Archive for the ‘protein’ Category

“DNA in a tigh squeeze”

October 16, 2007

Today Rob Phillips (http://www.rpgroup.caltech.edu/) gave a talk titled, “DNA in a tight squeeze: the other life of a macromolecular assembly.”

Phillips et al. study the atomic-level physics of DNA.  Their recent work focuses on DNA loops which are formed when transcription factors bind to regulatory sites.  Specifically, they modified the lac operon such that they can insert sequences of arbitrary length and content between the Oid and O1 sites.   A surprising result is that DNA is happiest to make loops of 75.5 base pair lengths, whereas the persistence length for DNA is 115 base pairs.  I think this result has ramifications for our understanding of the fitness of regulatory regions. I would like to see an experiment which explores evolutionary fitness with regard to loop length between cis-regulatory sites.

Phillips also showed results from his study correlating the osmotic pressure inside a viral capsid to the speed of genetic ejection.  His results show that viruses eject genetic material (into their host cell) very quickly at first.  However, as the inter-viral osmotic pressure declines, the rate of ejection also drops.  Eventually, the pressure reaches a point where no genetic material is ejected at all.  I have several questions about the content of the genetic material which may or may not be ejected.  Does it transcribe into a functional protein?  Or, does this “tail” material contain garbage which can safely be left inside the virus?

I find this research exciting because it intersects physics, chemistry, biology, statistics, and computer science.

(Finally: check-out the VIPER project for atomic-level exploration of viral structures) 

Spectral Network Analysis

August 29, 2007

This video is exciting:

Pavzner and his team address the challenge of determining a protein’s sequence, given mass spectrometry data. This problem is challenging because every protein undergoes translational modifications, and therefore mass-specs actually measure proteins which deviate (slightly) from their non-translated nucleotide sequences.

An unsolved challenge is to correctly infer a protein’s sequence, given mass-spec data. However, we CAN compare mass-specs against a database of existing (and known) mass-specs in order to guess the sequences. This process is computationally expensive because it requires a linear search of the database for every queried mass-spec search key.

Pavzner present a more efficient algorithm for “guessing” a protein’s sequence, given its mass-spectrum. His technique involves constructing a network of spectral data, and then using that network as the basis for a search. This is remarkably faster than traditional database searches. Pavzner, et al, apply this technique to whole-genome spectrometric data, and yield promising results.

My obscure notes:

17:00 – Why is the signal-to-noise ratio reduced “six-fold” ?

18:01 – Look-up reference for “anti-symmetric pass approach” to solving an alignment between two sequences of unequal length. Can we use this storage technique for other information domains: phylogenetic trees? Electroencephalographic data?

28:07 – The use of “snake venom” makes any science project sound cool.


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