Design of Biomimetic Antimicrobial Polymers
The SDSC Storage Resource Broker (SRB)
Simulating Emulsion Behavior Using NCSA's SGI Origin2000 Supercomputer
SDSC Science Interest Group
EOT-PACI

Design of Biomimetic Antimicrobial Polymers

Michael Klein, Robert Doerksen in collaboration with William DeGrado et al.

In this study, reported in Proc. Natl. Acad. Sci, 99, 5110 (April 16, 2002), Michael Klein's group at University of Pennsylvania collaborated with experimentalists at the University of Pennsylvania School of Medicine led by William DeGrado. This team has synthesized a novel family of 'arylamide' polymers that are antibacterial and could eventually be used to treat surfaces to be antibacterial on contact. Potential applications include treated fabrics, in effect an antimicrobial suit. The researchers have applied for patent protection of the technology.

The polymers mimic the structure and function of a class of endogenous defense proteins. These natural peptides have facially 'amphiphilic' structure -- postively charged hydrophilic and uncharged hydrophobic aminogroups segregate on opposite faces of the structure. It's believed thatthis 'amphilicity' accounts for the peptides ability to kill bacteria by attaching to and piercing the bacterial cell membrane.

The Univ. of Penn group and other groups (including Ghadiri of Scripps) have synthesized related peptides. A key advance of the University of Pennsylvania work, however, is that arylamide polymers appear to offer the same antibacterial properties but are much less expensive to produce.

Klein & post-doc Robert Doerksen used the TCS to carry out density-functional calculations to develop accurate torsional potentialsfor the arylamide polymers. The potentials available with packages such as CHARMM proved to be unsuited for these structures, giving inaccurate results in preliminary molecular dynamics runs. With
extensive computations -- 60,000 SUs to generate 14 torsional potentials during the
friendly user period, with efficient runs on 128 processors of Lemieux --
the researchers generated torsional potentials to describe the backbone unit of a
particular arylamide polymer, a potential which they then used to modify the CHARMM torsional potential.

The SDSC Storage Resource Broker (SRB)

Reagan Moore et al.

The data-intensive computing thrust group at SDSC, led by Reagan Moore, is building an integrated national digital library that accelerates the publication of scientific data. This requires the integration of distributed persistent digital archives, hierarchical storage systems, databases, data-handling systems, and digital libraries into integrated scientific information repositories.

One the their most important enabling technologies deployed to date is called Storage Resource Broker (SRB). SRB is client-server middleware that provides a uniform interface for

connecting to heterogeneous data resources over a network and accessing replicated data sets.

SRB, when used in conjunction with the Metadata Catalog (MCAT), provides a way to access data sets and resources from a user's workstation based on their attributes rather than their names or physical locations. SRB provides a uniform programmer interface that can be used to connect to heterogeneous resources that may be distributed and access data sets that may be replicated. SRB is available for several platforms including UNIX and Windows NT Workstations.

Meta data Catalog (MCAT) is a meta data repository system implemented at SDSC to provide a mechanism for storing and querying system-level and domain-dependent meta data using a uniform interface. MCAT provides a resource and data set discovery mechanism that can be effectively used to identify and discover resources and data sets of interest using a combination of their characteristic attributes instead of their physical names and/or locations.

Simulating Emulsion Behavior Using NCSA's SGI Origin2000 Supercomputer

Yuriko Renardy and Michael Renardy et al.

From household products to life-saving medical applications, emulsions improve our daily
activities in countless ways. We coat our hardwood floors with emulsions that add shine and prevent scratches. We keep cream cheese and margarine sealed against bacteria in plastic tubs made from emulsions. We mold emulsions to form intravenous tubes with glasslike clarity through which doctors can spot fluid blockages. Emulsions, stable suspensions of one liquid in another unmixable liquid, are some of the most versatile resources available.

'The experimental study of emulsions dates back to the ancient Egyptians and Babylonians, who mixed oil and vinegar to season their salads. However, the numerical simulation of that process is a more recent event,' explains Yuriko Renardy of Virginia Tech. Renardy, a math professor at the university, leads a group of scientists at Virginia Tech devoted to providing the expertise needed to making production of state-of-the-art emulsions a science.

For instance, the mayonnaise in your refrigerator is an emulsion of vegetable oil in lemon
juice, stabilized by a molecule found in egg yolks. When you put mayonnaise on bread with a knife, the spreading motion causes a process that scientists call shearing. During shearing, lipid globules in the mayonnaise deform, break up, and then coalesce. This drop deformation process resembles a simple version of emulsions mixed on a large scale for industrial use. Industries that use and produce emulsions want to know, if they feed a mixture of liquids with different sized drops into a mixer, how will it look when it comes out? The outcome is what scientists call drop-size distribution.

Imagine you want to make an IV tube. To do so, you must blend two unmixable liquids, each of which has a valuable characteristic, such as transparency and flexibility. After the liquids are blended, poured in molds, and cooled to a solid, the tube formed must espouse both characteristics. In order to accomplish this, you want the drop sizes of each liquid to be small and evenly dispersed. Smaller drops approximate mixing better than large drops because they provide more surface area in contact between the two liquids. They will still be unmixable liquids, but the separate drops will hold together much more securely. A secure emulsion will make the original liquids in the IV tube less likely to separate over time.

Renardy's team which includes another math professor, Michael Renardy, Jie Li, a postdoc, Damir Khismatullin, a research assistant professor, and Mary Ann Clarke, a PhD student, is numerically modeling the drop-size distribution of emulsion drops using NCSA's SGI Origin2000 supercomputer. So far they have used about 200,000 hours on the Origin2000 since the project's inception. The simulations required 32 to 64 processors for the most intense runs.

SDSC Science Interest Group

Girl Scout Science Interest Group 3908 is an ongoing program for 7th to 12th grade girls in San Diego County who have an interest in science. There are no prerequisites to be part of this program and no cost besides a small Girl Scout registration fee. The program consists of girl-planned science activities (including computer science), trips, and speakers in addition to normal Girl Scout activities. Mentoring by a scientist is available to interested girls.

The group is sponsored by the San Diego Supercomputer Center and under the supervision of Rozeanne Steckler and Michael Bailey.

The girls in the Science Interest Group offer a Computer Badge Day once or twice a year for Junior Girl Scouts (grades 4-6). Attendees spend most of a Saturday at the San Diego Supercomputer Center. They complete various exercises to familiarize themselves with the uses of computers in today's world.

They get hands-on experience on desktop computers (Macintoshes) and 3D UNIX-based graphics workstations (Silicon Graphics). They complete various exercises to familiarize themselves with the uses of computers in today's world. At the end of the day, each girl will have earned the Junior Girl Scout Computer badge and will receive the patch.

For more information see http://sciencegroup.sdsc.edu/ .