Here some of the figures of my grant.

Zinc fingers is typically a domain of about 60 amino acids that fold around one or more zinc ions and is found in over 400 eukaryotic proteins, many of which are involved in the regulation of gene expression and in the maintenance of chromatin structure. Zinc fingers typically show a C4HC3 signature (four cysteines, one histidine, three cysteines) with characteristic cysteine spacing and with additional conserved residues, most notably a tryptophan or other aromatic amino acid preceding the final cysteine pair. Studies have suggested a role for zinc fingers as nucleosome interaction determinants. However their functions are still elusive and controversial, as a variety of functions have been suggested, including phosphoinositide binding and E3 ubiquitin ligase activity. In addition to their role as a DNA-binding module,  zinc finger have been shown to mediate protein-protein and protein-lipid interactions as well.

What about the electrostatic surface properties of zinc-finger domains? Here an example with the models of the 4 zinc-fingers of one of the histone methyl-transferase I’m working on. On the figures, blue is positively charged, and red is negative. The large positive (blue) area will bind to the DNA. But, on the other face, there is room for binding to some positively charged partners. Fascinating!

What happened to Chang et al., is that they were working with some wrong electron density maps because of a gross error made early-on during the project pipeline. The culprit was an in-house data reduction program that switched critical column of data. Because of this error, they build/trace various proteins with the “wrong” hand.

Brian Matthews commentary is a solid X-ray crystallography 101 lesson. A lot have been said and written about Chang et al. mistake and their consequences. But, Brian Matthews point out that nowadays we are seeing an ever-increasing use of “black-box” procedures for structure determinations. The rapid development of easy to use X-ray crystallography softwares along with massive computing power render the structure determination fairly easy for one with limited X-ray crystallography knowledge. Solving a structure can be fairly straightforward but it can easily become a tricky task. In any cases but especially in tricky cases, one needs to be extremely cautious about the validity of the maps. Brian Matthews gave us a great lesson about the various checking we all should do when dealing with problems encountered by Chang et al.

X-ray crystallography is like anything else, it is an art. It requires experience, failures, learning from failures and constant knowledge update. Like everything else in Science, it is a grave mistake to assume that we master all the whereabouts of a technology/methodology. I guess, Chang et al. learnt it the hard way. However it raises another question: Shall we seek advice from a peer to help solving a problem in case of dealing with a very hot project? All the 5 retracted papers were all hot projects…

The take home message from this is to be über-cautious and don’t take nice looking maps for granted…

A week after I was interviewed by the committee 21 “Molecular and structural features underlying biological functions” and the fun began. I found what I hate the most among tenured-track faculties in France: very narrow-minded person, rude for no reasons, not listening to me at all…well pathetic people for most of them. The icing on the cake was when I was explaining my current project in the US about the molecular modelling of protein (funded by the NIH). I am a crystallographer but I am currently doing protein-modeling stuffs. The committee was obviously a group of hardcore old-school experimentalists and they violently told me that it is bullshit..meaning protein modeling is bullshit…. should I laugh now and tell them they are wrong, narrow-minded and stupid or should I save that for latter…My current research in protein modelling is all about models-validation with an experimentalist (X-ray crystallography) point of view!! The committee 16 was pleased with that, so why did you guys from the 21 didn’t get that?? Maybe I wasn’t clear enough. That’s must be the reason (sarcasm). 

Some of my friends who went through this hassle before me in different committee experienced the same fun. Awesome ! In my case, I guess it was just a bad experience on that one. But, don’t get me wrong. Working in France at a CNRS or INSERM lab is cool. You don’t get much salary compared to the US, but you do get plenty of vacations, a stress-free working environment (please don’t tell me you are under stress right ?) and if you move your ass a little, you can get some grant money to do good research. But you might end-up working with some people with this typical French narrow-minded mentality where they expect you to fall into a specific old-fashion category. If you are a little bit too atypical you are over.

This being said, it leads me to think: What the heck am I applying for positions at the CNRS or INSERM anyway? right ? Do I want to work with this kind of people? I feel so much better working in the US in every possible ways. Then now, ask yourself why so many of us leave France after graduating with a PhD and never come back in the French academia system ?

Those questions have been bugging me for the last couple of weeks. Ok, I don’t pretend that my papers are among the greatest ever published, however, the data I present are genuine and I always try to have a thorough analysis of a given question.

I’m writing this, because lately I came across a lot of papers that just garbage inaccurate to me. In no specific order, it can be: recycling old data into new one, controls experiments are missing or inaccurate, data too perfect to be true, writing a whole paper with experiments that just bring nothing new to the field, among others….

There is so many journals out there that it is somewhat easy to get a paper publish. If it failed to one journal, we just have to send it to another journal with a slightly lower impact factor. Even if in general, a correlation exists between impact factor and quality however, high impact factor journals are not immune of bad papers.

Nowadays, it is so tough to get funded that it had raised the bar very high in term of publications. A PI and a lab have to produce a lot of papers. Unfortunately it tends to seriously impact the quality, enhance the tendency of over-interpreting the data or fake them. I think the whole thing is definitively not moving in the right direction and that’s made me sad/angry.