Posts Tagged Structure

ATP Synthase movie

The proton driven turbine cranking out ATP – beautifully animated.
More background info at http://www.mrc-mbu.cam.ac.uk/research/atp-synthase.

shared by Rajini Rao via google+.

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R-omes aren’t build in a day

where R ∈ {Prote, Interact, Gen, …}

Tommy Carstensen

[…] built a model of DNA out of LEGO bricks (of PDB entry 2DAU, to be precise) to celebrate the 40th anniversary of the PDB. The clip also has educational value, explaining some of the basics of DNA structure and more.

[posted by Gerard J. Kleywegt via pdb-l mailing list (pdb-l@sdsc.edu)] For all those which are under the jurisdiction (=curse?) of the GEMA: the video (mp4) can also be found here.
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New Modeller release – 9.10

Modeller – One of the best approaches to structure prediction – just got an overhaul:

(Modeller) 9.10 is primarily a bugfix release relative to the last public release
(9.9). Major user-visible changes include:

  • Add Python 3 support
  • Add support for Mac OS X 10.7 (Lion)
  • Modeller on 64-bit Macs is now built with Intel Fortran, resulting in a roughly 2x speedup compared to 9.9.
  • Add Unicode support; all filenames should be UTF-8 encoded.

See the Modeller manual for a full change log: http://salilab.org/modeller/9.10/manual/node38.html

by email from Ben Webb, Modeller Caretaker (modeller-care@salilab.org)

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My (first) PREZI-ous


In order to test how alternative ways of presentation work in real life, I’ve created the “backbone” of a lecture on the basics of structural alignment.
The current version of the prezi can be viewed at here/.

The plan is to combine this with a couple of intro-slides (keynote) plus using / demonstrating some “practical” aspects of alignment “life” with pymol and other software (cmview, processing sketches). I guess it’s choosing the right medium for the message, so I’ll include some “real” 3D models and use the black/white board as well – so the prezi gives the overall outline, but does not contain the entire lecture.

So far it has been a smooth and rewarding experience to use prezi, especially since it alows to gather all the concepts on one screen and subsequently put a logical path through it. This results in an interative process by adding / removing items and changing the path accordingly. It really helped because I could start by throwing in all the important concepts I wanted to talk about without a pre-conceived linear order. The ordering is an “emergent property” of the process. Any feedback is very much welcome!

Thanks to Bosco Ho for inspirations (the title is from him), see his post “Structural alignment done right”.

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Speeding up molecular shape comparison

gpGPU acceleration is steadily contributing to progress in the computational LifeSciences, for example in rational DrugDesign. OpenEye scientific software announced a performance-increase of their molecular shape comparison ROCS by about 2-3 orders of magnitude (100x-1000x(!)) using GPUs. With this they won the “Best Show” award at the 2011 BioIT-World.

Now FastROCS processes 2 million conformations per second on a Quad Fermi box.

This enables all vs. all shape comparison across entire compound libraries. Below is an interview with Joe Corkery at the BioIT World, and they also have a couple of interesting posts on their blog.

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Structural impact of cancer mutations

Mapping cancer mutations to protein structures. The epidermal growth factor receptor 2 (ERBB2) is implicated in aggravating tumor growth in breast cancer.

Current sequencing efforts churn out massive amounts of (missense) mutations for a given reference genome – so cancer-cell lines are an obvious and worthy target for these shiny new big guns. Adressing the question of what these mutations are actually doing (wrong) and how they affect structure and function of proteins is not quite straightforward. The problem is that each tumor has a slightly different set of mutations, even parts of the same tumor might not be genetically identical. Are there detectable trends that would tell us more about the molecular mechanisms involved?

One could speculate about the dominant mode of action in tumor initiaition / progression at the molecular scale: For example, mutating a small, hydrophobic amino-acid in the core into a big, charged one might screw up the entire structure, rendering the protein inactive (loss-of-function). Alternatively, one could imagine how mutations at the surface alter binding affinity / specificity and cause havoc in the downstream signalling and regulatory pathways (gain-of-function).
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Molecular Dynamics Simulation for Drug Design

comparison of x-ray structures (blue)results of MD simulation (red) of villin (A) and FiP35 (B).

 

In a preview of his upcoming keynote at CHI (Cambridge Healthtech Institute) and Bio-IT World’s Eleventh Annual Structure-Based Drug Design conference, David E. Shaw, Chief Scientist of D. E. Shaw Research, talks with Bio-IT World editor Kevin Davies about a specialized supercomputer, called Anton, that has simulated the behavior of proteins for periods as long as two milliseconds. Excerpts from some of these simulations, showing events such as drugs finding their own binding sites, will be shown during his upcoming keynote address – “Millisecond-Long Molecular Dynamics Simulations of Proteins on a Special-Purpose Machine.”

As a sneak preview to the keynote, the Podcast “Anton: Molecular Dynamics Simulation for Drug Design” is available for download at http://bit.ly/mutTaM, for full details see http://bit.ly/ktxLs0.

In the podcast, D.E. Shaw discusses the combination of improvements in hard- and software that enabled them to go for such long simulations – “… many of the kinds of phenomena that are most interesting from the viewpoint of drug binding take place over longer timescales than was previously possible, even on the worlds fastest supercomputers to simulate“. The co-development of algorithms and specialised hardware results in Anton being a machine that is “so highly specialised that it wouldn’t be very useful for pretty much anything else“.

The podcast-links were posted on LinkedIn by James Prudhomme, Marketing Manager at Cambridge Healthtech Institute (CHI), hence this post should be marked as “advertisement” and treated (pretty much like anything else) with caution and a criticial mind. On the latter, I recommend Bosco’s excellent article “Thousands of hours of Molecular Dynamics saves you minutes of a Monte Carlo calculation” and more recently, “Purity in the atomic force-fields of molecular dynamics simulations“.

References: Here is a link to the article in science
Science 15 October 2010: Vol. 330 no. 6002 pp. 341-346 DOI: 10.1126/science.1187409

and to the full list of D.E. Shaw publications

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