In GIT the source code is distributed – there is no concept of a central source repository. Developers commit their chances to their local GIT systems, with all the advantages of versioning and source code history. Other developers pull code from you if they think that the changes you’ve advertised via your favourite communication channels are interesting. In theory, this allows for a very democratic and evolutionary code development. In addition to being distributed, GIT seems to be very fast when it comes to merging. Linus reports that he does hundreds of full merges per day and nothing take longer than 5 secs.

In practice, as Linus points out in his talk, there will always be one or very few repositories that people pull from – for the Linux kernel it will be Linus’s machine. In CDK it will very likely be Egon’s. Sorry Egon, you’ve got to be online all day

The last sentence already brings me to the point. I wonder if we should give GIT a try for CDK development. The advantages do sound enormous. Ok, there are disadvantage too, such as loosing the central web browsing of the SVN repository on SF. There may be ways around this, as Egon decribed here, but this seems like not using the real thing.

This is a brief impression dump after watching Linus’ talk today and I’m happy to hear your opinions

• Tom Blundell of Cambridge starts with “Exploring Biological and Chemical Space with High-Throughput Crystallographic, Biophysical and Computational Methods: The new Dimensions of Drug Discovery”. Tom starts with a view on a cell, stating its complicatedness or complexity. He points out the large number of crystal structures of drug targets and a lack of success of the pharma industry to make drugs fast and at reasonable cost. Tom then praises high-throughput automation in his research. A large amount of information will become available from projects like the “1000 genomes”. He describes the projects of his Astex company, soaking crystals with small molecule fragments to identify binders. Essentially, the rest of the talks is on innovative approaches to screening of compound libraries against protein libraries.
• Dave Winkler of Monash University, Australia, announces to talk about Complex Systems. Large molecules are brought home into the chemistry domain. He talks about properties of complex systems, such as emergent properties – unexpected properties apprearing from the interactions of many components or agents in complex systems. Dave mentions the role of networks, Gene networks, metabolic networks, protein-protein interaction networks for System Simulation . Dave states that Systems chemistry might simply be the application of Complex Systems Science applied to Chemistry. The level of simulation is essential when modelling emergent properties of complex systems. His groups builds mesoscale models of stem cell cytokine regulatory networks.
• Douglas Kell from Manchester spoke about Drugs and Xenobiotic Transport via Membrane Carriers. He emphasises the difference between a a biophysical approach vs. a mechanistic analysis. Douglas very nicely points out that a huge amount of work still lies in front of us in studying mechanistic properties of the parts to eventually put them together. He mentions ChEBI for the sake unifying chemical names, highlights the problems with literature mining. In his second part of his talk, he spoke about carrier-mediated cellular uptake vs. a lipid-only theory (logP being important here).
• Tim Clark of Erlangen uses Molecular Dynamics studies to look at Signal Transduction. He mentions that when they started seven years ago they did not know if the force fields were good enough and if they could ever simulate the system for long enough to get meaningful answers. The work was on the Tetracylcine Repressor (TetR) . Tetracyline comes into a cell, comlexes with Magnesium, and then docks to the TetR, and off goes the expression of the antiporter which transports Tetracycline out of the cell. TetR can be used to switch on and off genes in eukaryotes and prokaryotes. They were able to run these TetR MD simulations on the 100 nanoseconds time scale. He showed a low-frequency mode visualization of TetR MD yielding an understanding of induction mechanism of TeTR by Tetracycline. The binding pocket properties change enormously after binding, volume for example shrinking by more than 50 percent. What does that say about docking into rigid pockets?

Wednesday afternoon is, as usual, dedicated to a hike. This time, it goes to a castle on a top of a mountain behind Schloss Korb – very nice walk – we did it in 2004 already.

John Warner Backus (1924-2007) was both a person interested in Chemistry as well as a brilliant software engineer and computer scientist.
In the 50s he worked at IBM on a program he called the FORmula TRANslator, which quickly became FORTRAN – without any doubt the most influential programming language in science so far.
My first encounter with John Backus’ work was when listening to the computer science student with whom I shared an apartment during my chemistry studies. The Backus-Naur Form (BNF) – a notation for grammars of programming languages – is part of every computer science curriculum. Later I found it used by Axel Brunger to specify the grammar of the scripting language driving his restrained MD package XPLOR.
John Backus received the Turing Award in 1997 for his work on FORTRAN and on the Bachus-Naur-Form.

I wonder how it would translate into modern day terms and if there are any people out there below the age of 40 who know that the author means by “Trash-80s”.