Archive

Anti-aging drugs, metabolism, and disease

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Since today is my birthday I find myself thinking about aging. I went back and listened to one of the first FIB podcasts. It features Leonard Guarente, who helped start Elixir pharmaceuticals, a company specifically targeting aging and metabolic disease. Here’s a link to the mp3.

Is aging just a disease? Metabolism and aging appear to be very tightly coupled. Even more interesting is how calorie restriction (starvation) has a direct impact on reproduction and lifespan. Dr. Leonard Guarente identified the SIR2 gene 6 or 7 years ago. Sirtuin enzymes (pictured above) are NAD-dependent and activated under special conditions like starvation. The biochemistry suggests that therapies could be possible. Knockout the SIRT1 gene in mice and the quality of life is greatly decreased. Starve any organism from yeast to chimps and they live longer by activating specific pathways. There’s 7 genes in mammals so there’s obviously much left to be understood. Trying to inhibit specific enzymes is pretty common, but targeting pathways and complex signaling in cellular metabolism can be tricky. The signals exist in nature. The technology developed in systems biology and metabolomics could really help answer some important questions in the next 10 years or so.

Avalon pharmaceuticals has a technology for generating pathway signatures, so rather than screening compounds against a single target they claim to be able to target entire pathways. They also have an advanced candidate for solid tumor cancers that’s an IMPDH inhibitor. IMPDH is another NAD-dependent enzyme that I have done a small amount of work on.

WiiMD: Bowling on Big Ben

SC07

SC07 is in full swing in Reno. I promised some details about the PSC booth, more specifically the Wiimote controlled Molecular Dynamics demo. Some credit for this idea should go to Adam Marko, who is now a graduate student at UCSF joining the lab of Andrei Sali.

The real selling point of the Nintendo Wii video game console has been the Wiimote. For those who haven’t experienced one, the Wii Remote is very different from a typical video game controller. It has a built in accelerometer, motion sensing, and optical sensing. It communicates over bluetooth, and best of all it only costs around $50 US. These features work to enrich video games through unique human-computer interaction. The sports games that come bundled with the Wii demonstrate how previously mundane gameplay such as bowling, baseball, and tennis can be a blast with clever interaction design.

In the context of biotech, haptic interfaces could really have a big impact in how biologists, life scientists, and medical profesionals interact with computers and devices. The computer geek in me wants to believe that a keyboard and mouse is the one true way to use a computer but the success of video games consoles, Tablet PC’s, and iPhones are changing the face of computing. Imagine biosimulations which are no longer just scripts, plots, and post-process rendering but rather augmented reality. Where a scientist can use virtual instruments and interact with their simulations in real time.

Before I get ahead of myself, let me explain the demonstration you can see at the PSC booth if you’re attending SC07. It is quite simple to use a Wiimote to replace your mouse on a standard PC. Several months ago we played around with Wiimotes on our workstations, manipulating protein structures in VMD and CHIMERA which are both excellent molecular graphics and modeling programs. In this case the Wiimote just acts as a mouse, and doesn’t really offer much advantage, especially for someone who uses VMD with a mouse and keyboard. Pretty cool, but not very practical for me personally. So the Wii Remotes were left in the drawer until discussion about demos for SC07 arose. That’s when some other PSC heads got involved and the idea blossomed.

VMD is a cool program to use with a Wiimote, but a moving a single protein structure isn’t very interesting. Let’s do a NAMD simulation instead. Better yet, let’s use IMD to have an interactive NAMD simulation. And while we’re at it, let’s run it live on Big Ben (PSC’s 4,000+ processor Cray XT3). After all, Supercomputing is our middlename. The “WiiMD” demo is live at SC07 thanks to key efforts by Nathan Stone, Shawn Brown, and student Jordan Soyke. Unfortunately I could not be there to see the final result, but some work was done with PDIO, a middleware that routes data straight from the nodes of the XT3 to a remote location in real-time. There was also a rewrite of the Wiimote input driver, which Jordan talks about briefly in his blog.

Stop by the PSC booth if you get a chance. I hope to have pictures or video of the demo up sometime soon.

PSC Live! at SC07
WiiMD, interactive molecular dynamics with a wiimote?

And my two favorite blogs have noticed!
scalability.org – Coolest demo I saw today
BBGM – Finally found a reason to buy a Nintendo Wii

Supercomputing 2007

It’s that time of year. SC07 begins in Reno next week, and everyone around here is getting prepared. Unfortunately this is the second year in a row that I can’t attend Supercomputing. Last year I was at CASP and this year we are doing a 2-day structural genomics workshop at UTSA. Apparently I’m not the only one with Supercomputing blues. I will miss the chance to talk with vendors and work the PSC booth, but I at least have a poster and some labmates going to Reno.

While much of the conference is focused on high performance network technologies, there’s some great life science talks worth attending. There’s also a session that grabbed my attention,

High Performance Computing on GPUs with CUDA

where NAMD and NVidia developers will demonstrate MD simulations on graphics processors. Stay tuned for some juicy details about a demo from our booth.

Mathematics vs. Physics vs. Biology

Following up on my previous post about community efforts and collective intelligence. I recreated some figures from my notes on a presentation by Jooyoung Lee. He talked about how we are approaching problems in the sciences.

In mathematics, scientists work together on some fundamental problem A. So there’s community-wide efforts.

mathematics

In physics, scientists work together on problems that are closely related to original problem A. So there’s still community-wide efforts.

physics

Biology is somehow different. In biology, it seems that every scientist is working on their own problem, and some even have more than one!

biology

O’Reilly Book: Programming Collective Intelligence

I love me some O’Reilly books. After recently reading Beautiful Code (I should write a review soon). I am eagerly awaiting a new book I just bought from Amazon called Programming Collective Intelligence.

It was written by Toby Segaran, a developer at Genstruct

“This fascinating book demonstrates how you can build web applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you’ve found it.”

Some of the most successful spots on the web are winning on this exact principle. Google, Facebook, Digg, MySpace, Flikr, Twitter, YouTube, and the list goes on and on. As much as I hate the almost cliched phrase Web 2.0, there is clearly a difference in how successful web applications are designed today as opposed to 5 years ago. We need more community based efforts in biology. Educational efforts like Bioscreencast. Or competitions like CASP which I have participated in. The tools are in place. Given the grand challenges to our health and understanding of life, we can no longer afford to work alone.

A list of my favorite science blogs

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Science blogs are emerging everywhere. The-Scientist did an article about biomed at the PSC in the August issue. They’re now running a ‘Top Science Blogs’ poll which I found through Deepak’s post. Here’s my top 5 list according to my Google Reader trends view

by number of items read:

  1. business|bytes|genes|molecules
  2. What You’re Doing Is Rather Desperate
  3. Depth-First
  4. chem-bla-ics
  5. Propeller Twist

It’s not fair to stop at 5, since there’s so many other great science blogs that I read frequently..

On Nodalpoint

BleedingEdgeBiotech is now listed in the wiki at Nodalpoint thanks to Greg. The community there is fantastic and I am often inspired by the high quality content throughout. There’s even a nodalpoint facebook group that is growing rapidly.

An introduction to allosteric regulation

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A fundamental process of life is the selective and efficient catalysis of chemical reactions by enzymes. Enzymes are usually proteins (ribozymes are one exception), and when these catalysts are chained together they form pathways. Enzyme pathways can be loosely described by their inputs and outputs. An even better abstraction than pathways though is to think in terms of networks. Networks have hubs which are critical to the operation of the network. [Vidal Lab is doing great work in this area of cancer proteomics]

In biology, allosteric enzymes are typically the regulatory elements in a catalytic network. More importantly, interactions distant from the catalytic site can induce changes in activity. One of the first examples of regulated enzyme networks is a system of 5 enzymes in bacteria which catalyze the conversion of L-Threonine to L-Isoleucine. Threonine dehydratase, the first enzyme in the pathway, is specifically inhibited by the end product of the pathway. This is simple feedback-inhibition, where buildup of the end product regulates and slows down the entire pathway by modulating the first step. This simple model illustrates an important aspect of protein interaction. It’s not good enough to simply say that enzyme A “interacts with” enzyme B. We need models that can express things like feedback, messaging, and other more abstracted language about protein relationships.

Compared to genomics, the proteomics universe appears to be pretty messy. Proteins interact in networks with enormous complexity. The challenges for a reverse engineering approach are overwhelming. There is no high-throughput method for reliably characterizing protein functions. Systems Biology is applying simplistic network models, and the Gene Ontology Consortium is working to develop a language for cellular functions. Both of these efforts have much to gain from structural biology.

Further Reading:

Ligand binding and allostery can emerge simultaneously

Is allostery an intrinsic property of all dynamic proteins?

The changing landscape of protein allostery

Google’s Impact on Open Healthcare

I have some strong reservations about data ownership when we talk about a Google-dependent world. However I think the current state of biomedical informatics is begging for the information giant to step into the picture. Deepak over at BBGM linked to some intriguing screenshots of Google Health. My first thought, “It’s about time!”. Health information management is a disaster in the U.S., so maybe Google was afraid of tackling this problem since so much of it is still out of their control.

We shouldn’t have to fill out lengthy forms on paper every time we need health care. We need open health information systems. We need predictive, preventive, and personalized medicine, as described by Dr. Leroy Hood of the Institute for Systems Biology. Health care as I see it today is reactive, meaning it applies some generalized solution only after the problem manifests itself as an ailment. We can do better. It’s an unfortunate situation that physicians deal with lumbering and bureaucratic information systems. Medical records should exist in decentralized repositories with real-time services for care providers as well as for patients themselves.

Ruby on Grids

Eric Rollins did some interesting tests with Ruby. It should be possible to run parallel tasks effectively with DRb. I am going to do some more playing around with this.

The Ruby fanfare on the net seems to be approaching the “multi-core” crisis and several bloggers are talking about Ruby as a language for parallel environments.

Multicore Hardware and the Future of Ruby
Multi-core hysteria and the thread confusion
News for Week 25/2007
Distributed Ruby Workers on EC2