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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.

Introducing Small Molecule Design Puzzles

Hi everyone,

Today we are officially launching the Foldit small molecule drug discovery game mode.

To kick off the new game mode, we are releasing a new puzzle on acquired immunodeficiency syndrome (AIDS). It has been over three decades since the CDC reported on the discovery of AIDS and its cause, the human immunodeficiency virus (HIV). Currently, 17 million people globally are being treated for HIV with antiretroviral therapy (WHO Global AIDS Update 2016). A total of 2.1 million people were infected with HIV in 2015 and 1.1 million people died from AIDS, with the majority of patients being from in Africa.

(Source: UNAIDS Global AIDS Update 2016)

Current treatment therapies focus on blocking the enzymes used by HIV to reproduce. One such enzyme is HIV protease, an enzyme which the virus uses to cleave polypeptide precursors. Without a functioning HIV protease, the virus cannot make the proteins needed to produce new virus particles. Several small molecule drugs have been created to block HIV protease, such as saquinavir and amprenavir. These compounds inhibit HIV protease by binding in the enzyme active site, a large cleft running through the middle of the protein, which prevent the enzyme's substrates from binding to the enzyme. HIV protease is a good test case for small molecule design, as there's a wealth of information about what sorts of compounds bind to the enzyme.

For this puzzle, we are interested in what small molecule inhibitors you can design for HIV protease 1. As a starting point, we're giving you the base fragment for saquinavir in the binding pocket. What we'd like you to do is use the new small molecule design tools to alter the chemical structure of the inhibitor ligand to get a better binding (better scoring) ligand.

We recommend that you use the selection interface (Menu->Selection Interface) for this process, as it gives you the most control, but you can also access some of the drug design tools through the "Modes" entry of the original interface. In particular, the Ligand Design tool will be your main tool for altering the identity of the ligand.

In the selection interface, the Ligand Design tool will pop up after clicking on the ligand. (In the original interface, click Ligand Design from the modes menu before clicking on the ligand.) You can then click one or more individual atoms to change the atom's element, or to add and delete bonds, atoms and groups. Keep in mind the advanced GUI (Main/Menu->General Options->Show advanced GUI) enables additional options under View that may help in working with small molecules. (I like the "Cartoon Ligand" view, myself, as it allows you to select ligand hydrogen atoms.)

Explore the tools and different designs you can make for the small molecule! Remember, you can use the Upload for Scientists button for designs that you want us to look at, even if they are not the best-scoring solutions!

-rmoretti & freeradical

P.S. Didn't follow the development of the drug design mode? Catch up with these previous blog posts:

* Foldit drug design introduction
* Foldit Drug Design Part Two
* Foldit Drug Design Blog: Interface Update
* Drug design puzzles coming your way!
* Let's Get Ready for Drug Design Puzzles!
* Devprev Drug Design Update
* Drug Design Update: Tool Talk
* Drug Design Update: Merk Molecular Force Field
* Big Update: Experimental Client (Drug Design)

(Note that some features discussed are for older versions and have changed since.)

( Posted by  rmoretti 71 410  |  Tue, 09/19/2017 - 23:11  |  0 comments )

A Visit from a Veteran Foldit Player

A couple of weeks ago, the Foldit team had the pleasure of meeting with veteran Foldit player, Timo van der Laan! Timo, who was visiting Seattle from his home in the Netherlands, met with us to discuss volunteering his programming expertise. Timo's background in automating development processes and structuring documentation will be a huge asset as he works with our team on improving Foldit.

The team discussed numerous potential projects and afterward, bkoep took Timo on a tour of the lab where proteins designed by Foldit players are tested. They examined samples of plasmid DNA, each of which encodes the amino acid sequence of a Foldit player designs, which are inserted into E. coli cells. Then they visited the E. coli incubators where the bacteria are grown, with shaking platforms that keep the growth medium turbulent and well-aerated. Timo was introduced to some of the instruments are used to purify proteins, like a column for size exclusion chromatograph (SEC); as well as other instruments that are used to characterize proteins, like the circular dichroism (CD) spectrometer. Lastly, they viewed some of the protein crystallization trays that have been set up for the numerous projects of the Baker Lab.

bkoep and Timo
bkoep and Timo van der Laan on a tour of the Baker Lab

We thoroughly enjoyed meeting Timo after all these years and are looking forward to working with him on whatever project ends up getting nailed down!

You can read more about these instruments and the design testing process in our previous blog post.

( Posted by  smortier 71 1541  |  Wed, 06/21/2017 - 20:17  |  2 comments )

X-ray Diffraction

Since our last blog post, we've carried out an x-ray diffraction experiment with one of our protein crystals. We were lucky that the protein crystal yielded high quality diffraction data, and from this data we were able to solve the first-ever crystal structure of a protein designed by Foldit players—a near-exact match to the designed structure! Below we explain a bit more about x-ray diffraction. In a later post, we'll examine the final structure in more detail.

First, the protein crystal is harvested from the drop using a small loop of nylon, about 0.3 mm across. Protein crystals are often very fragile, so looping the crystal requires a steady hand (i.e. optimal coffee dosage). Even in the loop, the crystal is still immersed in an aqueous solution, with the surface tension of the water helping to keep the crystal in the loop. The loop is rapidly submerged in liquid nitrogen, at a temperature of about -200ºC, which quenches most of the thermal motion of molecules in the crystal.

Once frozen, our looped crystal is mounted on a robotic arm that positions the loop in the path of an x-ray beam. During x-ray exposure, the crystal is kept under a steady stream of cold nitrogen gas to limit temperature increases in the crystal. X-rays have a high energy, and a protein crystal can only endure so much exposure to x-rays before it starts to degrade. The protein lattice could disintegrate from the increased thermal motion of individual protein molecules, or else the x-rays could trigger chemical reactions within the protein, distorting its structure.

X-rays are simply a type of electromagnetic radiation with a very short wavelength—in this case about one angstrom. In an x-ray diffraction experiment, it's important that all radiation has exactly the same wavelength and is focused into a very narrow beam. With our crystal mounted in the path of the x-ray beam, an x-ray detector is positioned behind the crystal, and measures incident x-rays after they strike the crystal and are diffracted by electrons of the protein molecules within. Because of the regular arrangement of atoms in the protein crystal, diffracted x-rays undergo constructive interference in particular directions. This occurs when two equivalent "slices" of the crystal are oriented to coincide with the wavelength of the x-rays. Wherever constructive interference occurs, the detector registers an especially intense signal, shown as a dark spot on the image below. Taken together, these spots comprise a diffraction pattern.

Above is an x-ray diffraction pattern from a protein crystal. In the inset at the right, we can see that some spots seem to have duplicates which are slightly offset. This indicates that there are actually two identical crystals in the path of the x-ray, lying in slightly different orientations. Most likely, the crystal cracked in two during freezing. Fortunately, the image-processing software we use is sophisticated enough to correct for this issue.

The spacing and position of spots is governed by the size and shape of the crystal’s unit cell, the repeating unit that makes up the crystal. The intensity of each spot is determined by the distribution of electrons within the unit cell (i.e. the positions of atoms in the protein). Every atom of the unit cell contributes to each spot in the diffraction pattern. If you could change the electron density around just one atom of your crystallized protein, this would alter the intensity of every spot in the diffraction pattern!

Notice that spots farther from the center of the detector tend to be less intense. More distant spots contain higher resolution data about the electron density of the protein. If we adjust the contrast of this image, we can discern spots close to the edge of the detector. This protein diffracts x-rays to a resolution limit of 1.20 Å! In an electron density map derived from these diffraction patterns, we should be able to distinguish the positions of individual atoms.

If the crystal is rotated relative to the x-ray beam, then we would observe another diffraction pattern, as the new orientation produces constructive interference in different directions. We typically measure a new diffraction pattern at rotation intervals of 0.5 degrees, eventually rotating the crystal a total of 180 degrees (sometimes less for highly-symmetric crystals) to collect a complete dataset. This dataset was collected with a state-of-the-art detector that can measure individual photons; collecting a full dataset takes no more than a few minutes. In the early days of protein crystallography, it could take a whole day to collect a complete dataset!

The processing and interpretation of a these x-ray diffraction patterns is a complex, technical procedure, and we won't go into it here. But suffice it to say, this x-ray diffraction data revealed a full, high-resolution crystal structure of this Foldit player-designed protein!

Congratulations to Waya, Galaxie, and Susume who contributed to this solution in Puzzle 1297! All players should check out Puzzle 1384 to explore the refined electron density map from this data, and see if you can fold up the protein sequence into its crystal structure! We'll follow up later with a more detailed comparison of the designed model and the final crystal structure.

( Posted by  bkoep 71 390  |  Tue, 05/30/2017 - 04:59  |  4 comments )

Protein crystallization

It's time for an update on Foldit protein design! If you recall, our last update showed that several Foldit player-designed proteins appear folded and stable in solution. However, we'd like to have crystal structures of these proteins to show that they are indeed folding into their intended folds. The first step in getting a crystal structure is getting a protein crystal. Here we take a closer look at the protein crystallization process.

Above is a 96-well crystallization tray. We use a robot to rapidly set up crystallization experiments with 96 different conditions per tray. For this protein we set up four trays, to test a total of 384 crystallization conditions.

Each “well” in the 96-well tray is actually divided into four distinct regions. In the upper right, a square reservoir holds the mother liquor. The mother liquor is typically an aqueous buffer with some salt and a high concentration of precipitant. The reservoir is accompanied by three circular drop wells, each of which contains of drop of our protein sample mixed with the mother liquor. In this tray, the three drop wells are used to test different drop ratios, with protein and mother liquor combined in a ratio of 1:1, 2:1, or 1:2.

Each of the 96 wells is sealed off from the air and from neighboring wells. However, within a well, the three drops share an atmosphere with the reservoir, so that the drops can equilibrate with the reservoir by vapor diffusion. Over time, water evaporates from the drops and condenses in the reservoir. As the drop volume decreases, the protein concentration in the drop gradually increases. Eventually, the protein concentration reaches a critical point and the protein crystallizes.

In the drop above, we see several plate-like crystals radiating outward from a single origin. Most likely a small dust particle at the center served to “seed” the growth of all these crystals.

The crystals are not actually colored, per se, but exhibit birefringence—meaning that they refract light waves differently, depending on the orientation of the light waves with respect to the crystal lattice. When viewed through a microscope equipped with a light-polarizing filter, the birefringent crystals appear colored.

These crystals appear to be thin and plate-like, suggesting this particular crystal lattice extends readily in height and width, but less easily in depth. Sometimes, this is indicative of imperfections in the crystal packing, and can limit the quality of x-ray diffraction. To follow up, we’ll try to optimize the crystallization conditions by setting up a number of similar drops with slight alterations in the composition, in hopes that we get larger, more substantial crystals. However, there's a chance one of these crystals will diffract well enough to yield a crystal structure.

Once we have a nice, high-quality crystal that yields a good x-ray diffraction pattern, we can set about solving the crystal structure. A solved crystal structure will tell us definitively whether the protein folds up as the designer intended!

( Posted by  bkoep 71 390  |  Sat, 04/15/2017 - 00:09  |  8 comments )

Foldit design update - Part 2

This is an extension of last week's protein design update, in which we discussed recent improvements in backbone quality and showcased a collection of player designs that were brought into the wet lab. Our analysis is ongoing, and some of those designs may still yield results. But a few exceptional designs are already showing promise, and we thought those results warranted a separate, more focused analysis here.

Folded Proteins

Below are four proteins designed by Foldit players, then expressed and purified in the Baker lab (more here). Experimental data from circular dichroism (CD) spectroscopy suggest that these proteins are stable and well-folded (figures explained in the key below).

Note that our testing is not yet complete—we still do not know whether these proteins are folding into their intended conformation or some other, alternative structure. For that we will need atomic-resolution data from x-ray crystallography or other methods.

Susume (Anthropic Dreams) — Puzzle 1248

Waya, Galaxie, Susume (Anthropic Dreams) — Puzzle 1297

fiendish_ghoulPuzzle 1299

fiendish_ghoulPuzzle 1299

(A) Cartoon diagram of each Foldit player-designed protein. All of these designs feature α-helices packed against a single β-sheet, but no two designs share the same fold.

(B) Rosetta@home folding predictions (described here). Rosetta@home was able to successfully predict the structure of each design based on its amino acid sequence. The "funneled" cloud of red points reaching toward the lower-left corner of each plot indicates that Rosetta is able to reconstruct the intended fold from sequence information alone, and that the intended fold is furthermore predicted to be the most stable.

(C) The circular dichroism (CD) spectrum of purified protein shows that each protein contains significant secondary structure. This characteristic CD signature—with a broad, flat trough between 208 and 222 nm—suggests that both α-helices and β-sheets are present at 25°C (blue trace). We see that most of this structure is retained at 95°C (red trace), and that lost structure can be recovered upon cooling back to 25°C (green trace).

(D) Each protein is fairly thermostable, retaining a strong CD signal at 220 nm as it is heated from 25°C to 95°C.

(E) These proteins are unfolded by titration of concentrated guanidinium chloride (a chaotropic agent). The steep, sigmoidal transition from the folded to the unfolded state suggests that each of these proteins folds via a cooperative, two-state mechanism.

Crystallization Trials

The next step is to try to crystallize these proteins. Under very specific conditions, a concentrated sample of purified protein will self-organize into a highly-ordered crystal lattice. Protein crystals are useful to us because they comprise a large number (think trillions) of identical protein molecules all locked into the same orientation. If we aim a focused beam of x-rays at a protein crystal, electrons in the ordered crystal lattice will diffract the x-rays to produce an ordered diffraction pattern. From this diffraction pattern we can infer the distribution of ordered electrons in the crystal at extremely high resolution, in the form of an electron density map, thus revealing the atomic structure of the crystallized protein.

Unfortunately, protein crystallization is a delicate process, and is very sensitive to subtle change in conditions. Different proteins require wildly different conditions for crystallization, and we have no way to predict which conditions will allow a particular protein to crystallize. Protein concentration, buffer, pH, salts, ligands, precipitants, temperature, and time can all be critical factors for crystal growth. Typically, a crystallographer will set up high-throughput crystal screens, incubating concentrated protein in large arrays with hundreds of different conditions, and monitor them over periods of weeks or months.

Ultimately, protein crystallization is a lottery. Many proteins are never successfully crystallized. But, with a little luck, we'll be able to grow crystals of some of these proteins, collect x-ray diffraction data, and determine their full structure.

( Posted by  bkoep 71 390  |  Wed, 03/01/2017 - 17:45  |  9 comments )
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Developed by: UW Center for Game Science, UW Institute for Protein Design, Northeastern University, Vanderbilt University Meiler Lab, UC Davis
Supported by: DARPA, NSF, NIH, HHMI, Amazon, Microsoft, Adobe, Boehringer Ingelheim, RosettaCommons