New projects to help design selective inhibitors of protein methyltransferases

The Chodera lab has teamed up with Luo lab at MSKCC to study another important class of cancer targets: protein methyltransferases.

These are protein-modifying enzymes that catalyze the transfer of methyl groups to lysine or arginine residues as part of complex regulatory programs. While a number of cancers have alterations in protein methyltransferases, making them appealing targets for new anticancer therapeutics, it is not yet possible to fully understand their role in disease because of the current limited repertoire of compounds available to selectively inhibit these enzymes.

Spurred by recent encouraging results from the Luo lab in developing sinefungin scaffolds to selectively target key methyltransferases, we are working with them to better understand the origin of selectivity of these compounds, and to help them design new compounds that will allow researchers to better understand the roles these enzymes play in cancer and, eventually, develop potent new anticancer therapeutics.

Projects 10474, 10475, and 10476 study key protein methyltransferases NSD1, NSD2, and SETD2.

 

protein methyltransferase NSD1 (PDB ID 4h12)

Protein methyltransferase NSD1 (pdbid 4h12)

Investigating conformations accessible by Abl kinase- drug target for chronic myelogenous leukemia

Guest post by Sonya Hanson, postdoc in the Chodera lab.
(Project 10472)

We’re working our way through the kinase family here at the Chodera lab. You may have seen Danny’s post about EGFR earlier this year, and now we’ve started simulations of Abl kinase. Abl kinase has a special place in the history of cancer therapeutics, ‘dispelling the long-held myth that it was not feasible to develop selective inhibitors of key cell-signaling molecules as safe and effective medicines.’ Novartis’ development of the drug imatinib (or Gleevec commercially) to treat chronic myelogenous leukemia (CML) specifically targets a mutant Abl kinase that results from a chromosomal abnormality called ‘the Philadelphia chromosome’. There is even a book out recently that chronicles the development of Gleevec (The Philadelphia Chromosome).

While the success of imatinib was remarkable, many patients develop resistance to it and regress. A more recent drug targeting Abl kinase, ponatinib of Ariad Pharmaceuticals (Iclusig commercially), has been developed that overcomes some of these resistance mutations. However, now even ponatinib has been found to be susceptible to resistance mutants. With these simulations of Abl kinase, we are hoping to begin to understand a structural basis for the development of resistance mutants so we can develop drugs that anticipate and overcome them before the patient even has to experience regression. But to do this we will need many long timescale trajectories of Abl and later its mutants to achieve this deeper understanding of the development of resistance in CML. Additionally, this knowledge could inform models of resistance development in other cancers that result from kinase mutations or kinase up-regulation.

A new project to study early folding events in apomyoglobin

In a new NSF-funded collaboration, the Voelz Lab is working with the Roder Lab at Fox Chase Cancer Center to study early folding events in apomyoglobin.

Apomyoglobin (myoglobin without the heme group) is an extremely well-studied protein. In fact, mygolobin was the first protein to have its structure solved by x-ray crystallography (John Kendrew, 1958). At low pH, apomyoglobin assumes a “molten globule” state that is compact and only partially structured. Seminal experiments by Jennings and Wright (1993) showed that when apomyoglobin folds at normal pH, it goes through an early intermediate that closely corresponds to the low-pH molten globule state.

Now, more recent experiments from the Roder lab have revealed even more details of early folding events in myoglobin (Xu et al. 2012). Using Trp fluorescence spectroscopy in a continuous-flow fast mixer, the Roder lab have resolved the formation of up to four different conformational states, on timescales ranging from microseconds to milliseconds.

The Voelz Lab is working toward using molecular simulation to characterize these conformational states in atomic detail. Both the size of the protein (153 residues) and the timescale of early folding (~200 µs) make this a challenging problem to tackle, but we hope that simulations on Folding@home (coming soon!) combined with Markov State Model approaches will enable us to construct a highly detailed model of the early folding reaction, and new level of quantitative connection between simulations and experiments. In the years to come, this work will lead to new ways to combine computation and experiment to understand and fight human diseases.

Combining simulation and experiments to solve molecular structures

The Voelz lab has been making progress on combining simulation and experiments to solve molecular structures.

Most molecules do not have a single rigid structure in solvent. Instead, they exist in a range of different conformations. Stable proteins exist mostly in the folded conformation, but there is always a small fraction of population that is unfolded. Other molecules may have a very heterogeneous set of conformations, which can make determining their structure in solvent difficult. NMR experiments, for example, can be used for this, but structural information often gets “washed out” due to motional averaging.

Our new method, called BICePs (Bayesian inference of conformational populations) is a robust method to infer the populations of conformational states, using a combination of high-resolution computer modeling and information from experiments. We think BICePs will be very useful for determining the extent to which proteins and other molecules are well-structured in solution. In the future we plan to use it as a tool for designing well-structured mimics of proteins, called peptidomimetics. Our paper describing the new BICePs algorithm has been published in the latest issue of the Journal of Computational Chemistry.

fah-web.stanford.edu going down at 1pm pacific time for planned maintenance.

fah-web.stanford.edu going down at 1pm pacific time for planned maintenance.   We expect it will be down for about 30 minutes.

Native Client WUs down, we’re working on it

The Native Client WUs are down, we’re working on it.  This one may take a day or two for us to resolve.  We’ll keep donors posted as we know more.

Upgraded Maxwell support for Core17

With the newer NVIDIA drivers, it looks like Core17 works well on Maxwell.  We’ve released Core17 to Maxwell on adv (“Advanced Methods” setting).  If you’re having problems, you can set from adv back to the regular fah setting, allowing donors to opt out if they’re having problems.  The latest drivers are recommended.

Working with Andreessen Horowitz

Starting this week, I am adding an additional role to my work at Stanford (currently Director of Biophysics; Professor of Chemistry, and by courtesy, Computer Science, and Structural Biology; and Director of Folding@home) by doing consulting for Andreessen Horowitz (aka “a16z”), a venture capital firm with the goal of supporting companies with an emphasis on software making the difference.  Just as the web browser has changed the world, they are looking to support new ideas with a similar transformative character.  My role will be to be a conduit between academia and venture capital, to help good ideas at Universities to get the funding they need to create new products to help the world.  I’d like to stress that the Folding@home team is continuing full steam and that this new role has the hope for improved funding for activities at Stanford and for academic researchers in general.

New FAH Assignment Server Deployed

After over a year of internal development, we have deployed the new Folding@home Assignment Server (AS). The AS plays a central role in FAH. AS logic decides the “what” and “where” of Work Unit/Project assignment, i.e. what types of projects should be placed on which Work Servers (WS), among other things.

The new AS has several major benefits. It has the ability to more cleanly handle involvement of multiple Pande Group/Pande Group-associated Work Server maintainers. Assignments are now based on projects rather than Work Server type/availability. So now we have better control of pushing out our projects. We also have much better AS to WS connections thus avoiding the “no work” messages or other errors that resulted from slower AS/WS communication. The new WS now has a suite of analytics to help us better analyze how FAH assignments are working and improve issues much earlier, ideally before they become more serious.

Some recent Pande Group research on Calmodulin

Ariana Peck, a graduate student in our group recently presented her research on an important protein- Calmodulin (CaM).

Calmodulin is a calcium-binding messenger protein expressed in all eukaryotic cells. CaM transduces calcium signals by binding calcium ions and thus modifying/enabling it’s interactions with various target proteins. CaM along with calcium mediates many crucial processes such as inflammation, muscle contraction, memory, and immune response. Calcium is needed as a second messenger; calcium bound to proteins such as Calmodulin combine to act as messengers in our cells. The prevailing paradigm for Calmodulin function is that CaM plus bound calcium induces a conformational change. This results in target protein binding, in turn resulting in a cascade of cellular communication.

A few of the questions Ariana and our group are trying to answer are: How are Ca2+ dynamics so well regulated, and how do cells coordinate a response? What is the structural basis of diverse CaM target recognition? What is the mechanism of conformational change and can we find molecules (i.e. therapeutics for Cardiac Arrhythmias) that stabilize particular conformations?

Add your computer's power to over 327,000 others that are helping us find cures to Alzheimer's, Huntington's, Parkinson's and many cancers ...

... in just 5 minutes.

Step 1.

Download protein folding simulation software called

Folding@home

.

Step 2.

Run the installation. The software will automatically start up and open a web browser with your control panel.

Step 3.

Follow the instructions to Start Folding.

Stanford University

will send your computer a folding problem to solve. When your first job is completed, your computer will swap the results for a new job.

Download the protein folding simulation software that fits your machine.

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