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This is the place where we will describe some of the outcomes and results of your folding work, provide a glimpse of future challenges and developments, and in general give you a better sense of where we are and where foldit hopes to go in the future.

Newsletter July 24: A Good Week for Go Science

Hey folders!

Dev Josh here with your weekly Foldit update. Congratulations to Go Science! for being the top of all three puzzles this week! Go Science has been an open and active group since 2010. One of the best ways to learn and improve in Foldit is to join a group.

If Go Science isn't your style, try the hopeful and determined Anthropic Dreams, the fun and light Gargleblasters, or the dedicated Contenders

Solutions from This Week's Puzzles

(Disclaimer: This is not scientific feedback; these solutions are not officially endorsed by the Foldit scientists.)

Puzzle 1863: Refinement R1043

I've heard this puzzle was crashing pretty frequently. Thanks for your patience everyone, the devs are hard at work trying to fix these issues!

Puzzle 1864: Symmetric Trimer Design: Limited Interface

To master this puzzle, you needed to limit how big your binding interface was. Notice how the top scores rotated their helical bundles to limit their attachments!

Puzzle 1865: Coronavirus Anti-inflammatory Design 8

Bkoep said there were 15 unsolvable BUNS, but some of the top solutions got them down to 11! Great job on satisfying those BUNS everyone, keep it up!

Want to know more about why we're designing binders from scratch? Check out this forum thread for details on why we're not just using the ACE2 receptor design.

Recipe of the Week

This week's recipe is new but with great potential:
mwm64's UnBun is designed to help you reduce BUNS. This recipe only works on puzzles with the BUNS objective, and I haven't personally tried it out much, but I've heard a few folks are trying it. Plus, if you're looking to get involved with recipe evolving, this simple recipe could be a good way to get some practice with Lua. Given how important the BUNS objective is, we're going to need more recipes like this! So thanks mwm64 for making the first de-BUN-ifier!

Player of the Week

A quick shout-out this week to malphis, a friendly newcomer who joined a couple of months ago and has been really active in chat. Malphis has also been super helpful submitting bug reports to help the devs track down issues. Thanks!

Art of the Week

Looking for some more protein beauty? Check out this beautiful proteins blog! It's got a ton of real proteins that are naturally amazingly beautiful.

Today’s Master Folding Tips

Beginner: Before trying to wiggle your designed protein into the perfect shape, give it a mutate first! This will help the protein pack together better and give you a cleaner structure to work with. You can also mutate by hand: for example, although all of your amino acids start as isoleucine, it's actually better to set your loops to asparagine to start with.

Intermediate: Have you learned how to use the Rama map yet? We're working on a few new guides that should help make it easier to learn, but in the meantime Susume has two guides on how to use the Rama map to fix un-ideal loops and even copy a loop

Expert: Are you planning your design before you make it? Before you start drafting, spend a few minutes thinking about what your design will look like. How long will each helix and sheet be? Will you try to make pi stacks? What part of the protein will bind at the interface, and how will that give it shape complementarity? Once you're ready, use Loci's AA Edit and SS Edit to enter your design and give it a quick early/midgame rinse. Then hand it off to a novice member of your group to evolve and try another design!

Have a tip to share with the community? Reply with your wisdom, or post on our Forums!

Until next time, happy folding!

( Posted by  agcohn821 87 1215  |  Wed, 07/29/2020 - 18:53  |  0 comments )

Foldit Newsletter July 17: Bonjour Encore Triple Hélice

Hey folders!

Dev Josh here with your weekly Foldit update.

3 Solutions from This Week's Puzzle

(Disclaimer: This is not scientific feedback; these solutions are not officially endorsed by the Foldit scientists.)

Puzzle 1861: Symmetric Trimer Design: Buried Unsats

Triple helix is here to stay, look how clean and neat these bundles are! Great job silent gene and Spvincent

This solution took a less common approach to the triple helix meta. I'll let you decide for yourself whether you think it scored well or not. What do you think of it? Let us know in the Discord!

Puzzle 1862: Coronavirus Round 13

An extra special congratulations goes to clark92 for being top rank for this puzzle! This up-and-coming folder only started folding at the end of February, and already they've taken the leaderboards by storm!

These solutions come from some of our beginner folders! Can you tell what they could do better?

As a reminder, here are some helpful tips from bkoep on designing a good binder!

Want to get your top solution featured in the weekly newsletter? Click the "Share with Scientists" button in the "Open/Share Solution" menu and your solution might get featured! Don't forget to fill out our username sharing form if you'd like your username to be shown with your solutions!

Recipe of the Week

Not sure what recipes are good? Check out this all-in-one recipe: Constructor by Grom!
This mini-cookbook contains 19 different recipes all packed in one. Check it out for some inspiration this week!

Player of the Week

Big thanks to nspc this week for putting out two new French tutorial videos on how to get started with design puzzles and prediction puzzles.

If you're still on the intro puzzles, nspc also has a video on beating Hydrophobic Disaster.

I think I speak for everyone when I say merci beaucoup! Nspc (pc on Discord) is a beginner folder who has been learning fast by being really active in the chat. Say hi next time you see them around!

Art of the Week

Here's some art from 1861: a cool-looking triangle and a crazy ball of... I don't even know what... Thanks for sharing!

Today’s Master Folding Tips

Despite how common they are, I really recommend trying a helix bundle like the ones you've seen from the top-scoring solutions! Helices are easier to make than loops or sheets, so practicing on helix bundles is a great way to get a higher rank and practice the basics before trying something tricky and advanced like long loops or a sheet structure.

Are you paying attention to which structures your AA structure preferences. AAs prefer to be in? It's not a hard-and-fast rule, but check out the wiki for AA structure preferences. I find this especially helpful for getting started by mutating my isoleucines away into something more suitable for the structure I'm designing, like asparagines for loops, valines for sheets, and MALEK for helices.

How many structural motifs can you name? Most of you know pi stacking, some of you even know about beta hairpins. But do you know about ST turns, Greek keys, and Omega loops? What about sequence motifs?

Having these concepts in your toolkit will give you more conceptual legos from natural proteins to think about when designing. There's plenty of research out there on common patterns, and if you're looking for expert tips, then you're ready to dig into real literature. Good luck, and let us know what you find on the

Want to give your group a shoutout in the next newsletter? Reply with a blurb about what your group is and why new players should join, and your group might get featured in the next newsletter!

Until next time! Happy folding!

( Posted by  agcohn821 87 1215  |  Fri, 07/24/2020 - 03:47  |  0 comments )

Newsletter July 10: Triple-Quad Helices and Borromean Rings

(This post was originally sent out on July 10 to our mailing list. You can sign up for the mailing list here to receive weekly updates about Foldit, including tips and tricks and see the top-scoring solutions to the week's puzzles. Don't forget to join our Discord as well to stay in the chat even when you're not folding!)

Hey folders!

Dev Josh here with your weekly Foldit update.

Solutions from This Week's Puzzles

(Disclaimer: This is not scientific feedback; these solutions are not officially endorsed by the Foldit scientists.)

Puzzle 1858: Symmetric Trimer Design

Personally, I went with a 4-helix design for this puzzle, and it seems like that's what a lot of the highest scoring solutions did. But there were also a couple of 3-helix designs, and even some sheets!

Puzzle 1860: Refinement R1040

The highest scoring solutions for this puzzle kept two medium-sized sheets lined up and folded the rest into short helices around a core.

Compare this to some of the intermediate solutions. Although these folds are okay, they had some minor problems: some loose helices and poor scoring ends.

What was the trickiest part for you about this puzzle? Let's talk about it in Discord!

Recipe of the Week

This week's recipe has been described by Phyx as "The Best Recipe of 2014": Wisky's Repeating Rebuild All!

Let this late-game recipe run for 3-4 hours and it will do some rebuilding magic on your pose.

Player of the Week

I want to honor LociOiling! for constantly being the #1 contributor to our wiki!. This week he created the pages for Reaction Design Puzzles and Camera Controls! If you've ever read a wiki page that was made in the last few years, chances are Loci wrote it. Give him your thanks in chat next time you use the wiki!

Art of the Week

This week's most beautiful fold comes from Formula350 for his Borromean rings! This would never fold up in real life, but wow, is it pretty!

Today’s Master Folding Tips

Beginner: Don't be afraid to reassign your secondary structures to different sheets and helices! While this might seem like you're "changing the puzzle," you're really just making a suggestion for what shape the protein should take, and this suggestion can help your other tools better serve you. Try a bunch of different secondary structure assignments and use Ideal SS on them afterward, then see how this new arrangement might be easier or harder to fold. Play around with it, Foldit is about experimenting!

Intermediate: If you haven't learned to use Backbone Pins yet, I highly recommend it. This tool, hidden away in the view options, gives you more control over wiggling than CI alone. A locked pin is similar to a ZLB, it will keep your wiggle locked to that spot, while moving everything else more.

Expert: Although it might seem like more hbonds means better binding, hbonds at the interface don't actually add to the strength of the bind, since they aren't much stronger than these atoms simply binding to water. What use are interface hbonds then? Their purpose is eliminating BUNS. The real strength of your binding comes from hydrophobic interactions, shown in the Hiding and Packing subscores, and your hbond network gives the bind its specificity.

Want to recommend a recipe of the week or have your solution featured in the next newsletter? Send us your cookbooks and screenshots, we'd love to see what you're up to!

Until next time, happy folding!

( Posted by  joshmiller 87 879  |  Tue, 07/14/2020 - 20:19  |  0 comments )

Newsletter July 3: Initial Reactions

(This post was originally sent out on July 3 to our mailing list. You can sign up for the mailing list here to receive weekly updates about Foldit, including tips and tricks and see the top-scoring solutions to the week's puzzles. Don't forget to join our Discord as well to stay in the chat even when you're not folding!)

Hey folders!

Dev Josh here with your weekly Foldit update.

This week we saw the introduction of the Reaction Design tool. The devs are working hard on polishing it up and making it more usable! As always, thanks for your feedback and bug reports. You can submit more feedback here.

Top Results from Puzzle 1856: Coronavirus Round 12

In this puzzle, I accidentally evo'ed on a broken developer build and got the top score. Whoops, sorry about that!
Here are some of the solutions at the top of the leaderboards. [A note from our scientists: the top of the leaderboards doesn't always mean the most scientifically useful. These highlights are not scientific feedback and are not officially endorsed as scientifically valid designs by the Foldit team.]

Join the mailing list to see what others are folding!

Recipe of the Week

This week's recipe is an oldie but a goodie from drjr. The recipe is called Reset, and it does what it says on the tin: reset to the best score, unfreeze the protein, remove all your bands, and set the CI to 1. A simple recipe, but a handy quality of life tool for when you just need to backtrack a little.

Player of the Week

Quick shoutout to argyrw for always being a friendly voice in chat! Say hi to her in global or veteran chat.

Today’s Master Folding Tips

Beginner: Are you still using Pull to draft your protein in the early game? Try making cutpoints and moving pieces around with the Move tool, it's so much easier! Don't forget to disable cutpoint bands in the Behavior tab, or they'll all come together again when you wiggle.

Intermediate: It can be really tempting mid-game to just switch to running recipes. But give some time to carefully inspect every acceptor and donor (the red and blue dots) to see what hydrogen bonds you can form, and manually mutate as needed. Not only will this lower your BUNS, but it'll help form a strong hbond network. The scientists love this, and your rank will too!

Expert: If you haven't already, read bkoep's blog on binder design metrics. DDG, SASA, and SC are going to become really important soon since we're looking to add objectives for them. So understanding and practicing these principles now can help you get a headstart on the competition! Use the protein design sandbox to try out some ideas.

Have a tip to share or a recipe to recommend? Reply with your suggestions or make a wiki page for your ideas! Reaction Design doesn't have a page yet, so if you understand this tool, help out your community by writing about it! (Since writing this post, LociOiling has graciously created the page for Reaction Design puzzles.)

Until next time, happy folding!

( Posted by  joshmiller 87 879  |  Mon, 07/06/2020 - 18:11  |  3 comments )

Experiment results for IL6R binders

The results from our IL6R binder experiment are back! This experiment tested 100 Foldit designs from the first two rounds of our Coronavirus Anti-inflammatory puzzles, to see if any of them bind to the IL6R target.

In short, we did not see any successful binding from the Foldit designs. This is unfortunate, but we should not be too discouraged! Read on for more details about the experiment, and what these results mean for Foldit (hint: more binder design puzzles!).

This is a long blog post, broken into a few different sections. First, we’ll explain some background about DNA libraries and fluorescence-activated cell sorting techniques that were used for this experiment. Then we’ll go over the experiment results for protein expression and target binding. Finally, we’ll close out with some discussion about these results, and thoughts about what’s next for Foldit.

DNA libraries

In order to test lots of proteins at once, we order a custom DNA library. A DNA library is a mixed pool containing thousands of different DNA genes that encode our designed proteins.

In this experiment, the library includes genes for 100 Foldit player designs and thousands of designs from IPD researchers. All of these designs are intended to bind to the IL6R target.

We insert this mixture of genes into a yeast culture so that each yeast cell gets a gene for just one binder design.

We insert our designed gene alongside a companion gene that encodes a yeast membrane protein. When these genes are decoded, our designed protein is linked to the companion membrane protein. The yeast cell exports these to the cell membrane, so that our designed binder is displayed on the outside of the yeast cell, but is still tethered to the companion protein embedded in the membrane.

Although we expect the yeast cell to have lots of binders on the surface, those binders should all be identical since they came from the same gene.

Figure 1. A DNA library is a mixture with DNA genes encoding thousands of protein designs. The genes are inserted into yeast cells so that the yeast cells can decode the genes and express the designed proteins. The yeast cells export the designed proteins to the cell membrane so that they are displayed on the yeast surface.

Now we have a culture with millions and millions of yeast cells, which are displaying our library with thousands of different binder designs. Each yeast cell displays only one of the designs from the library; but there may be many identical yeast cells that each display the same design.

Fluorescence-activated cell sorting (FACS)

Now that our designed protein is displayed on the yeast surface, we tag the protein with a fluorescent molecule that emits green light. The intensity of green fluorescence corresponds to the amount of protein displayed on the yeast surface (higher intensity = more protein).

In a separate tube, our target protein (IL6R) is free-floating in solution, and we tag it with a different fluorescent molecule that emits red light.

Then we mix the free-floating target IL6R with our yeast cells. We expect the target will stick to binders that are displayed on the yeast surface. However, if one of our designed proteins does not bind the target, then no target molecules will stick to that yeast cell.

Now we'd like to measure how much target is stuck to each yeast cell. We use a microfluidics device to pass yeast cells, one at a time, in front of a sensitive photometer, which measures the intensity of green and red fluorescence in two separate measurements.

These two measurements are typically plotted as a scatter plot. Each point represents one yeast cell, where the x-axis is intensity of green fluorescence (the amount of displayed protein), and the y-axis is intensity of red fluorescence (the amount of bound target).

Figure 2. (A) Green-tagged designs are tethered to the yeast surface, while red-tagged target is free-floating. If a design successfully binds the target, then a yeast cell will have high-intensity green and red fluorescence. (B) FACS scatter plot of yeast fluorescence measurements. Each point is a yeast cell, with green fluorescence (expression) on the x-axis, and red fluorescence (binding) on the y-axis. Points in the top right corner represent cells with both red and green fluorescence, indicating good expression and binding. (Note that the colors in the plot represent point density; for example, the patch of red near the center of the plot means there are lots of overlapping points in this region.)

After taking these measurements, the cell sorter can redirect each individual yeast cell to one of two buckets (“select” or “reject”), based on their fluorescence. Normally, we are looking for cells that have strong expression (intense green) and strong binding (intense red). So we want to select the top right quadrant of the scatter plot, and reject everything else.

After sorting, we end up with a “select” bucket of all the yeast cells displaying successful binders (these were cells with intense red and green fluorescence, indicating that they express well and stick to the target).

The last step of this experiment is to figure out which proteins were displayed on those cells. There were thousands of designs in our library; which ones stick to the target?

For this, we use DNA sequencing to read the genes of everything in our “select” bucket. If we read a gene encoding one of our designs, then we know that a yeast cell displaying our design was sorted into the select bucket, and so it must have had strong red and green fluorescence.

The final output of our experiment is a list of genes that were found in the "select" bucket, and the number of times we read each gene. If our bucket contains multiple, identical yeast cells with the same gene, then we expect to see multiple reads of that gene.

The data

Below is a preview of the data from this experiment. You can download the data for all 100 Foldit designs here.

design_id       counts1 counts2 counts3 counts4 counts5 counts6 DDG     SASA        SC      BUNS
2009432_c0003   21      0       0       0       0       0       -26.908 946.664     0.600   9
2009432_c0004   57      3       0       0       0       0       -35.443 1198.221    0.669   8
2009432_c0006   29      0       3       0       0       0       -40.365 1386.322    0.647   10
2009432_c0007   17      0       5       0       1       0       -53.948 1635.076    0.679   15
2009432_c0009   67      0       0       0       0       0       -31.730 1032.899    0.665   6
2009432_c0010   94      0       0       0       0       0       -31.894 1267.798    0.672   10
2009432_c0011   57      0       0       0       0       0       -30.796 1122.379    0.553   9
2009432_c0012   111     1       0       0       0       0       -37.067 1340.479    0.641   10
2009432_c0014   5       0       0       0       0       0       -44.323 1378.069    0.554   13
2009432_c0016   16      0       0       0       0       0       -39.257 1460.892    0.649   10

In the table above, you can see that each design has six “counts” columns. These correspond to six different FACS experiments with the IL6R binder library, which we'll describe below:

  1. Expression
  2. Binding at 1000 nM
  3. Binding at 100 nM
  4. Binding at 10 nM
  5. Binding at 1 nM
  6. Binding at 0.1 nM

Sorting for expression

In experiment #1, we try to measure how well the yeast can express and display our designed proteins. We don’t mix the target IL6R protein with our yeast and we don’t measure red fluorescence for binding. We only select yeast with strong green fluorescence, collecting cells that have lots of designed protein displayed on their surface.

The expression experiment is a helpful control for the later binding experiments, but it can also tell us something about how well our proteins behave. Stable, well folded proteins are easily displayed by the yeast, and these yeast will have strong green fluorescence. In contrast, unstable, poorly folded proteins are less likely to be displayed, and will show weaker fluorescence.

For many of the Foldit designs, the sequencing counts from experiment #1 are a little low. The median expression count for a design in this entire library was about 50, and only a third of the Foldit designs met this threshold. This suggests that some of these protein designs are not folding very well.

This is in line with our expectations. When Foldit players design monomer proteins from scratch, we see about a 50% success rate for good folding in the lab (50% is very good by protein design standards!). Binder design is harder than bare monomer design, because we generally have to sacrifice folding stability to optimize binding. So we should expect that <50% of binder designs will fold properly.

Sorting for binding

After selecting for expression, we can start selecting designs from our library based on binding.

This time we mix our yeast cells with red-tagged target IL6R that is free in solution. In the early experiments we mix with a high concentration of the target (1000 nM).

A binding measurement at high concentrations of target is a lenient test for binding. There are lots of target molecules floating around, so even weak binders are likely to have some target stuck to them.

After letting the yeast cells equilibrate with the target in solution, we pass the yeast through the cell sorter and measure the intensity of both red and green light. If a cell lights up for both expression and binding (in the top right quadrant), then we send it to the select bucket for sequencing.

Figure 3. FACS scatter plots. (A) The fluorescence measurements from expression experiment #1. We see two clusters of cells in the bottom left and bottom right quadrants, representing cells with poor expression and high expression, respectively. We select everything in the bottom right quadrant. Note that this experiment does not include any IL6R target, so there is no red fluorescent signal for binding (there are no cells in the top left or top right quadrants). (B) The fluorescence measurements from binding experiment #2. After incubating the yeast cells with target IL6R, we see that some cells have both green and red fluorescence (the top right quadrant). This indicates both strong expression and also strong binding.

We typically repeat the binding experiment, reducing the concentration of target each time. Binding measurements at low concentrations of target provide a stringent test for binding. At 0.1 nM target concentration, we are likely to see binder and target stuck together only if they bind very tightly.

We see very low sequencing counts for all of the Foldit designs--even at high concentration of target--which indicates zero binders. Some designs show a couple of reads in one or two of the binding experiments, but this is within the range of noise that we would expect for zero binders.

Why didn't the Foldit designs bind to the target?

These results are slightly disappointing, but we should not be too discouraged!

Although none of our Foldit designs bound to the IL6R target, we did see a few binders from the designs by IPD researchers. Below are the counts from the tightest IPD binder:

design_id      counts1 counts2 counts3 counts4 counts5 counts6 DDG     SASA        SC      BUNS
IPD_design     144     38      69      56      13      52      -39.114 1720.442    0.640   9

Figure 4. An IPD-designed protein binder with exceptional binder metrics, which appears to bind IL6R. The IL6R library included thousands of proteins designed by IPD researchers with highly optimized binder metrics. Only a handful of designs successfully bound to the target.

Why did we see binding from IPD designs but not from Foldit designs? The IPD designs had exceptional binder metrics. Recall from our previous blogpost that certain metrics seem to correlate with good binding (DDG, SASA, BUNS, shape complementarity). If we rank the tested designs using these metrics, we find that this IPD design outranks all but three of our Foldit designs.

In order to design successful protein binders in Foldit, we will need to focus on these binder metrics. If we can make these metrics available in Foldit puzzles, we are confident that Foldit players will be able to optimize them just as well as IPD researchers. To that end, the Foldit team has been working to add new Objectives that can compute all of these metrics in Foldit. We should be able to release the first prototype Objectives in an update very soon!

Another important consideration here is the sheer number of IPD designs tested. The library for this experiment included thousands of IPD designs, and all of them had top-tier binding metrics like the one above. Even with those thousands of designs, we only got a few binder hits out of the library.

Unfortunately, such high failure rates are typical for protein binder experiments. We have to remember that protein design is a difficult challenge with many pitfalls, and our understanding of protein folding and binding is imperfect. To succeed in protein binder design, we will need to generate lots of designs to test.

What's next for Foldit?

The Foldit designs in this experiment came from just the first two rounds of the anti-inflammatory puzzles, back in April. Since then, we’ve seen even more great designs from Foldit players, and we’ll continue to run binder design puzzles as we work to improve the Foldit tools.

Soon Foldit will have prototype Objectives for calculating DDG, SASA, and shape complementarity. Already, it seems that players have been able to use the new BUNS Objective to improve designs in recent weeks.

We’re excited to keep pressing on the problem of protein binder design! We are used to tackling hard problems in Foldit, we tend to learn a lot about proteins in the process. We think that Foldit players have a lot to contribute in this arena, and we’ll be looking to tackle new (and harder) targets in the coming months.

Remember that we also have an experiment under way to test Foldit-designed binders for the coronavirus spike protein, and we should have results from that experiment soon. So stay tuned for more, and happy folding!

( Posted by  bkoep 87 723  |  Tue, 06/30/2020 - 22:34  |  9 comments )
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