Rosetta-News

[cappy]

neue minirosetta version

The minirosetta application has been updated to version 1.39. In this version, we added two important applications to minirosetta, docking and protein folding with explicit zinc metal ion. New features have been added to the graphic to show chain colors for a multi-chain protein complex and display metal ions by sphere.

desweitern gabs im journal 2 beiträge von david baker in den letzten tage

We just got good news from the CASP organizers--our results were among the best at casp8 and we have been asked to describe the methods we used -- including all of your work -- at the CASP8 meeting in December. There are a number of evaluations of the performance of the automatic servers at CASP8 available on the web, and comparison of our models to the servers shows that all of your efforts led on average to quite a bit better models. Of course, we don't yet know other "human" groups did on the CASP8 targets--for this we will have to wait for the meeting!

I'm also excited because I've been working on improvements to the energy function which underlies most rosetta@home calculations, and the first tests of the improvements should run on rosetta@home this next week!

und

We have many exciting calculations just starting to run on rosetta@home! If you split your computational resources between several different projects this would be a good time to temporarily increase rosetta@home's share. We are testing many new methods (see Chu's post today about zinc binding proteins for one of them) and we are eagerly examining each new work unit coming back from your computers. I am very excited personally as I'm doing the first large scale test of (what I think are) improvements in the energy function underlying the searches that I've been working on the past few months (these are the work units with "split" in them).

dann weiterhin viel spaß beim knuspern

[cappy]

neue minirosetta version 1.40

The minirosetta application has been updated to version 1.40. This version contains improved protein-protein docking along with small-molecule ligands and the capabilities to do design, where the surface amino-acid residues are allowed to mutate during the simulation. Messages on the scientific aspects will be posted on the message board.

und was aus dem journal

Please see Sarel's post today on protein-protein interface design about to start up on rosetta@home. Sarel is designing proteins to block the action of pathogens like cholera, and we are excited that with your help we can make inhibitors for many proteins causing disease. We are also starting large scale tests of brand new structure prediction methods, including some that I have been developing myself. This is a very exciting time at rosetta@home!

hier noch die beiträge aus dem Design of protein-protein interfaces thread

Hello,

My name is Sarel Fleishman and I've been a postdoc in the Baker lab for the past two years. My project deals with structure prediction and design of protein-protein interfaces and you may have read a few messages from me on CAPRI and structure prediction. Now, I'm very excited to tell you that with minirosetta v1.40 we can do design work using the massive computational power of Rosetta @ Home.

A few words on protein-interface design. The primary challenge in this field is to be able to take a protein target and to design another protein that would bind to it in a specific way. Nature provides us with hundreds of thousands of examples of such protein-binding events. Such events are used for the amplification of signals within and between our cells in processes related to growth and development as well as for recognition, e.g., in the immune system. When such signals go awry, protein interactions become the center of events for uncontrolled cell growth, or cancer. Many pathogenic bacteria and viruses hijack molecular recognition processes to promote their growth and proliferation causing sickness and endangering lives.

These processes being so central to both health and disease it is hardly surprising that being able to manipulate them computationally is a major ongoing goal of molecular biology. Being able to target a protein and bind to it would open the way to novel therapies for a large number of diseases.

We have selected a small number of protein targets for which we want to design protein binders. As an example, one such target that I have been working on is cholera toxin. This protein is a crucial component of the process by which the cholera bacterium causes cells in the gut to excrete large amounts of water, which causes death from dehydration (see the following wiki page for more details: http://en.wikipedia.org/wiki/Cholera). We have developed a computational strategy that allows us to design proteins to bind to the cholera toxin and disable it.

We are now in the process of testing this and similar design methodologies on a number of other targets. But expanding the number of targets we quickly realized that we need a lot more computational resources to adequately address this problem. This is why we have turned to Rosetta @ Home and to you for your help in this exciting project.

The simulations that you will see in protein interface design will be quite different from one another. In each case we tailor the design strategy to the particular protein target, stressing, for instance, the formation of interactions with a specific key region on the protein surface. In general, though, the simulations will involve docking steps, where the protein binder moves with respect to the target and design, where amino acid residues on the surface of the protein binder change in order to better attach to the target. Promising protein designs are synthesized in our lab and tested for binding to the target protein.

I am working on this project with my colleagues Eva and Jacob, and for each target that we test using Rosetta @ Home we will provide background material on the target and why we selected it on this thread.

These design simulations tend to use more memory than many prediction runs (typically at most 800Mb). We will test different ways of reducing this memory load so that our simulations could run on all participating computers in the Rosetta @ Home project, but initially we will only run these simulations on computers that can handle this memory restriction. Please report any problems that you might have with this simulation.

Thank you very much for participating in this project! I'm looking forward to getting feedback and results from you.

und

My name is Jacob Corn, and I'm a postdoc in the Baker Lab, working with Eva and Sarel on the design of protein-protein interfaces. As Sarel mentioned, this is an incredibly important problem, both for basic science and molecular medicine. But it is also an incredibly difficult problem. Without your support, we would never have enough computing power to work on these kinds of projects.

One target that I am attempting to design towards is interleukin 23 (aka IL23). Your body normally uses this protein to trigger the inflammatory response, which is a normal part of your body's immune system. However, if IL23 messages start to run out of control, they can cause serious autoimmune disorders, such as Chron's Disease. You can find more information on IL23 here
http://en.wikipedia.org/wiki/Interleukin_23
and Chron's Disease here
http://en.wikipedia.org/wiki/Chron%27s_disease.

This week you may receive jobs with titles like "IL23p40_p40BrubYhbond_design_jecorn". These design simulations first dock two proteins against each other (one of which is IL23), then try to iteratively optimize the surface of one protein to better match the surface of IL23. Using the results of your calculations, I will the designed proteins and test them for binding to IL23, hopefully producing a new inhibitor to combat runaway diseases caused by runaway IL23 signals.

I'm very excited about this project, and look forward to your feedback.

und noch ein beitrag von sarel aus dem thread protein-protein docking @rosetta

Hello,

Round 16 of CAPRI, the experiment comparing computational docking methods has started recently, and we're excited to test new algorithms. Over the next few days you will see jobs going out where two protein chains are docked with respect to one another. In one of the chains you will see a ligand showing up as an object comprised of spheres attached to one of the protein partners.

Our challenge is to predict the conformation of the two protein partners, and much of the biological data point to the possibility that the two partners should bind close to the ligand. Hence, it was important that we get the modeling of the ligand right for this to work, and we will now be able to test that! We are not excluding other binding possibilities, though, so many of the simulations will dock the two protein partners in alternative sites.

An important issue in protein-protein docking is motion of the backbone of the protein chain. In this round of CAPRI we plan on experimenting with such backbone motion during the docking simulation. So, in some of the simulations that you get, you will see that after the two partners find a particular orientation the backbones wiggle. Such wiggling motion is often observed when protein structures are compared between their bound and unbound states, and it is widely accepted that such motion is a crucial component of protein recognition events.

Finally, these changes should not introduce any new memory restrictions compared to previous docking simulations.

Thank you all for participating!

vllt könnte jemand die sache übersetzen

dann allen noch ein happy crunching

[cappy]

mal wieder was ausm rosetta forum

Hi everyone,
A quick update on computational design in general, and IL23 in particular.

As many people noticed, these design jobs are taking longer and using more memory than most R@H work units. This is because we are working with proteins that are much larger than what you normally fold during an abinitio run. For reference, imagine that abinitio runs are folding a steel chain with 1-inch links, and that the position of each link changes during the course of the workunit. Abinitio workunits then origami-fold about 8 feet of constant chain into a nice, pretty structure.

By contrast, our design workunits are dealing with two chains, each of which is twenty five to fifty feet long. Not only can the whole folded chain move, the positions of each link can shift slightly, *and* we're constantly swapping out links as the simulation progresses! We have twenty different links to play with, and each position on each chain could be any one of the twenty. Our challenge is to figure out how the two chains should lay on top of one another and what link should be at what position to make the the chains best fit together. As you can imagine, all of that takes a great deal of computing power, and about half a gigabyte of memory. We've put a temporary hold on future design workunits until we do a more benchmarking and fix the issues that you've brought up. For example, we are considering restricting design runs to machines with no less than 1GB of RAM.

Now the good news: Thanks to all of your work, the IL23 design project is moving at an incredible pace. Over the last 5 days, you generated half a million potential therapeutics for IL23! That's completely unprecedented for this kind of project, and would have taken me forever to do on our lab computers. So even though it was a somewhat rocky start, you have all made a very significant contribution towards creating an IL23 anti-inflammatory drug. I'm very much looking forward to sifting through all of the potential therapeutics you've designed, and I feel that R@H really holds the key to making this project work.

[cappy]

kleiner text von sarel aus dem thread design of protein-protein interfaces

There has been a lot of interest in this thread, so I thought that I would write a little more about our design strategy and the importance of Rosetta @ Home's computational resources for the project's success. First, our approach in designing a new protein inhibitor to a natural target revolves around the idea that nature provides us with many thousands of diverse examples of protein interactions from which to learn. Studying these interactions in detail, we find that there are many unifying principles, such as the importance of energetic considerations (for more information, see http://en.wikipedia.org/wiki/Van_der_Waals_force). But, beyond these unifying principles it is striking to see just how diverse a phenomenon protein-protein interactions is! A great resource to learn more about the beauty and the implications of protein structures and interactions is the RCSB's molecule of the month feature, and here's one such feature on one of my targets, cholera toxin:
http://www.rcsb.org/pdb/static.do?p=edu ... b69_1.html
As these illustrations and many other examples show, many protein interactions are uniquely optimized to take advantage of the physical interactions between chemical groups on the proteins' surfaces. Additionally, the surfaces of the proteins usually show very high shape complementarity as in the spectacular example provided by the protein that constitutes the majority of our connective tissue, collagen:
http://www.rcsb.org/pdb/static.do?p=edu ... db4_1.html

Building on the idea that Rosetta captures correctly the unifying energetic principles, as evidenced by its successes in structure prediction and many different protein design tasks, we are still faced with the daunting challenge of how to best capture the great diversity encompassed by the protein-interaction phenomenon. In other words, how can we, for instance, find a protein, the surface of which would ideally fit with the surface of our target of choice as in the collagen example above? This is exactly the point where we need all that sampling power that you make available through the Rosetta @ Home project. Given a target protein, such as cholera toxin, we would like to massively test different amino-acid sequences. We would then like to make sure that each such sequence makes good physical sense, shows high shape complementarity, and would provide sufficient affinity. Since each target implies its own set of unique challenges (e.g., its molecular shape is unique), we specifically tailor a different protocol (or sequence of design steps) to each target and we want to test several such protocols for each given target in a trial-and-error way. Multiply all these computationally intensive tasks by the many millions of conformations that we would like to test for our potential binders with respect to the target and you see how it is that only through Rosetta @ Home we can begin to imagine finding a comprehensive solution to this great challenge!

[cappy]

eine news aus dem rosetta journal

Two exciting things today:

First, Rosetta@home is Wikipedia's article of the day for December 1, 2008! Welcome to new participants who learned about our project today!
(we had an unplanned outage this morning, but you can believe we (this means the behind the scenes heroes Keith and David) worked like crazy to get the project back up as fast as possible!).

Second, the CASP8 results are now publicly available! http://predictioncenter.org/casp8/results.cgi.
Your Rosetta@home results are the ones labeled "dbaker" (this is a complete misnomer as I deserve very little credit for any of this). in any event, now you can compare to POEM and other methods, it takes a while to navigate through all of the information now available. If any of you come up with simpler overall summaries please post for the rest of us!

The CASP8 meeting is Dec 3 - 5 and I'll be posting results from the "human expert" evaluators as they come in.

[cappy]

hier die caps 8 resultate sind on

Welcome again to new participants!

I can explain a bit how to look at the results at http://predictioncenter.org/casp8/results.cgi:

In the box near the top that says "all groups" click and choose for example "DBAKER" (your predictions at rosetta@home) or "POEM" or whatever method you are interested in. then inspect the plots that appear on the page. each prediction by each group is represented by a red line, and predictions by the group you selected by a black line. the best prediction is represented by the line that is underneath all the other lines (the height is the distance from the true structure, the x axis, the fraction of the protein considered).
your rosetta@home predictions stand out for a number of targets, particular prediction problems like
T487D4 (target 487 domain 4).

[DersaureFritz]

Und nun fehlt nur noch die Übersetzung!

[Michael H.W. Weber]

Ganz kurz: Auf der angegebenen Seite sind doch für jedes Protein Grafiken angegeben, die anlickbar sind. Dort auf das jeweilige Diagramm klicken, welches dann vergrößert wird. Nun kann man unten eine Checkbox setzen - z.B. bei POEM oder DBAKER (Rosetta). Der Graph wird neu angezeigt und diesmal ist die Strukturvorhersage der angeklickten Argbeitsgruppe von den anderen Linien unterscheidbar dargestellt. Je flacher die Kurve verläuft, desto besser die Strukturvorhersage. Man sieht generell, daß je größer die Zahl der Aminosäuren (x-Achse), desto schlechter die Vorhersagen. Rosetta und POEM kommen ganz gut weg. Ich habe aber nun wirklich noch lange nicht jedes einzelne Protein angesehen, sodaß ich etwas darüber aussagen könnte, welches der beiden Projekte nun das bessere ist... Viel Spaß!

Michael.

[DersaureFritz]

Danke Dir!

[cappy]

so minirosetta gibt es nun in der version 1.45

This update includes fixes to long runtimes for 'relax' jobs, validation errors, check point recovery issues, and numerical instability in hydrogen-bond scoring.

We think we might have fixed the preemption problem so please keep an eye out for this. The "can't acquire lockfile" issue might also be related. If you are having lockfile problems, please make sure there are no other boinc applications running in the same slot. If necessary, turn off the client and make sure all boinc apps are not running, and then restart the client.

die kurze google übersetzung

Dieses Update enthält Updates zu lange Laufzeiten für "Entspannung" Arbeitsplätze, Validierung Fehler, Check Point Erholung Fragen, und numerische Instabilität in Wasserstoff-Bond-Scoring.

desweiteren hat David Baker gestern den Raymond & Beverly Sackler International Prize in Biophysik gewonnen
weitere informationen gibt es hier

http://uwnews.org/uweek/article.aspx?id=45635

ps. sehr interessanter artikel

----------------------------
und noch ein beitrag aus dem thread structure prediction of zinc-binding proteins

Great data mining work, robertniles! Thank everyone for such a wonderful discussion. Definitely all the other metals are our to-do list and we are very excited about introducing for the first time metal into Rosetta structure modeling. As mentioned in my original post, Zinc is one of the most abundant metals found in natural protein molecules, playing both important structural (stabilizing proteins) and catalytic (helping realize protein functions) roles. A lot of zinc-binding proteins are involved in DNA binding and recognition and the most popular structure motif is referred as "zinc finger". For example, an enzyme called Integrase in HIV virus has a structural domain that contains zinc-binding sites and is believed to be responsible for multimerization of this enzyme. To understand how the zinc binding affect this process will certainly help us find new insights to fight against HIV. I am glad to see the last post mentions matrix metalloproteases because I am soon to join a new lab which have done a lot of work in characterizing unknown MMPs in human proteomics which are believed to be cancer related. I am very grateful to everyone's contribution to our project and I will surely keep everyone posted when there is any exciting results we will obtain in future.

die google übersetzung

reat Data-Mining-Arbeit, robertniles! Ich danke allen für eine solche wunderbare Diskussion. Definitiv alle anderen Metalle sind unsere To-do-Liste, und wir sind sehr begeistert über die Einführung zum ersten Mal in Metall Rosetta Struktur Modellierung. Wie bereits in meiner ursprünglichen Post, Zink ist eines der häufigsten Metalle in natürliche Eiweiß-Moleküle, spielen beide wichtige strukturelle (Stabilisierung der Proteine) und katalytische (hilft realisieren Protein-Funktionen) Rollen. Eine Menge von Zink-bindenden Proteinen beteiligt sind in der DNA-Bindung und die Anerkennung und die beliebtesten Struktur Motiv wird als "Zink-Finger". Zum Beispiel, ein Enzym namens Integrase in HIV-Virus hat eine strukturelle Domäne, enthält Zink-Bindungsstellen und ist der Ansicht, die für multimerization dieses Enzyms. Um zu verstehen, wie die Zink-Bindung beeinflussen diesen Prozess wird sicherlich helfen Sie uns, neue Erkenntnisse im Kampf gegen HIV. Ich freue mich, um zu sehen, die letzten Beitrag erwähnt Matrix metalloproteases, weil ich bald an einer neuen Labor, die haben eine Menge Arbeit in die Charakterisierung unbekannt MMPs in der Human-Proteomik, die glaubte, dass Krebs im Zusammenhang. Ich bin sehr dankbar, dass jeder einen Beitrag zu unserem Projekt und ich werde sicher halten alle gebucht, wenn es einen spannenden Ergebnisse werden wir in Zukunft erhalten.

[DO3PSN]

Weißte, nichts gegen die Google-Übersetzungen, aber sie sind immer fähig, mir ein Lachen ins Gesicht zu zaubern.

Gruß

Philipp

[cappy]

das freut mich

naja da ich englisch nicht so beherrsche und ja nicht immer hier einer übersetzt und nicht jeder *der das gleiche problem hat wie ich* sich die mühe macht das selber bei google dann zu übersetzen füge ich es gleich mit ein