.
Equally important as flexibility per se are changes in the flexibility upon complex formation. Thus,
analyzing flexibility and modeling plasticity of macromolecules without having to do expensive
calculations is of great importance. Here, flexibility concepts grounded in rigidity theory [1] are applied
and further developed to investigate flexibility changes upon macromolecular association and to model
conformational variability in macromolecules.
Initially, for validation purposes, the influence of protein-protein complex formation between H-Ras and
the Ras-binding domain of C-Raf1 on the intrinsic flexibility of both binding partners has been
investigated using molecular dynamics simulations and a network analysis based on graph theory [1].
Encouragingly, convincing agreement is found, although the computational time requirement of the
network analysis is several orders of magnitude smaller than for the simulations [2].
Second, we present a method for rapidly estimating vibrational entropy changes upon macromolecular
complex formation using results from the network analysis. Changes in the (internal) degrees of
freedom of binding partners provide an entropic contribution that needs to be taken into account when
calculating binding affinities. Currently, normal mode analysis (NMA) is considered to be the ¿gold
standard¿ to estimate these changes. However, NMA is computationally expensive even for
macromolecules of about 5000 atoms. Convincingly, for a data set of 10 protein-protein complexes
with widely varying properties, total vibrational entropy changes as determined by our method
correlate well (r2 = 0.84) with those obtained from NMA, despite only a fraction of computational time
required.
Third, we introduce a two-step approach for modeling macromolecular plasticity. In the first step, the
flexibility of the macromolecule is investigated by a network analysis. Subsequently, applying a block
normal mode analysis, internal motions of flexible regions are modeled using collective variables,
whereas only translational and rotational motions are allowed for rigid regions (¿blocks¿). Our method
was applied to a set of protein structures for which conformational changes upon binding have been
observed. Predicted motions agree well with those found in experiment, both in terms of direction and
(relative) magnitude of the motion.
Finally, an approach for fully-flexible protein-ligand docking will be presented that is based on an
elastic grid representation of interaction fields inside the binding pocket of potential drug targets.
[1] Jacobs DJ, Rader AJ, Kuhn LA, Thorpe MF. Protein flexibility predictions using graph theory.
Proteins 2002;44:150-165.
[2] Gohlke, H, Kuhn, LA, Case, DA. Change in protein flexibility upon complex formation: Analysis
of Ras-Raf using molecular dynamics and a molecular framework approach. Proteins
2004;56:322-337.
[3] Ahmed, A, Gohlke, H. Multi-scale modeling of macromolecular conformational changes
combining concepts from rigidity and elastic network theory. Proteins 2006, in press.
Analysis of the Four-Point Scheme
by Ulrich Reif, Darmstadt University of Technology, Germany
The four-point scheme is the simplest subdivision
scheme for curves which is non-trivial in the sense that it
is not derived from uniform B-splines. In it generalized
form, it involves a tension parameter w by which the
shape of the generated limit curves can be controlled.
In this talk, we present a solution to the notorious problem
how to characterize the set of all such parameters for which
the generated limit curves are C^1.
Alper Üngör
(ungoratcisedotufldotedu)
August 2005