Today we report in Nature the design and initial applications of the first completely artificial protein switch that can work inside living cells to modify—or even commandeer—the cell’s complex internal circuitry.

The switch is dubbed LOCKR, short for Latching, Orthogonal Cage/Key pRotein.

“In the same way that integrated circuits enabled the explosion of the computer chip industry, these versatile and dynamic biological switches could soon unlock precise control over the behavior of living cells and, ultimately, our health,” said Hana El-Samad, the Kuo Family Professor of Biochemistry and Biophysics at UCSF and co-senior author of the reports.

LOCKR is made of multiple parts. One chain, called the Cage, sequesters a bioactive peptide. Binding of a second molecule, called the Key, to the Cage causes a change in conformation, exposing the peptide. By swapping out the identify of the caged peptide and by tuning binding affinities, different LOCKR switches can be created for a wide range of signaling outputs.

LOCKR can be used to modify gene expression, redirect cellular traffic, degrade specific proteins, and tightly interface with natural proteins. Together with our colleagues at UCSF, we also built new biological circuits that behave like autonomous sensors. These circuits detect cues from the cell’s internal or external environment and respond by making changes to the cell, just as a thermostat senses ambient temperature and directs a heating or cooling system to shut itself off when a desired temperature is reached.

The lead authors of the reports are Bobby Langan and Scott Boyken of the IPD and Andrew Ng of the UC Berkeley-UCSF Graduate Program in Bioengineering. Both Bobby and Scott have gone on to research positions at Lyell.

“Right now, every cell is responding to its environment,” said Bobby. “Cells receive stimuli, then have to figure out what to do about it. They use natural systems to tune gene expression or degrade proteins, for example.”

Bobby and colleagues set out to create a new way to interface with these cellular systems. They used Rosetta to create and tune LOCKR, testing their tool first in vitro then in vivo.

“LOCKR opens a whole new realm of possibility for programming cells,” said Ng. “We are now limited more by our imagination and creativity rather than the proteins that nature has evolved.”

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Read the full reports:

De novo design of bioactive protein switches

Modular and tunable biological feedback control using a de novo protein switch

 

Today we report in Science the identification of hundreds of previously uncharacterized protein–protein interactions in E. coli and the pathogenic bacterium M. tuberculosis. These include both previously unknown protein complexes and previously uncharacterized components of known complexes.

This research was led by postdoctoral fellow Qian Cong and included former Baker lab graduate student Sergey Ovchinnikov, now a John Harvard Distinguished Science Fellow at Harvard.

Augmented by sequences from over 40,000 bacterial genomes, the team assessed coevolution between 5.4 million pairs of E. coliproteins. After finding orthologs and building paired alignments, they used a local statistical model to identify over 21,000 putative protein–protein interactions. Three-dimensional models for proteins in each pair were generated and docked, leading to 804 pairs with the strongest evidence for coevolution.

When compared to predictions inferred from high-throughput experimental screening methods, this new coevolution-based method for identifying protein–protein interactions outperforms in both precision and recall on multiple benchmarks.

814 additional pairs were added to this high-confidence set by incorporating protein pairs reported to interact in experimental studies or on the same operon.

“Coevolution has been useful for understanding how specific proteins interact, but we can now use it as a tool for discovery,” said lead author Qian Cong. “We are going to apply this tool to more pathogens, and the human genome. Our success will depend on how much work other scientists put into annotating which parts of the genome are genes and which parts are something else.”

Read the full report: https://science.sciencemag.org/content/365/6449/185  PDF

Today we report the design of synthetic protein arrays that assemble on the surface of mica, a common and exceptionally smooth crystalline mineral. This work, which was performed in collaboration with the De Yoreo lab at PNNL, provides a foundation for understanding how protein-crystal interactions can be systematically programmed.

Our goal was to engineer artificial proteins to self-assemble on a crystal surface by creating an exact match between the pattern of amino acids in the protein and the atoms of the crystal.

“Biology has an amazing ability to organize matter from the atomic scale all the way up to blue whales,” said co-first author Harley Pyles, a graduate student at the Institute for Protein Design. “Now, using protein design, we can create brand new biomolecules that assemble from atomic- to millimeter-length scales. In this case, mica, a naturally occurring crystal, is acting like a big Lego baseplate on top of which we are assembling new protein architectures.”

Rosetta was used to engineer new proteins with customized patterns of electrical charge on their surfaces — new Lego blocks perfectly matched to the mica baseplate. Different designs formed different patterns when deposited on the mica surface, including crowded wires and highly organized honeycomb-like arrays.

“Even though we designed specific atomic-level interactions, we get these structures, in part, because the proteins are crowded out by the water and are forced to pack together,” said James De Yoreo. “This was unexpected behavior and demonstrates that we need to better understand the role of water in ordering proteins in molecular-scale systems.”

By redesigning parts of the proteins, the team was able to produce honeycomb lattices in which they could digitally tune the diameters of the honeycomb pores by just a few nanometers.

Designing atomically precise filaments and lattices from scratch could unlock entirely novel materials and new strategies for synthesizing semiconductor and metallic nanoparticle circuits for photovoltaic or energy storage applications. Alternatively, the protein honeycombs could be used as extremely precise filters, according to co-first author Shuai Zhang, a postdoctoral researcher at PNNL. “The pores would be small enough to filter viruses out of drinking water or filter particulates out of air,” he said.

Read the full report: https://www.nature.com/articles/s41586-019-1361-6  PDF

Citizen scientists can now use Foldit to successfully design synthetic proteins. The initial results of this unique collaboration appear today in Nature.

Brian Koepnick, a recent PhD graduate in the Baker lab, led a team that worked on Foldit behind the scenes, introducing new features into the game that they believed would help players home in on better folded structures.

Players were provided with a poly-isoleucine backbone in a fully extended conformation (60-100 residues in length). They had seven days to fold the backbone into a compact structure and assign a sequence specifying this new structure.

Scores in Foldit are calculated using Rosetta. By competing with one another to reach the highest score, Foldit players arrive at virtual proteins with extremely low energies (a high Foldit score corresponds to low protein energy). But since energy alone is not enough for protein design, the Foldit team made adjustments to the Foldit score function. These included requiring the presence of a hydrophobic core, limiting the placement of glycine and alanine, and other side-chain specific terms.

The team experimentally tested 146 Foldit designs. 56 were found to be stable monomers when expressed in E coli. X-ray crystallography and NMR were used to determine the structure of four Foldit designs, which agreed strongly with their design model.

Every step of the way, the team relied on the work of Foldit players to expose problems with the score function. Foldit players are excellent at exploring new kinds of protein folds. For this reason, Foldit players are incredibly helpful for identifying unanticipated weaknesses in Rosetta, and ultimately can improve our understanding of protein folding.

Now that Foldit players can accurately design high-quality proteins from scratch, we can start to challenge Foldit players with more applied protein design problems. Foldit players can now help to design proteins that can assemble into multi-component structures, or that can bind to biological targets as potent medicines, or that can degrade toxic chemicals.

Because Foldit depends on the cooperation and competition of its player community, our scientific ability grows rapidly with the number of Foldit players. We look forward to expanding the Foldit community and recruiting more creative and curious Foldit players!

Read the full manuscript: https://rdcu.be/bFE7R   PDF

Today the Baker lab shares some exciting collaborative results of their efforts to design rigid and tunable receptor dimerizers. The first authors of this report are Kritika Mohan, Stanford, and George Ueda, IPD.

From Science:

Exploring a range of signaling
Cytokines are small proteins that bind to the extracellular domains of transmembrane receptors to activate signaling pathways inside the cell. They often act by dimerizing their receptors, and changes in dimer orientation of the extracellular domains can change the signaling output. Mohan et al. systematically explored this tuning effect by designing a series of dimer ligands for the erythropoietin receptor in which they varied the distance and angle between monomers. The topology affected the strength of activation and differentially affected different pathways, which raises the potential for exploiting such ligands in medicinal chemistry.

Read the full report: https://science.sciencemag.org/content/364/6442/eaav7532  PDF

Natural proteins often shift their shapes in precise ways in order to function. Achieving similar molecular rearrangements by design, however, has been a long-standing challenge. Today, a team of researchers lead by scientists at the IPD report in Science the rational design of synthetic proteins that move in response to their environment in predictable and tunable ways.

The team, which included researchers from UW, HHMI, LBNL, and OSU, set out to create pH-responsive oligomers, or pROs, that self-assemble into designed configurations at neutral pH and cooperatively disassemble at lower pH.

The project was lead by Scott Boyken, a recent postdoctoral fellow in the Baker lab, who used a three-step procedure to create the dynamic proteins: first, parametric design was used to create helical-bundle backbones which were then fitted with histidine-rich hydrogen-bond networks using the HBNet algorithm. Finally, for each pRO, the remainder of the new protein sequence was assigned using Rosetta.

“Designing new proteins with moving parts has been a long-term goal of my postdoctoral work,” said Boyken. “Because we designed these proteins from scratch, we were able to control the exact number and location of the histidines. This let us tune the proteins to fall apart at different levels of acidity.”

Collaborators in the Wysocki Lab at OSU used native mass spectrometry to determine the amount of acid needed to cause disassembly of the proteins. They confirmed the design hypothesis that having more histidines at interfaces between the proteins would cause the assemblies to collapse more cooperatively.

Researchers in the Lee lab were able to show that these pROs can disrupt artificial membranes in a pH-dependent manner, mirroring the behavior of natural membrane fusion proteins which also contain amphipathic helices.

Follow-up experiments with the Lippincott-Schwartz lab showed that these proteins can also disrupt endosomal membranes in mammalian cells, making pROs an attractive tool for engineering the delivery of biologics into the cytoplasm through endosomal escape.

Read the full report here: https://science.sciencemag.org/content/364/6441/658  PDF

This week we report in NSMB a combined computational design and experimental selection approach for creating proteins that bind selectively to closely related receptor subtypes. This project was led by Luke Dang, a former Baker lab graduate student, and Yi Miao, a postdoctoral researcher in Christopher Garcia’s lab at Stanford.

Abstract:

To discriminate between closely related members of a protein family that differ at a limited number of spatially distant positions is a challenge for drug discovery. We describe a combined computational design and experimental selection approach for generating binders targeting functional sites with large, shape complementary interfaces to read out subtle sequence differences for subtype-specific antagonism. Repeat proteins are computationally docked against a functionally relevant region of the target protein surface that varies in the different subtypes, and the interface sequences are optimized for affinity and specificity first computationally and then experimentally. We used this approach to generate a series of human Frizzled (Fz) subtype-selective antagonists with extensive shape complementary interaction surfaces considerably larger than those of repeat proteins selected from random libraries. In vivo administration revealed that Wnt-dependent pericentral liver gene expression involves multiple Fz subtypes, while maintenance of the intestinal crypt stem cell compartment involves only a limited subset.

Read the full report here: https://www.nature.com/articles/s41594-019-0224-z    PDF

This week we report in JACS a general approach for designing self-assembling 2D protein arrays. This project was led by Zibo Chen, a recent Baker lab graduate student, and featured collaborators from the, DiMaio, De Yoreo and Kollman labs at UW.

Abstract:

Modular self-assembly of biomolecules in two dimensions (2D) is straightforward with DNA but has been difficult to realize with proteins, due to the lack of modular specificity similar to Watson-Crick base pairing. Here we describe a general approach to design 2D arrays using ​de novo designed pseudosymmetric protein building blocks. A homodimeric helical bundle was reconnected into a monomeric building block, and the surface was redesigned in Rosetta to enable self-assembly into a 2D array in the C 1 2 layer symmetry group. Two out of ten designed arrays assembled to μm scale under negative stain electron microscopy, and displayed the designed lattice geometry with assembly size up to 100 nm under atomic force microscopy. The design of 2D arrays with pseudosymmetric building blocks is an important step toward the design of programmable protein self-assembly via pseudosymmetric patterning of orthogonal binding interfaces.

Read the full report here: https://pubs.acs.org/doi/abs/10.1021/jacs.9b01978# PDF

Today we report in Cell our first computer-designed nanoparticle vaccine targeting respiratory syncytial virus, the primary cause of pneumonia in young children and the leading cause of infant mortality worldwide after malaria.

Although virtually every child will get infected by RSV before the age of three, an estimated 99 percent of deaths associated with the virus occur in developing countries. Despite substantial effort, there is not yet a safe and effective vaccine for RSV.

An international team co-led by researchers at our Institute has generated a first-of-its-kind vaccine that elicits broadly neutralizing antibodies against RSV in mice and monkeys, paving the way for human clinical trials.

“This is the first of many vaccine candidates we have made using this technology,” said senior author Neil King. By swapping out the proteins along the outside of the nanoparticle, Neil’s team hopes to create additional vaccines for diseases as diverse as HIV, malaria, and cancer.

Vaccines by design

Scientists in the King Lab created the vaccine candidate by fusing DS-Cav1, a stabilized version of the viral glycoprotein RSV F which is responsible for membrane fusion, onto their designed two-component protein nanoparticle platform. This yielded a vaccine that can be tuned to display a variable number of antigens by mixing different versions of the purified parts.

Vaccine researchers Brooke Fiala and Neil King in the lab.

With a computer-generated protein nanoparticle at its core, the new multivalent vaccine candidate — dubbed DS-Cav1–I53-50 — is more stable than the trimeric antigen alone. In laboratory testing, it exhibited no discernible loss in antibody binding performance after being stored at elevated temperatures for two weeks. This may translate into a vaccine that does not require refrigeration, greatly reducing the cost and complexity of global vaccine distribution.

The new nanoparticle vaccine based on DS-Cav1 was also ten times more potent in initial tests than DS-Cav1 alone, suggesting it may translate into a more effective vaccine with more durable protection. DS-Cav1 was developed at the National Institute for Allergy and Infectious Disease Vaccine Research Center at the National Institutes of Health and has been shown to elicit significantly higher neutralizing antibody titers than postfusion F in animals​ and humans. DS-Cav1 is itself being evaluated in a Phase 1 study by NIH as an RSV vaccine candidate.

The RSV vaccine team was led by researchers at UW and the Institute for Research in Biomedicine in Bellinzona, Switzerland. It also included scientists from the Fred Hutch Cancer Research Center in Seattle, USA; the Karolinska Institute in Stockholm, Sweden; the Vaccine Formulation Institute in Godalming, UK; the European Virus Bioinformatics Center in Jena, Germany; the Vaccine Formulation Laboratory at the University of Lausanne, Switzerland; and the ​Institute of Microbiology at ETH Zürich, Switzerland. The project was funded in part by the Bill and Melinda Gates Foundation.

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Read the full report here: https://www.cell.com/cell/fulltext/S0092-8674(19)30109-6 (PDF)

Today we report in Nature the first de novo designed proteins with anti-cancer activity.

These compact molecules were designed to stimulate the same receptors as IL-2, a powerful immunotherapeutic drug, while avoiding unwanted off-target receptor interactions. We believe this is just the first of many computer-generated cancer drugs with enhanced specificity and potency.

“People have tried for 30 years to alter IL-2 to make it safer and more effective, but because naturally occurring proteins tend not to be very stable, this has proved to be very hard to do,” said a lead author of the paper, Daniel-Adriano Silva, an IPD biochemist. “Neo-2/15 is very small and very stable. Because we designed it from scratch, we understand all its parts, and we can continue to improve it making it even more stable and active.”

“Neo-2/15 has therapeutic properties that are at least as good as or better than naturally occurring IL-2, but it was computationally designed to be much less toxic,” said another lead author, Umut Ulge, an internal medicine physician and IPD biochemist.

Daniel, Umut, Carl Walky and Alfredo Rubio from the IPD have started a company to help bring this exciting drug to market. We wish them the very best in their new venture!

Read the full report here: https://www.nature.com/articles/s41586-018-0830-7 (PDF)

To close out the year, Baker Lab scientists published a new report describing the creation of proteins that mimic DNA. We believe this breakthrough will aid the creation of bioactive nanomachines.

DNA is a widely used building material at the nanoscale because it is simple and predictable: A pairs with T and C pairs with G. Because of this, DNA strands can be programmed to click together into precise and increasingly complex structures. But DNA has drawbacks. It is not as bioactive as RNA, and not nearly as active as proteins. Bioactive protein assemblies run cells (kinetochores, polymerases, proteasomes, etc). What if designing them was as easy as clicking together DNA?

Using computational design, we created heterodimeric proteins that form double helices with hydrogen-bond mediated specificity. When a pool of these new protein zippers gets melted and then allowed to refold, only the proper pairings form. They are all-against-all orthogonal. With these new tools in hand, we can now begin constructing large protein-based machines that self-assemble in predictable ways.

This project was led by graduate student Zibo Chen and was done in collaboration with the Wysocki Lab at Ohio State University and the Sgourakis Lab at the UC Santa Cruz. The work used support from the SIBYLS program with SAXS and the ALS resources at LBNL, as well as the Argonne Leadership Computing Facility at ANL.

Read the full here: https://www.nature.com/articles/s41586-018-0802-y (PDF)

The basic parts of proteins — helices, strands and loops — can be combined in countless ways. But certain combinations are trickier than others. This week scientists from the IPD, along with collaborators in Brno and Santa Cruz, published the first-ever example of designed non-local beta-strand interactions.

Beta-sheet proteins carry out critical functions in biology, and hence are attractive scaffolds for computational protein design, but the de novo design of all-beta-sheet proteins from first principles has lagged far behind the design of all-alpha or mixed-alpha-beta domains.

Local beta-strand interactions occur when residues near one other hydrogen bond to form compact sheets. To get similar interactions from stretches of residues that are not close in primary sequence, a protein backbone must fold into a complex interwoven shape. The successful design of non-local beta-strand interactions demonstrates a significant advance in our ability to control both fine features (such as precise hydrogen bonding) and global features (such as complex topology) in proteins and opens the door to the design of a broad range of non-local beta-sheet structures.

By studying loops that connect unpaired beta-strands (beta-arches), the team identified a series of structural relationships between loop geometry, side chain directionality and beta-strand length that arise from hydrogen bonding and packing constraints on regular beta-sheet structures. They used these rules to de novo design jellyroll structures with double-stranded beta-helices formed by eight antiparallel β-strands. NMR of a hyperthermostable design closely matched the computational model, demonstrating accurate control over the beta-sheet structure and loop geometry.

Read the full report here: https://www.nature.com/articles/s41594-018-0141-6 (PDF)

In the summer of 1961, Osamu Shimomura drove across the country in a cramped station wagon to scoop jellyfish from the docks of Friday Harbor. He wanted to discover what made them glow.

It took Shimomura and other biochemists more 30 years to find a full answer. By then, recombinant DNA technology allowed researchers to clone and characterize the two proteins responsible: aequorin and GFP. The latter would earn Shimomura his share of the 2008 Nobel Prize.

GFP, a 238-residue beta-barrel with a covalently linked chromophore, transformed how scientists study cells and the molecules in them. As a genetic tag, GFP has illuminated the inner workings of human brain cells, bacteria, fungi and more.

This week, scientists from the IPD report in Nature the design of a completely artificial fluorescent beta-barrel protein.

Many natural proteins evolved to bind small molecules. Reengineering such proteins is rarely straightforward, limiting how they can be applied. The new findings demonstrate that proteins unlike any found in nature can be rationally-designed to bind to and act on specific small molecules with high precision and affinity.

The lead authors of the paper are Jiayi Dou, Ph.D and Anastassia A. Vorobieva, Ph.D., then both senior fellows in the Baker lab.

Anastassia Vorobieva with her son Alexandre (left) and Jiayi Dou (right).

To make the fluorescent protein the researchers had to achieve another first: Creating beta-barrels from scratch. The fold was ideal because one end of its cylindrical shape could be used to stabilize the protein while the other could be used to create a cavity that would serve as the binding site for the target molecule, DFHBI. In nature, beta-barrels proteins bind a wide range of small molecules.

Rosetta was used to design the scaffold de novo. To create the cavity, the team used a new docking algorithm called the “Rotamer Interaction Field” or RIF, developed by William Sheffler, Ph.D., a senior research scientist in the Baker lab, that rapidly identifies all potential structures of cavities that fulfill the prerequisites for binding specific molecules.

The designed protein absorbs blue and emits cyan light. It is stable up to 75°C.

“It worked in bacterial, yeast and mammalian cells,” said Dou, “and being half the size of green fluorescent protein should be very useful to researchers.”

“Equally important,” Baker added, “it greatly advances our understanding of the determinants of protein folding and binding beyond what we have learned from describing existing protein structures.”

Written by Ian Haydon

Read the article here: https://www.nature.com/articles/s41586-018-0509-0
View the PDF here: Fluorescent proteins designed from scratch

Today at 11am, the paper titled “A Computationally Designed Hemagglutinin Stem-Binding Protein Provides In Vivo Protection from Influenza Independent of a Host Immune Response” was published to the PLOS Pathogen website. This paper was contributed to by several IPD members, including Aaron Chevalier, Jorgen Nelson, Lance Stewart, Lauren Carter, and David Baker. The research was performed in collaboration with colleagues in Deborah Fuller’s lab at UW’s Department of Microbiology. You can find the paper here. Scroll down for the official press release.

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Fighting Flu with Designer Drugs: A New Compound Given Before or After Exposure Fends Off Different Influenza Strains

A study published on February 4th in PLOS Pathogens reports that a new antiviral drug protects mice against a range of influenza virus strains. The compound seems to act superior to Oseltamivir (Tamiflu) and independent of the host immune response.
Influenza viruses under the microscope look a bit like balls covered with spikes. The spikes are actually two different proteins, hemagglutinin (HA) and neuraminidase (NA). Both proteins consist of an inner stem region (which doesn’t differ much between flu strains), and a highly variable outer blob. The individual variants fall into designated groups, and this is how flu strains are categorized (for example as H1N1, or H3N5).
Ongoing mutations that change the HA and NA blobs are the reason why flu vaccines differ from season to season; they are based on researchers’ best guesses of what next year’s prominent strains will look like. And dangerous pandemic strains often have radically new blobs against which existing immunity is limited.
In the search for drugs that act broadly against different influenza strains, researchers had previously shown that antibodies against the HA stem region can prevent influenza infection. Such antibodies are protective, at least in part, because they activate the host immune response which then destroys the whole HA/antibody complex. The approach, then, depends on a fully functional immune system—which is not present in infants, the elderly, or immune-compromised individuals.
Inspired by the earlier work, Deborah Fuller from the University of Washington in Seattle, USA, who is interested in developing influenza drugs and vaccines, teamed up with David Baker, also at the University of Washington, who is an expert in computational protein design. Together with colleagues, they set out to design small molecules that—like the protective antibodies—bind to the HA stem, and to test whether these small molecules can protect against influenza infection. Designed to mimic antibodies, the small molecules bind the virus in a similar manner. However, because they don’t engage the immune system the way antibodies do, and because of questions of stability and potency, it was not clear whether they would be able to prevent infection in animals, or eventually, in humans.
Before testing their molecules in animals, the researchers optimized their favorite small molecule candidate by systematically generating thousands of versions and testing how tightly they bound HA stems from seven different influenza strains. As they predicted, the resulting molecule, called HB36.6, protected cells against influenza virus infection in vitro (i.e., in test tubes).
The researchers next tested HB36.6 in “challenge experiments” in mice. They gave mice a single intranasal dose of the drug and 2 hours, 24 hours, or 48 hours later injected them with a normally lethal dose of influenza virus. This one-time HB36.6 treatment, when given up to 48 hours before the challenge, conveyed complete protection: All of the treated mice survived and had little weight loss, whereas all untreated control mice died after losing a third of their body weight or more. Intranasal HB36.6 was also able to protect mice after they had been exposed to flu virus, when administered either as a single dose within a day after exposure, or when it was given daily for four days starting 24 hours after exposure.
This protection does not depend on an intact host immune response. When the researchers repeated the challenge experiments in two different immune-deficient mouse strains, they found that HB36.6 can protect these mice as well.
Comparing HB36.6 with Oseltamivir, the researchers found that a single dose of HB36.6 provided better protection than 10 doses (twice daily for 5 days) of Oseltamivir. Furthermore, when they gave a low dose of HB36.6 post-infection (which by itself was not able to afford full protection) together with twice-daily doses of Oseltamivir, all the mice survived, indicating a synergistic effect when the two antiviral drugs are combined.
Their results, the researchers conclude, “show that computationally designed proteins have potent anti-viral efficacy in vivo and suggests promise for development of a new class of HA stem-targeted antivirals for both therapeutic and prophylactic protection against seasonal and emerging strains of influenza”.

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Custom design with atomic level accuracy enables researchers to craft a whole new world of proteins

Naturally occurring proteins are the nanoscale machines that carry out essentially all of the critical functions in living things.

While it has been known for over 40 years that the sequence of amino acids completely determines the shape of the protein, it has been very challenging to predict from the amino acid sequence of the protein its three-dimensional structure, and conversely, to come up with brand new amino acid sequences which fold up into hitherto unseen structures.

Over the past months, scientists at the Institute for Protein Design at the University of Washington and the Fred Hutch, along with colleagues at other institutions, have reported advances in two long-standing problem areas related to the construction of new proteins from scratch.

“It has been a watershed year for protein structure prediction and design,” said UW Medicine researcher David Baker, a University of Washington professor of biochemistry, Howard Hughes Medical Institute investigator and head of the Institute for Protein Design.

The protein structure problem is about figuring out how a protein’s chemical makeup predetermines its molecular structure, and in turn, its biological role.   UW researchers have developed powerful new algorithms using co-evolution data from DNA sequences to make unprecedented highly accurate blind ‘ab initio’ structure predictions of large proteins (>200 amino acids in length). This has opened the door to accurate prediction of the structures for hundreds of thousands of newly discovered proteins in the ocean, soil, and gut microbiome.

Equally difficult is the second problem, which is designing amino acid sequences that will fold into brand new protein structures. Breakthroughs demonstrate that it is now possible to make brand new amino acid sequences with exacting precision for folds inspired by the natural world; and more importantly to make amino acid sequences from scratch for totally novel unknown folds, far surpassing what is predicted to occur in natural proteins.

The new proteins are designed with the help of volunteers around the world participating in the Rosetta@Home distributed computing project. The designed amino acid sequences are encoded in synthetic genes, the proteins are produced in the laboratory, and their structures determined with X-ray crystallography.   The computer models in almost all cases match the experimentally determined crystal structures with near atomic level accuracy.

Researchers report new protein designs for barrels, sheets, rings, and screws –all with near atomic level accuracy. This builds on previous reports of designed protein cubes and spheres; providing proof that it is possible to make a totally new class of protein materials.

With these advances in both protein structure prediction and molecular design, Institute for Protein Design researchers hope to build a new world of proteins with exact specifications for performing critically needed tasks in medical, environmental and industrial arenas.

Examples of their goals are nanoscale tools that:

boost the immune response against HIV and other recalcitrant viruses

block the flu virus so that it can’t infect cells

deliver drugs to cancer cells with precision and reduced side effects

stop allergens from causing symptoms

neutralize deposits, called amyloids, thought to damage vital tissues in Alzheimer’s disease

mop up medications in the body as an antidote

fulfill other diagnostic, therapeutic, and clean energy needs

Just as the manufacturing industry was revolutionized by creating interchangeable parts designed to precise specifications, custom designed protein modules with the right twist, turns, and connections for their modular assembly is a bold new direction for biotechnology.

Results providing proof of this possible future have been reported in recent months by researchers the UW Institute for Protein Design in collaboration with researchers at the Fred Hutch, Max Planck Institute for Developmental Biology, Janelia Research Campus, and the Institute for Molecular Science in Japan.

 

 

Evolution offers clues to shaping proteins: The function of many proteins tends to stay the same across species, even after their amino acid sequences have changed over billions of years of evolution. Locating co-evolved pairs of amino acids helps calculate their proximity when the molecule folds. UW graduate student Sergey Ovchinnikov applied this co-evolution DNA sequence analysis in an E-Life paper published on September 3, 2015 entitled “Large-scale determination of previously unsolved protein structures using evolutionary information” that illuminated for the first time the structures of 58 families of proteins containing hundreds of thousands of additional structurally related family members.

“This achievement was a grand slam home run in the history of protein structure prediction,” said Baker.

 

 

Modular construction of proteins with repeating motifs: Proteins composed of repeated modules, similar to interlocking Lego® blocks, are common in the natural world. Two papers published in the December 16 issue of Nature entitled, “Exploring the repeat protein universe through computational protein design,” and “Rational design of alpha-helical tandem repeat proteins with closed architectures,” shows that existing repeat proteins occupy only a small fraction of the available space, and that it is possible to design totally new proteins with precisely specified geometries that go far beyond what nature has achieved. The work was led by postdoctoral fellows TJ Brunette, Fabio Parmeggiani and Po-Ssu Huang in the lab of David Baker at the University of Washington Institute for Protein Design and Lindsey Doyle and Phil Bradley at the Fred Hutchinson Cancer Research Institute in Seattle.

 

 

Barrel-fold design: , Baker lab postdoctoral fellow Po-Ssu Huang, together with Birte Höcker at the Max Planck Institute for Developmental Biology (Tübingen, Germany) discovered the critical but elusive design principles for a barrel-shaped fold underpinning many natural enzyme molecules. The custom designed barrels folds were built at the Institute for Protein Design and reported on November 23, 2015 in the Nature Chemical Biology paper, “De novo design of a four-fold symmetric TIM-barrel protein with atomic-level accuracy.” This breakthrough has opened the door for bioengineers to generate totally new enzymes that speed up chemical reactions by positioning smaller molecules in custom barrel compartments.

Self-assembling apparatus: Naturally occurring ordered protein arrays along a flat plane are found in bacteria, the heart, and other muscles. Overcoming protein interaction complexities, researchers at UW Institute for Protein Design and the Janelia Research Campus of the Howard Hughes Medical Institute succeeded in programming proteins to self-assemble into novel symmetric, 2-dimensional sheets of protein lattice patterns. UW graduate student Shane Gonen in the Baker lab together with his brother Tamir Gonen at Janelia described their work in the June 19, 2015 issue of Science, “Design of ordered two-dimensional arrays mediated by non-covalent protein-protein interfaces.” This research has application in the design self-assembling protein nanomaterials, especially those that could serve as efficient sensors or light harvesters.

Precision sculpting: Protein designers are continuously refining the principles for fashioning ideal protein structures. The latest paper in the October 6, 2015 Proceedings of the National Academy of Sciences, “Control over overall shape and size in de novo designed proteins” further explains methods for systematically varying protein architecture inspired by nature. Such finesse is needed in optimizing designed proteins to take on exact shapes to perform specified functions.   This work has been led by Baker lab graduate student Yu-Ru Lin in collaboration with Nobuyasu Koga at the Institute for Molecular Science in Japan.

Funding Sources:

The Institute of Protein Design has been funded by several federal agencies, including National Institutes of Health, U.S. Department of Energy, National Science Foundation, U.S. Defense Threat Reduction Agency, and U.S. Air Force Office of Scientific Research, the Washington Research Foundation, the Life Sciences Discovery Fund, as well as through private support.

The Institute also depends on a cadre of citizen scientists around the world who volunteer their personal and computer time for protein folding prediction studies through Rosetta@home and the multi-player on-line protein folding game Foldit.

 

A similar story was also published in UW Health Science’s Newsbeat. Read it here.

In the early 1990s, researchers in the field of protein structure prediction were challenged by the problem of how to impartially judge the accuracy of prediction algorithms.  This realization led the protein structure prediction the community to start the Critical Assessment of protein Structure Prediction (CASP), a community-wide, worldwide experiment for protein structure prediction taking place every two years since 1994.   In each CASP, an independent scientific advisory board solicits other researchers to submit experimentally verified, but unpublished, 3D protein structures to CASP.   The linear amino acid sequences of these proteins are then provided to structure prediction researchers, who each have an equal and limited amount of time to submit final structure predictions to the CASP advisory board.  The submitted structure predictions are then compared to the experimentally verified structures using the same metrics for all CASP contributors.  Even though the primary goal of CASP is to help advance methods for identifying protein 3D structure given only its linear amino acid sequence, many view the experiment more as a “world championship” in protein structure prediction.

Over a 16 year period (CASP3-11), the Baker lab has consistently achieved top performance in the hardest category of structure prediction; the “Twilight Zone” where the linear amino acid sequence of the protein shares no discernable relation to any publicly available 3D structure. In 2014 this culminated in our highly accurate blind structure predictions of two large proteins each >200 amino acids in length. Our methods involve using DNA sequence information to help us predict the 3D structures of proteins.

We recently published these results in E-life, and the results are getting significant attention.

You can read the general-public summary here:
http://elifesciences.org/content/4/e09248/abstract-2

Or find the whole thing here:
http://elifesciences.org/content/4/e09248

Also, learn about the first author of the paper, Sergey Ovchinnikov, by watching this interview: