Tag Archives: proteins

Science, a new quality-control pathway in the nuclear inner membrane.

Just a quick post to report a truly amazing paper published on Science just few days ago. The protein production line in cells involves a quality-control system, associated to the ER, dedicated to the elimination of misfolded proteins, and defined as ER-associated protein degradation (ERAD). The ER holds a specific subdomain in the proximity of the nucleus, the inner nuclear membrane (INM). Scientists at the CRG in Barcelona have found a new quality-control system, associated to and specific of the INM. Quantitative proteomics approach in yeast revealed a new ERAD branch, composed by three proteins forming a  complex: the ASI complex. The three proteins, Asi1, Asi-2 and Asi-3 have the function to get rid of misfolded proteins, promote the degradation of functional regulators of sterol biosynthesis and regulate the protein concentration in nucleus. As head investigator and co-author Pedro Carvalho affirms, “(…) this quality control system has two key functions. It gets rid of misfolded proteins and, surprisingly, it also helps prevent the nucleus accumulating proteins that should not be there“. The full article can be found here.

Dealing with Uniprot- Python programming interface.

My thesis is mostly focused on proteins, and be sure that I got really familiar with Uniprot. Uniprot comes out with a strong user interface that ease any approach. Biochemists can easily find what they need as a bioinformatician can set up his scripts to obtain information directly from the database. In fact, Uniprot has a very good programming interface, compatible with all the main programming languages, and very well explained on a detailed official tutorial. To find it, you can click this link, or you can search in google with the query “uniprot programmatically”. To me, it’s been quite complicated to find this page browsing in the website, since Uniprot documentation is huge (and I have no patience for this).

For instance, I have to retrieve a brunch of Helix Turn Helix transcriptional factors in fasta format. I’ve got a text file with one ID per line and must save them as Seq objects from the Bio.SeqIO Biopython module. Quite easy indeed, all the game is on the following function:

import urllib,urllib2

def getseq(ID, extention):
    req = urllib2.Request(url)
    response = urllib2.urlopen(req)
    return response.read()

Please, consider that I still can’t figure out how to display ‘t’ tabs in wordpress,  change the spacing if you’ll ever use this. The response.read() returning value can be managed as a string. One can iterate this in order to print everything on a text file to be parsed with the SeqIO.parse() method. As shown, importing both urllib and urllib2 is mandatory. The amazing thing of uniprot is that the programmatic acces to the website is facilitated by the very simple organization of the database. If you know the ID, you just have to add the file type you need and build a web address with the filetype as extention.

PyMOD, a PyMol plugin for embedding multiple alignments in homology modelling

The project I want to discuss today is probably the best thing that came out from my actual lab in the latest years (Bioinformatics Lab at Biochemistry Department of Sapienza University of Rome). Carried on by Emanuele Bramucci for his Master thesis, PyMOD is a plugin for the famous molecular visualization system PyMol and it has been released in 2011.

It represents a simple and user- friendly bridge between PyMol and other several applications of interest, such as PSI- BLAST, MUSCLE, CEalign, Modeller and ClustalW. Sequence similarity searches, multiple sequence-structure alignments, and homology modelling within PyMOL, as said on the homepage of the project. It is full supported for any OS (Windows, Mac OS and Linux), but not tested on PyMol 1.5 yet.

On the top, the video of a workflow example is embedded. I suggest you to visit the project’s homepage:


and enjoy the video and his delighting blues music. It really worths in any case.



Four billion years old protein 3D structure determined by an Euro- American team. Showing the potential of evolutionary research.

One of the biggest challenges in molecular evolution studies is to gain informations about the evolution of protein tertiary structures. When we try to determine the evolutionary origins of proteins, we basically consider the structure similarities between contemporary proteins, since we don’t generally have enough paleo- materials to analyze. Therefore, we can only abstract a putative model of the ancestors of proteins.

The international team leaded by Sanchez- Ruiz from the spanish University of Granada overcome this problem resolving the x-ray structure of Precambrian thiredoxins. In an earlier paper, Sanchez- Ruiz and his collaborators constructed a phylogenetic tree of thioredoxins- proteins that are present in the three domains of life (archaea, bacteria and eukariotes).

The tree leaded the way for the resurrection of Precambrian proteins in the labotratory and the characterization of their features. In the new study, published on structure the last august 8th,  Sanchez- Ruiz teamed up with Jose Gavira from the Andalutian Institute of Earth Sciences (Spanish National Research Council — University of Granada) to analyze the X-ray chrystal structure of the resurrected proteins. The finidings are simply striking. The present- day thireodoxins are remarkably similar to those that existed 4 billions of years ago, a period really close to the origins of life. This is consistant to the punctuated- equilibrium model of evolution, in wich protein structures changes occur intermittently in short periods, with long periods of conservation.

This work is remarkable because of his capability to show the full potential of theoretical and base- research approaches in biology. The same author underlines it as it follows:

In addition to uncovering the basic principles of protein structure evolution, our approach will provide invaluable information regarding how the 3D structure of a protein is encoded by its amino acid sequence. (…) It could also provide information about how to design proteins with novel structures — an important goal in protein engineering and biotechnology.

For a theoretical biology blog it is very important to remark this. The base research approaches and theoretical contributions play a crucial role for the development of applied fields such as biomedical research and biotechnology.