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protein-ligand interactions

I was reading a review that came in Structure’s recent issue. The article is titled “Protein Modeling: What Happened to the ‘Protein Structure Gap’?” [1] It was very interesting to read, especially the section called “Know your limits“.

Wouldn’t it be a great idea to put all these homology modeled structures that were published (of course, in a peer-reviewed journal) in one place? For some researchers, homology models are usually considered with a pinch (sorry a bucket!) of salt. Still, why should I spend time on modeling the protein, if a model exists already?

ResearchBlogging.orgI have been in situations, where I would come across a paper that describes a structure that was homology modeled and made conclusions from that. Usually, my first stop is at ModBase. Would the structure in ModBase is exactly as the model discussed? So I would scurry to find the coordinates of it in the supplementary materials or in the respective lab website. And, I would not always be lucky. That would start an awkward journey of contacting the authors and explain my ulterior motive of looking at the structure. (Sometimes, I would think the authors must be misunderstanding my motive as to find faults. No! I am not that bad! ūüôā )

Enter Protein Model Portal (PMP) [2] in the picture and the Model archive (currently in beta version). In PMP, one can give a query and get a list of structures (experimentally determined and modeled) to view. In case of only modeled structures, the structures from ModBase, Swissmodel are also listed. The next step is where it gets interesting. After selecting the radio buttons against each structure, one can compare the structural variability between the structures.There are other features in the website that tells the reliability, parameters and constraints of the model.

Below is a screenshot of a query protein of my current research in PMP (http://www.proteinmodelportal.org/)

Screen Shot 2013-09-04 at 5.14.38 PMModel archive, on the other hand, provides a DOI for each model deposited, exactly as in PDB. This is important since, if a peer-reviewed publication had a homology modeled structure, it needs to be made available to the public and other scientific colleagues to look at it. The argument is the same that was put across journals when PDB was founded. If you are publishing a paper with a homology modeled structure, deposit in Model archive and mention it in the manuscript. That the structures will be available to start working form and add more parameters and constraints is great!

The archive is still being established and I think it will take some time before this also becomes a crucial step in publishing articles on homology modeled structures. Thanks to Prof. Torsten Schwede, here is a screenshot of the two homology models of DapE [4] that were deposited in Model archive and the paper describing the protein was published in Metallomics [5] Click on this link to access the models.

Screenshot of DapE homology models deposited in Model archive

Screenshot of DapE homology models deposited in Model archiveDo spread the word about Model archive.

Friends, I don’t want to sound patronizing, but next time you model a structure, you realize that the homology models had some contribution in the conclusion, do think of submitting the structures to Model archive. Plus, mention a sentence as to where the models have been uploaded to. ūüôā

Since, this is a community based effort and if you have any suggestions/comments do send them to Prof. Torsten Schwede (http://www.biozentrum.unibas.ch/research/groups-platforms/overview/unit/schwede/)

I will touch more on homology modeled structures on the next post. Adios amigos!

References:

  1. Torsten Schwede (2013). Protein Modeling: What Happened to the ‚ÄúProtein Structure Gap‚ÄĚ? Structure, 21 (9), 1531-1540 DOI: 10.1016/j.str.2013.08.007
  2. Haas J, Roth S, Arnold K, Kiefer F, Schmidt T, Bordoli L, & Schwede T (2013). The Protein Model Portal–a comprehensive resource for protein structure and model information. Database : the journal of biological databases and curation, 2013 PMID: 23624946
  3. Schwede T, Sali A, Honig B, Levitt M, Berman HM, Jones D, Brenner SE, Burley SK, Das R, Dokholyan NV, Dunbrack RL Jr, Fidelis K, Fiser A, Godzik A, Huang YJ, Humblet C, Jacobson MP, Joachimiak A, Krystek SR Jr, Kortemme T, Kryshtafovych A, Montelione GT, Moult J, Murray D, Sanchez R, Sosnick TR, Standley DM, Stouch T, Vajda S, Vasquez M, Westbrook JD, & Wilson IA (2009). Outcome of a workshop on applications of protein models in biomedical research. Structure (London, England : 1993), 17 (2), 151-9 PMID: 19217386
  4. http://www.modelarchive.org/doi/10.5452/ma-a1nb6
  5. Narasimha Rao Uda, Grégory Upert, Gaetano Angelici, Stefan Nicolet, Tobias Schmidt, Torsten Schwede, & Marc Creus (2013). Zinc-selective inhibition of the promiscuous bacterial amide-hydrolase DapE: implications of metal heterogeneity for evolution and antibiotic drug design
    Metallomics DOI: 10.1039/c3mt00125c

Listen to the classic song while reading the post!

If you were born in the 1960’s and if you happen to do The Twist with your partner your heart would of course be racing!¬†Thanks to¬†G protein-coupled inwardly-rectifying potassium channels¬†(GIRKs) your heart can beat back to normal levels. Ironically, the protein does a “twist” to slow down the heart. Go Figure!

GIRK is basically a potassium ion-transporter and found in cardiac cells. It regulates the membrane voltage after the GPCR activated G-beta and G-gamma bind to the transporter.

In this groundbreaking work, three structures were used to understand the dynamics of the transporter.

  • The normal GIRK transporter
  • The GIRK bound with G-gamma, and
  • A GIRK mutant (R201A) that is always in the open conformation.
13705779702211

GIRK wildtype (201 position shown as magenta spheres) ions as spheres. PDB id: 3SYO

The mechanism of transporting the K+ ion across the membrane starts after the G-beta and G-gamma bind to GIRK, and thus getting a twist of 4 degrees clockwise (looking from inside the cell). This is observed as a highly energetic, but stable conformation. In other words, a “meta-stable” form. It is just waiting for a “spark” (binding of Na+ ion), due to which it twists further to open the channel to a wider 9 degrees, thereby allowing the K+ to be transported across the membrane.¬†

This twisting and untwisting continues till the resting potential (Nernst K+) is reached, thus slowing the firing frequency in pacemaker cardiac cells, resulting in slower heart rate.

The coordinates of the GIRK-G-gamma complex will be released soon. LINK

ResearchBlogging.org

References:

  1. Whorton, M., & MacKinnon, R. (2013). X-ray structure of the mammalian GIRK2‚Äďő≤ő≥ G-protein complex Nature DOI: 10.1038/nature12241

Image courtesy: Google

Not always, but sometimes one wants to flatten the interactions between a protein and a ligand. The aim is to unclutter the three-dimensional (3D) information to a 2D image. With such visualizations, the advantages is that one gets to see the various interactions without any of them getting buried, and concentrate on the crucial ones that are the key to protein-ligand interactions. The situations where these 2D representations are used are broadly of two areas:

  1. Plotting the interactions of protein-ligand complexes in the existing data (from PDB database)
  2. Plotting the interactions between a protein and a potential drug/small molecule from a molecular docking result. Again, the input could be from a single small molecule docking or from a virtual screening.

In this post, we will see three tools that help us in achieving the goal of plotting protein-ligand interactions. ResearchBlogging.org
LIGPLOT – For many years, Ligplot (1) has been the choice for plotting 2D interactions. Infact, the database pdbsum makes ligplot images for a given protein-ligand interactions. The main two things shown are the hydrogen bonds and hydrophobic interactions.

Hydrogen bonds are indicated by dashed lines between the atoms involved, while hydrophobic contacts are represented by an arc with spokes radiating towards the ligand atoms they contact. The contacted atoms are shown with spokes radiating back.

LIGPLOT

PoseView – This is a new tool that came out two years ago (2). It has Ligplot-like image generation but it has more features than Ligplot.

The 2D depiction shows hydrogen bonds as dashed lines between the interaction partners on either side. Hydrophobic interactions are illustrated as smooth contour lines between the respective amino acids and the ligand.

Recently PDB database incroporated poseview with the structures that are present. So, one can get the 2D plots straight away from PDB itself in the Ligand section of each protein, for example here. The web-interface for PoseView can be accessed here.

PoseView

BINding ANAlyzer (BINANA) – This is probably the most recent protein-ligand representation tool (3). Although, not exactly a 2D plotting tool, it has more features than Ligplot or PoseView, namely it can plot electrostatic interactions, pi pi stacking, cation-pi interactions, and more. The only downside is that it needs the input in .PDBQT format. This can be obtained via AutoDock Tools. The output can be visualized via VMD, thus making the 2D back into 3D bu with distinguishable features.

BINANA

References:

1. Wallace AC, Laskowski RA, & Thornton JM (1995). LIGPLOT: a program to generate schematic diagrams of protein-ligand interactions. Protein engineering, 8 (2), 127-34 PMID: 7630882

2. Stierand, K., & Rarey, M. (2010). Drawing the PDB: Protein‚ąíLigand Complexes in Two Dimensions ACS Medicinal Chemistry Letters, 1 (9), 540-545 DOI: 10.1021/ml100164p

3. Durrant, J., & McCammon, J. (2011). BINANA: A novel algorithm for ligand-binding characterization Journal of Molecular Graphics and Modelling, 29 (6), 888-893 DOI: 10.1016/j.jmgm.2011.01.004