Category: IPD Publication

Design of novel cavity containing proteins

An example of computationally designed proteins made of curved beta-sheets and helices forming cavities with different sizes and shapes. (Benjamin Basanta)

The latest paper coming out from the IPD was published today on the Science website. It’s titled “Principles for designing proteins with cavities formed by curved β sheets” with first co-authors Enrique Marcos and Benjamin Basanta, a former and current IPD member, respectively. Other IPD members on the paper include Tamuka Chidyausiku, Gustav Oberdorfer, Daniel-Adriano Silva, Jiayi Dou, and David Baker. Dr. Baker wrote a summary about the publication:

Some of the key functions of the proteins in our bodies and in all living things are to catalyze chemical reactions—speed up the rates by many orders of magnitude-and to sense and respond to small molecules in the body and in the environment.  New proteins that catalyze chemical reactions and/or sense and respond to compounds not found in nature would have wide use in medicine and industry.

Another example of computationally designed proteins made of curved beta-sheets and helices forming cavities with different sizes and shapes (Tamuka Chidyausiku)

Computational protein design can in principle be used to generate such new catalysts and receptors, but a major challenge to accomplishing this has been the inability to design proteins with cavities within which the catalysis or small molecule binding can take place.  This paper describes a general approach for designing proteins with cavities with tunable size and shape. The method opens the door to design of new catalysts and binding proteins [by generating proteins with appropriately sized and shaped cavities to hold the small molecule and lining the cavity with amino acid functional groups to carry out catalysis and/or binding].

Read the UW’s HS NewsBeat write-up here.

Hyper-stable Designed Peptides and the Coming of Age for De Novo Protein Design

Small constrained peptides combine the stability of small molecule drugs with the selectivity and potency of antibody-based therapeutics. However, peptide-based therapeutics have largely remained underexplored due to the limited diversity of naturally occurring peptide scaffolds, and a lack of methods to design them rationally.  New computational design and wet lab methods developed at the Institute for Protein Design have now opened the door to rational design of a whole new world of hyper-stable drug-like peptide structures.

In an article published in Nature this week, Baker lab / IPD scientists and their collaborators describe the development of computational methods for de novo design of constrained peptides with exceptional stabilities. They used these computational methods to design 18-47 residue constrained peptides with diverse shapes and sizes. The designed peptides presented in the paper cover three broad categories:

1) genetically encodable disulfide cross-linked peptides,

2) synthetic disulfide cross-linked peptides with non-canonical sequences, and

3) cyclic peptides with non-canonical backbones and sequences.

Experimentally determined structures for these peptides are nearly identical to their design models.

EHEE Designed Peptide, Visual Illustration by Vikram Mulligan. The molecular surface is shown as a transparent blue shell, and the peptide’s backbone structure is pink. The amino acid’s side chains are white (carbon atoms), blue (nitrogen atoms) and red (oxygen atoms). The crisscrossing bonds that give the peptide its constrained, stable shape are in bright white.

By including D-amino acids (mirror images of the L-amino acids), and thus expanding the palette of building blocks, Baker lab scientists designed peptides in a sequence and structure space sampled rarely by Nature. Indeed, the article describes successful design of a cyclic 2-helix peptide of mix chirality that represents a shape beyond natural secondary- and tertiary structure.

These designed peptides also exhibit exceptional stability to thermal and chemical denaturation, and thus could serve as attractive scaffolds for design of novel peptide-based therapeutics. More broadly, development of this new computational toolkit to precisely design constrained peptides opens the door for “on-demand” development of a new generation of peptide-based therapeutics.

These and other breakthroughs in computational protein design are also covered in a Nature review article by David Baker, Po-Ssu Huang, and Scott E. Boyken entitled “The coming of age of de novo protein design”, part of special supplement on The Protein World.

Illustrations of designed peptides with different configurations of two structures: tightly wound ribbons and flat, arrow-shaped ribbons.
Illustrations of designed peptides with different configurations of two structures: tightly wound ribbons and flat, arrow-shaped ribbons.

See additional news coverage

HS NewsBeat, Hutch News,

Funding Sources

The National Institutes of Health provided partial support for this work through grants P50 AG005136, T32-H600035., GM094597, GM090205, and HHSN272201200025C.  Additional funding was provided by The Three Dreamers.

Designed Protein Containers Push Bioengineering Boundaries

Earlier this month, Baker lab researchers reported the computational design of a hyperstable 60-subunit protein icosahedron in Nature (Hsia et al); icosahedral protein structures are commonly observed in natural biological systems for packaging and transport (e.g. viral capsids). The described design was composed of 60 trimeric protein building blocks that self-assembled in a nanocage.

In new work published today, Baker lab scientists and collaborators have taken this work to an exciting new level by engineering 120-subunit icosahedral nanocages that self-assemble from not one, but two distinct protein components. The new designed proteins are described in the latest issue of Science in a paper entitled “Accurate design of megadalton-scale multi-component icosahedral protein complexes”.

In this paper, former Baker lab graduate student Jacob Bale, Ph.D. and collaborators describe the computational design and experimental characterization of ten two-component protein complexes that self-assemble into nanocages with atomic-level accuracy. These nanocages are the largest designed proteins to date with molecular weights of 1.8-2.8 megadaltons and diameters comparable to small viral capsids. The structures have been confirmed by X-ray crystallography (see figure). The advantage of a multi-component protein complex is the ability to control assembly by mixing individually prepared subunits. The authors show that in vitro mixing of the designed subunits occurs rapidly and enables controlled packaging of negatively charged GFP by introducing positive charges on the interior surfaces of the two copmonents.

The ability to design, with atomic-level precision, these large protein nanostructures that can encapsulate biologically relevant cargo and that can be genetically modified with various functionalities opens up exciting new opportunities for targeted drug delivery and vaccine design. A link to the paper and additional information is below:

Link to PDF can be found here

Featured article and video in Science magazine:

This protein designer aims to revolutionize medicines and materials” – Science

Other related news items:

Virus-inspired contender design may lead to cell cargo ships” – UW Health Sciences NewsBeat

Large Protein Nanocages Could Improve Drug Design and Delivery” – HHMI News

Biggest Little Self-Assembling Protein Nanostructures Created” – DARPA News and Events


Watch a short video about the designed protein nanocages

See specific descriptions on these nanoparticles from Jacob Bale, Neil King, and Yang Hsia

Nature provides many examples of self- and co-assembling protein-based molecular machines, including icosahedral protein cages that serve as scaffolds, enzymes, and compartments for essential biochemical reactions and icosahedral virus capsids, which encapsidate and protect viral genomes and mediate entry into host cells. Inspired by these natural materials, we report the computational design and experimental characterization of co-assembling two-component 120-subunit icosahedral protein nanostructures with molecular weights (1.8-2.8 MDa) and dimensions (24-40 nm diameter) comparable to small viral capsids. Electron microscopy, SAXS, and X-ray crystallography show that ten designs spanning three distinct icosahedral architectures form materials closely matching the design models. In vitro assembly of independently purified components reveals rapid assembly rates comparable to viral capsids and enables controlled packaging of molecular cargo via charge complementarity. The ability to design megadalton-scale materials with atomic-level accuracy and controllable assembly opens the door to a new generation of genetically programmable protein-based molecular machines.

Reprinted with permission from AAAS
Reprinted with permission from AAAS

Flu Binder Paper Debuts in PLOS Pathogens

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.

FluBinder Rendered by Vikram Mulligan, PhD
FluBinder Rendered by Vikram Mulligan, PhD

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”.

Big moves in protein structure prediction and design

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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.

CASP3-11 Results Published in E-Life

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:

Or find the whole thing here:

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

August IPD News Roundup



Following the groundbreaking 2014 Nature paper describing the development of a computational method to design multi-component coassembling protein nanoparticles, comes a publication in Protein Science from Baker lab graduate student Jacob Bale and collaborators. Titled “Structure of a designed tetrahedral protein assembly variant engineered to have improved soluble expression“, the paper reports a variant of a previously low yielding tetrahedral designed material for which structure determination was difficult. The new variant described in the paper had a much improved yield after redesign and the structure obtained agreed with the computational model with high atomic-level accuracy. The methods used here to improve soluble protein yield will be generally applicable to improving the yield of many designed protein nanomaterials.



Congratulations to newly minted PhDs and graduates of the Baker lab Dr. Shawn Yu and Dr. Ray Wang! Both defended their dissertations this month. Dr. Yu gave a talk on “Computational design of interleukin-2 mimetics” and Dr. Wang spoke about “Protein structure determination from cryoEM density maps”. We wish them the best of the luck in their next steps!

The annual RosettaCON meeting was held July 29-Aug1 at the beautiful Sleeping Lady Mountain Resort in Leavenworth, WA. Many IPD scientists attended the conference, heard talks from researchers in Rosetta labs across the country, presented posters on their own research, and socialized with the larger Rosetta community.

New Science paper: Designed 2-D protein arrays

A new Science paper is out from IPD faculty Dr. David Baker titled Design of ordered two-dimensional arrays mediated by noncovalent protein-protein interfaces. Read the abstract below and the article at the link:

We describe a general approach to designing two-dimensional (2D) protein arrays mediated by noncovalent protein-protein interfaces. Protein homo-oligomers are placed into one of the seventeen 2D layer groups, the degrees of freedom of the lattice are sampled to identify configurations with shape-complementary interacting surfaces, and the interaction energy is minimized using sequence design calculations. We used the method to design proteins that self-assemble into layer groups P 3 2 1, P 4 2(1) 2, and P 6. Projection maps of micrometer-scale arrays, assembled both in vitro and in vivo, are consistent with the design models and display the target layer group symmetry. Such programmable 2D protein lattices should enable new approaches to structure determination, sensing, and nanomaterial engineering.

Shown is a 2D array with P 6 symmetry. (Left) the P 6 lattice has two degrees of freedom available for sampling. Sixfolds are represented by hexagons. (Middle) Computationally designed 2D array. (Right) Electron microscopy of designed P 6 array.

Designer Proteins to Target Cancer Cells

BINDI Designer Protein What if scientists could design a completely new protein that is precision-tuned to bind and inhibit cancer-causing proteins in the body? Collaborating scientists at the UW Institute for Protein Design (IPD) and Molecular Engineering and Sciences Institute (MolES) have made this idea a reality with the designed protein BINDI. BINDI (BHRF1-INhibiting Design acting Intracellularly) is a completely novel protein, based on a new protein scaffold not found in nature, and designed to bind BHRF1, a protein encoded by the Epstein-Barr virus (EBV) which is responsible for disregulating cell growth towards a cancerous state. Learn more here.

Accurate Design of Co-Assembling Multi-Component Protein Nanomaterials

TwoComponentthumbnailA new paper is out in the June 5 issue of Nature entitled Accurate design of co-assembling multi-component protein nanomaterials. Scientists at the Institute for Protein Design (IPD), in collaboration with researchers at UCLA and HHMI, have built upon their previous work constructing single-component protein nanocages and can now design and build self-assembling protein nanomaterials made up of multiple components with near atomic-level accuracy. Learn more about this innovative work at this link.

Design of Activated Serine-Containing Catalytic Triads with Atomic-Level Accuracy

Catalytic Serine TriadBaker lab members published in Nature Chemical Biology a paper entitled “Design of activated serine-containing catalytic triads with atomic-level accuracy“, describing the computational design of proteins with idealized serine-containing catalytic triads which can capture and neutralize organophosphate probes.  This work has utility in design of scavengers of environmental toxins. Learn more at this link.

A Computationally Designed Metalloprotein Using an Unnatural Amino Acid

Mulligan metal binder figureWhat if scientists could design proteins to capture specific metals from our environment?  The utility for cleaning up metals from waste water, soils, and our bodies could be tremendous.  Dr. Jeremy Mills and collaborators in Dr. Baker’s group at the University of Washington’s Institute for Protein Design (IPD) address this challenge in the first reported use of computational protein design software, Rosetta, to engineer a new metal binding protein (“MB-07”) which incorporates an “unnatural amino acid” (UAA) to achieve very high affinity binding to metal cations.  Learn more at this link.

Computational Design of a pH Sensitive Antibody Binder

Designed pH-dependent Fc binder (blue) exploits protonation of Histidine-433 (orange) in the Fc portion Immunoglobulin G (IgG, light cyan surface)

Purification of antibody IgG from crude serum or culture medium is required for virtually all research, diagnostic, and therapeutic antibody applications.  Researchers at the Institute for Protein Design (IPD) have used computational methods to design a new protein (called “Fc-Binder”) that is programed to bind to the constant portion of IgG (aka “Fc” region) at basic pH (8.0) but to release the IgG at slightly acidic pH (5.5).  Published on-line at PNAS (Dec. 31, 2013), the paper is entitled Computational design of a pH-sensitive IgG binding protein, co-authored by Strauch, E. – M., Fleishman S. J., & Baker D.  Learn more at this link.

Computational Protein Design To Improve Detoxification Rates Of Nerve Agents

Phosphotriesterase EngineeringV-type nerve agents are among the most toxic compounds known, and are chemically related to pesticides widespread in the environment. Using an integrated approach, described in an ACS Chemical Biology paper entitled Engineering V-type nerve agents detoxifying enzymes using computationally focused libraries, Dr. Izhack Cherny, Dr. Per Greisen, and collaborators increased the rate of nerve agent detoxification by the enzyme phosphotriesterase (PTE) by 5000-fold by redesigning the active site.   Learn more at this link.

Computational Design Of A Protein That Binds Polar Surfaces

Enzyme Inhibitor DesignIn a Journal of Molecular Biology publication entitled Computational design of a protein-based enzyme inhibitor, Dr. Erik Procko and collaborators describe the computational design of a protein-based enzyme inhibitor that binds the polar active site of hen egg lysosome (HEL).  Computational design of a protein that binds polar surfaces has not been previously accomplished.  Learn more at this link.

One Small Molecule Binding Protein, One Giant Leap for Protein Design

Illustration rendering of the digoxigenin binding protein was prepared by Vikram Mulligan

Reported on-line  in Nature (Sept. 4, 2013) researchers at the Institute for Protein Design describe the use of Rosetta computer algorithms to design a protein which binds with high affinity and specificity to a small drug molecule, digoxigenin a dangerous but sometimes life saving cardiac glycoside.  Learn more at this link.



IPD Researchers Publish New Protocols for Preparing Protein Scaffold Libraries for Functional Site Design

Pareto-optimal refinementIPD researchers in the Baker group have published new computational protocols for preparing protein scaffold libraries for functional site design.  Their paper entitled “A Pareto-optimal refinement method for protein design scaffolds improves the search for amino acids with the lowest energy subject to a set of constraints specifying function.  Learn more at this link.

Centenary Award and Frederick Gowland Hopkins Memorial Lecture

Centenary Award LectureDr. David Baker, Director of the IPD delivered the Centenary Award and Frederick Gowland Hopkins Memorial Lecture at  at the MRC Laboratory of Molecular Biology, Cambridge, UK, on December, 13, 2012.   Baker’s lecture entitled “Protein folding, structure prediction and design”  can be read at this published link.  

See:  Baker, D. (2014).  Protein folding, structure prediction and design.. Biochemical Society transactions. 42(2), 225-9.

Proteins Made to Order. Researchers at the IPD Design Proteins from Scratch with Predictable Structures

Design of Ideal Folded ProteinsA team from David Baker’s laboratory at the University of Washington in Seattle have described a set of “rules” for the design of proteins from scratch, and have demonstrated the successful design of five new proteins that fold reliably into predicted conformations.  Their work was published Nature.  Learn more at this link.

Computational Design of Self-Assembling Protein Nanomaterials with Atomic Level Accuracy

Self Assembling NanomaterialsIPD researchers in the Baker group have published in Science a paper entitled “Computational design of self-assembling protein nanomaterials with atomic level accuracy.”  They describe a general computational method for designing proteins that self-assemble to a desired symmetric architecture.  Protein building blocks are docked together symmetrically to identify complementary packing arrangements, and low-energy protein-protein interfaces are then designed between the building blocks in order to drive self-assembly.  Read more at this link.