Shaw was once a computer scientist at Columbia, then he went off to make some billions on Wall Street. (He was introduced to the Harvard audience as “King Quant.”) He has now turned to computational molecular biology, setting up his own lab and building a series of special-purpose computers designed for molecular-dynamics simulations. The machines are called Anton, in honor of Leeuwenhoek. Shaw’s group has built eight of them so far, each with 512 processors. A kiloprocessor model is expected to come on line in a few weeks.

http://bit-player.org/2010/a-molecular-millisecond

In the case of DNA structures, the design is guided by the desired geometry of the product, and the binding is assured simply by Watson-Crick pairing. You know this, of course, since it’s what we worked on together at Nanorex, but the principle generalizes to messier problems like the design of protein folds and protein-protein interfaces. Here, computational tools must do a lot more work, but the work consists of searching a combinatorial space of amino-acid sequences and geometry tweaks, all with reference to static structures and meeting design objectives for the intended product.
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In this connection, readers with spare machine cycles might want to look at Rosetta@Home; readers with spare brain cycles might want to look at and FoldIt. I’ve enjoyed both, and the Baker Lab is doing state-of-the-art work

The third video of the T4 assembly is a beautiful piece of work but it worries me. We’ll want to engineer protein-based machinery, and viruses will be at the low end of the complexity scale we want to work with. Look how complicated even just a T4 virus is — there are a dozen or more protein species involved, fitting together in complicated ways, with hundreds of copies involved. The design and simulation task to design a new virus would be large. The simulation resources exist in the pharmaceutical industry, but perhaps not elsewhere.

If the pharma industry develops protein machines, all the knowledge will be under patents and other IP protections, and the products will be expensive to the end user. If we can find the necessary simulation resources in academia, there won’t be much profit motive to incentivize development. It would be good to see the rapid development that’ s possible in a closed-source commercial world combined with the openness of an open-source world, but it’s not clear how that would be funded.

An excellent narrated animation of the processes involved in biological productive nanosystems, here visualizing the molecular biology’s most central “dogma”. The video is based on scientific data describing molecular structure and function, showin…