Foldit Plays for Jain Foundation / DYSF
As another example of applying Foldit to human disease, this month we have a puzzle on the protein dysferlin. The deficiency or absence of dysferlin causes one genetic type of Limb Girdle Muscular Dystrophy. Muscular dystrophy caused by dysferlin has autosomal recessive inheritance (meaning it is equally likely to affect females and males) and typical onset between the ages of 15 and 30. The UW Institute for Protein Design is conducting a research project on the structure and function of dysferlin for the Jain Foundation, a nonprofit foundation based in Seattle which supports research and the development of treatments for dysferlinopathy. The exact function of dysferlin is not completely understood, but it is thought to be involved in repair of the muscle cell membrane if it is damaged, and in resetting the muscle to a quiescent state following contraction. Sept. 30 is Limb Girdle Muscular Dystrophy Awareness Day, and we are introducing Puzzle 1291: Dysferlin C2B Domain to commemorate this day and to spread awareness to the Foldit community.
The following video features an interview with a neurologist on Limb Girdle Muscular Dystrophy, and with a patient who has dysferlin deficiency.
Ferlins are a family of transmembrane proteins which contain multiple C2 domains. The N-terminus is located inside the cell, and there is a single transmembrane domain near the C-terminus, which is located on the cell’s exterior. Ferlins are thought to participate in membrane fusion events and are involved in a variety of functions in many organisms. The first ferlin to be described is fer-1 in C. elegans, which is required for sperm function and hence fertility (giving rise to the name “fer”). Ferlins has also been described in drosophila and sea urchins. Deficiencies in two of the five mammalian ferlins have been associated with human disease. Otoferlin is required for transduction of signals from the inner ear to the nervous system for hearing, and its deficiency is a genetic cause of deafness. The most abundant dysferlin isoform in skeletal muscle is 2080 amino acids long, and contains at least seven C2 domains as well as additional protein domains of other types.( Posted by inkycatz 78 2772 | Thu, 09/29/2016 - 19:33 | 0 comments )
One goal frequently cited by citizen scientists is to work on problems that benefit human health. Foldit is uniquely positioned to enable this because the game allows players to fold and design proteins, which are often implicated in human disease. In particular, Foldit players can have a huge impact on rare and neglected diseases, which are more common in developing nations than in Western nations and generally receive less attention from pharmaceutical companies. Foldit can help through structure-based drug design (SBDD). The steps involved in SBDD are 1) identification of a target (a protein), 2) crystallization of the target, and 3) design of small-molecule drugs for the target. Through collaboration with the non-profit organization Infectious Disease Research Institute (IDRI), we would like Foldit players to experience this process. We hope that Foldit players will be able to positively impact a specific neglected disease: tuberculosis (TB).
TB is caused by the bacillus Mycobacterium tuberculosis. TB disproportionally impacts impoverished communities and killed 1.5 million people in 2014 alone (2014 is the most recent year that data is available). Additionally, it is estimated that 9.6 million people have fallen ill with TB in 2014, a number that includes 5.4 million men, 3.2 million women, and 1 million children. Figure 1 shows an estimate for incidence rates of TB from the World Health Organization (WHO).
A major issue in treating TB is that the bacterium has evolved to become resistant to current treatments – most notably, antibiotics and even combinations of antibiotics (see WHO for more information on the problem of antibiotic-resistant tuberculosis). The medical community needs a new drug to kill the bacteria; a target and crystal structure for SBDD will greatly accelerate design of new drugs.
Scientists at the non-profit organization Infectious Disease Research Institute (IDRI), and at Eli Lilly, have been working together to identify a suitable target and drug for TB. Their TB Drug Discovery collaboration is embodied in the following video.
These scientists have identified an essential enzyme in M. tuberculosis, LepB, as a target; unfortunately, there is no crystal structure available for the protein to perform SBDD. This protein target is notoriously difficult to work with since it is bound to the cytoplasmic membrane and only small amounts of the protein are available for crystallization trials. More accurate models can be used to guide protein engineering, with the goal of producing more soluble and crystallizable protein. Once crystals have been obtained and X-ray diffraction data obtained, the models will be used for molecular replacement (this is similar to the HIV retroviral puzzle that Foldit players helped solve in 2011). LepB is a difficult target in both experiments and in modeling. The closest homolog to the Protein Data Bank shares ~25% sequence similarity.
This is where citizen scientists can help! We would like to use models created from Foldit players to help solve the crystal structure, once crystals are obtained. These models will have a direct impact on human health, as this target is currently being actively investigated for drug design. Further, this is a prime example of how crowd-sourced citizen scientists, non-profit organizations, and a pharmaceutical company can work in harmony to develop cures for neglected diseases.
The work done here will be published, regardless of the results (e.g., if no crystal structure is obtained due to experimental difficulties, we will still publish Foldit players' models and the players’ names will be on the paper). If crystals are created and a structure is obtained, the players who have models that help with determination of the structure will be on the publication. Rest assured, we will publish what we have so that the whole scientific community can have access to it and help to fight TB.
We are hoping that we can take this puzzle and work through the whole drug design process (through the SBDD process). After models are created, and hopefully a structure is determined, we would like to use the new drug design game elements to design small-molecule drugs against TB as well. You can see in Figure 1 just how much the scientific community needs this.
This puzzle is currently scheduled to appear on Tuesday, 12 July 2016.( Posted by free_radical 78 2772 | Thu, 07/07/2016 - 17:30 | 6 comments )
Little update: Experimental Client (Drug Design)
There is a new update to the experimental drug design group. The changes include:
Change the format for the Ligand Queue tool to follow the Remix tool
Fix several spelling errors in drug design tools
Fix selecting/deselecting atoms in selection interface not properly selecting atoms
Fix incorrectly disabling certain buttons in Selection interface design menu that should be disabled
Add proper protonation and charges to designed molecules
Slightly modify Similarity Filter for better results
Fix mismatch between counting donors/acceptors in Rule of Five Filter and View Options
Fix some issues surrounding crashes in MMFF
Please respond to bug reports in this thread.( Posted by free_radical 78 2772 | Wed, 06/08/2016 - 15:37 | 0 comments )
Big Update: Experimental Client (Drug Design)
There is a new update to the ligand design client (experimental update group). In order to get the experimental client to work, follow the steps outlined here. There is a new puzzle, two new filters, and two new tools released with this update. Also, several bugs have been addressed and others noted:
Bug fixes that are complete
• Fix atom tree crashes when wiggling complex molecules/molecules clashing with backbone
• Fix errors associated with MMFF minimization
• Fix several loading issues
• Move MMFF to wiggle/shake/design submenu in selection tool
• Add new icon for MMFF
Known issues on the schedule for fixing
• When switching from design panel to undo, it is possible to have spheres left behind from the design panel.
• Original interface needs a position for MMFF button
• Switching tracks in undo menu works – occasionally
• Graphics for drawn 2D small molecules in Ligand Queue Tool needs to be greatly improved
• Scaling of bonus for Rule of Five and Similarity filter
New puzzle released
When a patient is diagnosed with HIV, they are almost immediately given anti-viral drugs that target HIV Protease 1. This protease is essential for the life cycle of HIV and inhibiting it helps prevent the spread of HIV within the body. To inhibit the protease, scientists have developed small molecules that trap the protease in a conformation that stops the enzyme from working normally.
To aid the scientists in their designs, they often look at specific ligand centric metrics. Ligand centric methods focus on attributes of the small molecule and ignore the protein. Two metrics, ligand similarity and Lipenski’s Rule of Five are often used during the design process. For this puzzle, we have provided two new filters that help track ligand similarity and Lipenski’s Rule of Five along with two new tools.
The new Rule of Five filter
Lipenski’s Rule of Five is a set of rules that are used to evaluate designed small molecules. The rules are based off of observations for known chemical entities that have made it to market. This is a ligand centric filter, meaning it only takes into account the small molecule being designed, not the protein – small molecule complex. You will be penalized if you violate the rules during design. The rules are:
• No more than 5 hydrogen bond donors
• No more than 10 hydrogen bond acceptors
• Molecular weight less than 500 daltons
• A logP of 5 or less
Molecular weight is determined by summing all the elements weights in a small molecule. For example, carbon has a weight of 12 and hydrogen has a weight of 1. If you have 6 carbons and 6 hydrogens, the weight would be 78. LogP is a measure of how soluble a small molecule is. The more soluble a molecule is, the more likely it is to be taken up into your body. LogP is determined based on the type of atoms present in a small molecule.
All of Lipenski’s rules are reported by the Rule of Five Filter; however, you can view these properties by clicking the ligand view tool.
The new Ligand Similarity filter
Ligand Similarity is used to describe the similarity between small molecules and known drugs. In the new HIV Protease puzzle, the Ligand Similarity filter is used specifically to identify how similar the designed small molecules are to known “tight” binders. This means that the higher the bonus received, the closer that you are to known chemical entities. This tops out at 75% similarity, to encourage looking for new designs. If you show the filter while using it, atoms that are similar to known binders will be highlighted. Changing those highlighted atoms will result in divergence away from known binders.
The new Ligand Queue tool
This tool will be changed from its current state to work more like the remix tool. The purpose of the Ligand Queue tool is to provide a set of small molecules to players; the set comes from actual experiments -– high-throughput screens, virtual high-throughput screens, and automated designs. For the HIV Protease puzzle, the small molecules that are shown are very low binders to HIV. Modifications of these ligands can result in making a small molecule that tightly binds HIV Protease. The ligands provide a good starting spot for design. This tool is still in a rough developmental state, but it is currently useful for providing context for a new concept.
High throughput screening and virtual screening are tools that scientists use to quickly identify small molecules that might bind a protein target. This is usually done by a robot that will screen millions of compounds rapidly. After the compounds have been screened, a process of identifying the molecule and modifying it occurs. This whole process is one of the first things done for each new protein target. We will discuss this more in a later blog post!
The new Ligand View tool
The ligand view tool provides ligand centric values that help you decide if the small molecule being designed is “drug-like”. The current values reported by the ligand view tool will be later incorporated into a filter to further guide you in your designs. In addition to the ligand centric metrics, there is also an iso surface tool that draws an isosurface around the ligand binding pocket to help better show packing against the ligand.
Enjoy! Post your questions and comments here and we'll do our best to get them addressed in future updates.( Posted by free_radical 78 2772 | Wed, 05/18/2016 - 19:52 | 3 comments )
Remix and Fragment Insertion
This post will cover the new Remix tool and the idea of Fragment Insertion in protein design.
A Fragment is a shape for a piece of protein backbone. Fragments can be of any size. A fragment of size 3 will be a shape for 3 residues in a row, size 9 will be for 9 residues.
When we insert a fragment, we are copying the shape of that fragment onto a piece of backbone. Think of it as copy/paste for a piece of backbone shape. Below you can see 3 different fragments in turquoise that were copied onto the backbone by Remix.
The collection of fragments that we copy/paste from is called a fragment library.
We want our fragment library to be filled with the best fragments possible - fragments that we’re confident are good shapes that will give our folds the highest chance of success.
So where does our fragment library come from?
Often times the best approach to protein folding (or anything, really) is to take what works and re-use it.
We have thousands of proteins from nature whose shape we already know. We’re certain that those shapes work because we have physical proof. By looking at these known shapes, we can look for fragments that are common in many natural proteins. We take these and make our fragment library out of them.
Then, when someone needs a shape for a piece of backbone, we look into our library and find fragments which we can copy/paste onto our protein. The tool that does this looking up and copy/paste is called the fragment picker.
Foldit's Fragment Pickers
Rebuild was the first and original fragment picker in Foldit. Rebuild picks from a library of fragments of size 3. When you run rebuild on a piece of backbone, it picks a random sub-piece of size 3 within your selection, looks up a fragment, then copies and pastes it onto your protein.
There are two problems with Rebuild. The first is that only having fragments of size 3 means that if you want a bigger fragment, you’re going to have to combine several smaller fragments, which is less scientifically valid.
The second and larger problem is that Rebuild isn’t very particular about which shapes it chooses. You just ask for fragments of size 3 and it gives them to you*. Then Rebuild does a bunch of work behind the scenes to try and make the fragments fit into your selection.
You can see the actual fragments Rebuild is trying to insert (no behind the scenes work to make it fit) by putting a cutpoint at one end of the selection and disabling cutpoint forces. Take a look at some of the results below:
As you can see, these fragments really don't fit very well. The blue band represents the gap between where the endpoint is and where it needs to be. The only way to make them "fit" requires destroying the original fragment in the process.
Remix tries to solve both of these problems. Firstly, Remix's fragment library has fragments from size 3 up to size 9.
Second, and more importantly, when you ask for a fragment out of Remix, it instead looks for a fragment that will naturally fit between the ends of your selection.
Here are some results of Remix without any modification after insertion:
All of these fragments just fit. The yellow band shows you the cutpoint is already close enough to be closed. In reality, we still "fix" the fragments from Remix as well, but they only need minor adjustment, so the fragment is left intact.
What this means is that Remix is much better at leaving you with more scientifically valid fragments.
* Rebuild does take your backbone sequence and secondary structure into account when doing a lookup, but no conformation information.
Using The New Remix
Remixing through the UI
To Remix a piece of backbone, select the piece and hit the Remix button (or, in the original interface, right click and hit the Remix button). This will pop up the Remix UI.
Let's go over the UI here. First off, there are arrow keys left and right. These let you cycle through the various fragments that Remix found for this selection. You can see which fragment you're currently looking at in the text below the buttons. The first fragment is always what you started with before you ran Remix, and won't change anything.
The Stop button accepts the currently shown fragment. You can also use the stop button in the upper left hand corner of the screen, and it will have the same effect.
Next to the text showing which fragment you have selected, you can also see a score. This score allows you to get an idea of how well fragments score without having to close the tool and shake the selection. Keep in mind it's only a rough estimate, and is only useful for comparing the results relatively. Your final score will likely be nothing like the score shown here.
Lastly, we have the Plus button. This button gives you access to the quicksave functionality of the new Remix tool.
When you press the button, you will see a new button pop up above.
Pressing this new Plus button will quicksave this fragment to Slot 1.
After saving, you can click that quicksave button to go back to that fragment. Pressing Plus for an additional fragment will give you the option of saving to a new quicksave slot, or overwriting an existing one. You can also press the Stop button that replaced the Plus in order to cancel the quicksave.
When you've got all the fragments you want, press Stop and these fragments will be available in your Quicksave slots. Pressing Ctrl-1 through Ctrl-8 will give you access to them.
Remixing with Scripts
Remix can also be accessed via scripts. Here's a quick tutorial on how to use it:
The function call for Remix is
When you run this function, it will Remix your selection and place up to num_results different results into your quicksave slots, starting at slot start_quicksave. It will return the number of results that were actually inserted, as sometimes there will not be as many as you have requested available.
Let's look at an example:
If there were 3 or more results, this would print "3" and place the results in quicksave slots 5,6,7.
If there were only two results available, it would print "2" and you would only have results in quicksave slots 5 and 6.
Fragment picking is best used for figuring out the loops of the protein. Loop shapes vary a lot more than other secondary structure, and so finding good loops is harder, and using actual fragments from real proteins becomes more important.
In general, it is best to use the larger fragments, since that gives you a bigger piece of good backbone in a way that several smaller Remixes may not.
Don't put too much value in the estimated score shown in the Remix UI. Differences of less than 100 points aren't very meaningful.
In the event that Remix doesn't find anything, try selecting one more or one less residue on either side of the selection. Often times this will be enough to give you a better range of results. This is easy to do in the Selection Interface, but requires some secondary structure reassigning in the Original Interface.
Lastly, after inserting a fragment, any changes to that selection will put you further and further from the fragment. As such, it's best if you can find a fragment that requires minimal modification to make it into your final design.( Posted by jflat06 78 1060 | Wed, 05/11/2016 - 00:16 | 5 comments )