![\"Researcher](\"\/\/media.nature.com\/w800\/magazine-assets\/d41586-019-02251-x\/d41586-019-02251-x_16920424.jpg\")
<\/div>\n<\/div>By designing a protein from the ground up, researchers can create molecules with forms and functions not found in nature.<\/span>Credit: Brian DalBalcon<\/p>\n<\/figcaption><\/figure>\n <\/p>\n <\/p>\n Cassie Bryan\u2019s success at crafting a protein that worked as she intended was a long time coming. When it finally happened, after six long years, she hit the bar and celebrated with beers \u2014 and a karaoke rendition of Joan Jett\u2019s \u2018Bad Reputation\u2019.<\/p>\n Bryan joined the protein-design laboratory of David Baker in 2012 as a graduate student at the University of Washington, Seattle. Her project was to design a protein that could bind to PD-1 \u2014 a protein on the surface of white blood cells that throttles the activity of the immune system.<\/p>\n At first, Bryan did what protein engineers have long done: she tweaked an existing natural protein to make it bind to PD-1. But, two years into her project, she decided that approach was going nowhere. And an explosion of interest in PD-1 as a cancer-immunotherapy target during that time meant her goalposts kept moving. Meanwhile, the lab was growing ever more adept at a different approach. Instead of modifying natural proteins to fit a particular need, the Baker lab began creating proteins from scratch.<\/p>\n Although considerably harder than conventional protein engineering,\u00a0de novo<\/i>\u00a0protein design offers several advantages, says Brian Kuhlman, a protein engineer at the University of North Carolina at Chapel Hill, who as a postdoc with Baker in 2003 led the lab\u2019s first\u00a0de novo<\/i>\u00a0success1<\/a><\/sup>, a 93-amino-acid molecule called Top7. Natural proteins are difficult to modify without disrupting their overall structure. But by making proteins from scratch, researchers can design proteins to be more forgiving. They can build enzymes with activities unknown to nature, using co-factors and amino acids that are not part of the standard macromolecular toolkit. And scientists can test their understanding of protein biology, to ensure that they truly grasp the fundamentals.<\/p>\n \u201cWe\u2019re making everything up from scratch,\u201d says Baker. \u201cAnd that\u2019s a very strict rule in the lab: you\u2019re not allowed to start with anything that exists in nature, because we wanted to be able to be sure we understand everything and design everything from first principles.\u201d<\/p>\n For the most part, these artificial proteins have been what Baker calls \u201crocks\u201d \u2014 ultra-stable proteins, such as Top7, of defined shape that other researchers can build on. Over the past few years, however, scientists have grown ever more skilled at imparting function, creating everything from fluorescent and cell-signalling proteins to candidate vaccines. But they\u2019re in the minority in the design community \u2014 Baker estimates that 95\u201399% of protein engineering \u201cis still done by random mutation and selection\u201d. And\u00a0de novo<\/i>\u00a0protein engineering often requires weeks of computational time and months of iteration. Still, computational advances and a broadening user base is making the process more accessible.<\/p>\n \u201cIt\u2019s a tremendous time to be in this area,\u201d says Donald Hilvert, a protein chemist at the Swiss Federal Institute of Technology (ETH) Zurich, who has worked with Kuhlman to create enzymes called esterases. \u201cThe combination of computation, structure, molecular biology, detailed biophysical measurements \u2014 all of this is coming together in such a beautiful way.\u201d<\/p>\n <\/p>\n It\u2019s complicated<\/strong><\/p>\n Protein folding is complicated. Built as long chains of amino acids, newly formed proteins quickly collapse into a specific folded shape, from which the molecules derive their function. Researchers have long known that a protein\u2019s sequence defines its shape. And they can experimentally determine that shape using X-ray crystallography and cryo-electron microscopy. What they could not do was predict the shape from the sequence alone.<\/p>\n That\u2019s because a protein\u2019s structure is defined by multiple competing forces. A protein is basically a long string of carbon, nitrogen, oxygen and hydrogen, with amino-acid side chains dangling like charms on a molecular bracelet. The molecule cannot fold into just any shape, however \u2014 the possibilities are constrained as different parts of the protein jostle for position and balance attractive and repulsive forces. The trick in protein-folding prediction is to work out those forces, and thus the precise angles that the protein bonds will take.<\/p>\n <\/p>\n Cassie Bryan at the University of Washington built a protein that binds to the cell-surface protein PD-1.<\/span>Credit: Brian DalBalcon<\/p>\n<\/figcaption><\/figure>\n <\/p>\n <\/p>\n The Baker lab uses a suite of molecular modelling and search tools called Rosetta, which can calculate the energy of a folded protein and search for the lowest energy sequence for a given structure, or the lowest energy structure for a given sequence. Baker developed Rosetta in the late 1990s as a tool for predicting structure. The software has been under continuous development ever since, both by members of his lab and a community of several hundred users called the Rosetta Commons, to improve its performance and capabilities.<\/p>\n For instance, in a project to design short circular peptides called macrocycles \u2014 which can have antibiotic and anticancer properties \u2014 Baker lab postdocs Parisa Hosseinzadeh, Gaurav Bhardwaj and Vikram Mulligan (who is now at the Simons Foundation in New York City) collaborated2<\/a><\/sup>\u00a0to teach Rosetta how to handle \u2018d\u2019 amino acids. These are chemical mirror images of the \u2018l\u2019 residues used by cells, and therefore have different properties. Protein designer Neil King, a Baker lab alumnus who is still at the University of Washington, has modified Rosetta to design self-assembling protein nanoparticles.<\/p>\n Although each\u00a0de novo<\/i>\u00a0project in his lab is different, Baker says that they all follow the same basic strategy. First, decide on a desired class of structures \u2014 a \u2018Platonic ideal\u2019 of a shape, as he puts it. Then, use Rosetta to design tens of thousands of potential backbone conformations to match that shape, flesh those out with side-chain residues, and test that the calculated sequences will fold into the desired form. Finally, synthesize genes that will express the best designs, test, iterate and repeat.<\/p>\n \u201cOnly a very small fraction of possible backbone conformations are actually designable,\u201d Baker says. And researchers might need to search through millions of possibilities and dozens of physical proteins before selecting the right candidate. Zibo Chen, a graduate from the Baker lab who is now at the California Institute of Technology in Pasadena, sifted through some 87 million backbones to identify 2,251 designs that are capable of protein\u2013protein interaction. The computation took about six weeks on several hundred processor cores.<\/p>\n Inspired by DNA origami – in which DNA molecules are folded into nanostructures – Chen wanted to identify hydrogen-bonding strategies that would allow him to design perfectly orthogonal protein pairs (proteins that would interact only with a specified artificial partner, but not with other similarly designed proteins). Such proteins could be used to create novel biosensors, genetic circuits or just whimsical shapes. Chen joined the lab, he says, partly because he wanted to see whether he could recreate with protein what DNA nanotechnologists had made with nucleic acids: a macromolecular smiley face emoji. Earlier this year, Chen described the first step towards such a design: a self-assembling 2D array3<\/a><\/sup>. \u201cI was quite naive about what I could achieve in five years,\u201d he says.<\/p>\n Bryan designed her protein \u2014 all 46 amino acids of it, tiny by protein standards \u2014 to interface with, and hopefully regulate, PD-1. The protein, she says, is simply a flat surface \u2014 a \u03b2-sheet \u2014 scaffolded by a single, rod-like \u03b1-helix. In cartoon form, it resembles an old-fashioned iron used to press clothes. \u201cThe helix is kind of like a handle, and the actual functional end is the iron that sticks to the receptor,\u201d she explains.<\/p>\n Bryan first tried to modify an existing protein to assume that shape, but found she couldn\u2019t produce the protein in a usable form. So, inspired by the known structure of PD-1 binding to its natural ligand PD-L2, she identified three crucial residues, coded their positions into Rosetta and directed the software to build a protein that would support it. She extended an essential loop by five amino acids to improve binding to the human target. And using a high-throughput screening strategy based on flow cytometry (a cell-analysis technique) and DNA sequencing, she tested every amino-acid variant at every position to nudge the structure towards ever-stronger interactions. On the way to designing her protein, Bryan received her degree, despite a three-year detour when she realized that her engineered protein couldn\u2019t interact with its human counterpart owing to some crucial sugar modifications.<\/p>\n Finally, Bryan had a breakthrough: the protein bound to lymphocytes in a flow cytometer. With so many ups and downs, Bryan was sceptical of reading too much into any one experiment, she says. But those flow data, provided by her immunology colleagues, made her believe. \u201cIt was these immunology collaborators who know T cells really well, and they\u2019re telling me that on real human T cells from real people, we saw this strong effect that hadn\u2019t really been seen before with similar molecules.\u201d<\/p>\n King, who has designed a self-assembling nanoparticle that could serve as a candidate vaccine for respiratory syncytial virus4<\/a><\/sup>, describes shepherding a molecule from concept to reality as surreal. \u201cYou\u2019re making it up,\u201d he says. \u201cIt\u2019s literally a computer fantasy. And when it actually works in the real world, it\u2019s just magical.\u201d<\/p>\n And so Bryan celebrated, as she says, with beers and Joan Jett.<\/p>\n <\/p>\n Designing for function<\/strong><\/p>\n At this point, there\u2019s little that protein engineers cannot do, Baker says \u2014 at least in terms of shape. But most proteins don\u2019t exist simply to assume a specific shape; it\u2019s function that matters.<\/p>\n Function, such as the ability to catalyse a chemical reaction, complicates design, says Hosseinzadeh, because it adds new variables to the problem. \u201cWhen I pick for shape, the only thing I care about is the overall energy,\u201d she says. \u201cBut when you design for function, there are certain other things that come into consideration \u2014 for example, does this molecule make good contacts with the protein surface that I want to target? Are the targeting side chains positioned in the correct place? And does it cover the [interaction] surface?\u201d<\/p>\n When Anastassia Vorobieva, a postdoc in Baker\u2019s lab and Jiayi Dou, who is now at Stanford University in California, decided to create a\u00a0de novo<\/i>analogue of green fluorescent protein, the two researchers came to the project with different agendas. Vorobieva wanted to create a \u03b2-barrel, a common structural motif that had yet to be created from scratch; Dou wanted to build a protein that could stabilize a small molecule, such as a fluorophore.<\/p>\n A \u03b2-barrel is a structure in which one edge of a \u03b2-sheet connects with the other, creating a hollow pore or pocket. But they are particularly tricky to create, Vorobieva says, because the individual threads of the sheet are sticky; if the protein isn\u2019t designed just so, it will degrade into a useless mess.<\/p>\n Vorobieva\u2019s aim was to create a barrel with a smoothly curving surface. But that design placed an unexpected strain on the peptide backbone. A few well-placed glycine residues imparted a squarish cross section, but relieved the stress enough for the design to succeed. Vorobieva showed this with a crystal structure that closely matched her concept5<\/a><\/sup>. That \u201cwas the final strongest experiment that showed we were doing everything right\u201d, she says.<\/p>\n To make the protein functional, Dou reproduced Vorobieva\u2019s original design, but with additional constraints to stabilize a fluorescent molecule. She worked with Baker lab research scientist Will Sheffler, who was designing a new Rosetta module to sample the possible binding conformations of a small molecule bound to a protein. Dou balanced stability and function by deliberately restricting the fluorophore to the top of the barrel. Dou identified 2,102 candidate designs, and synthesized 56. Two fluoresced in the presence of the fluorescent substrate, one of which Dou further modified to maximize brightness and validate her design \u2014 an effort that involved testing some 2,090 gene variants.<\/p>\n <\/p>\n A 3D model of a protein. The sequence of amino acids in a protein defines its shape.<\/span>Credit: Ian Hayden\/Institute for Protein Design<\/p>\n<\/figcaption><\/figure>\n <\/p>\n <\/p>\n Protein design almost always involves selection and iteration, notes Lynne Regan, a protein chemist at the University of Edinburgh, UK. Researchers cannot yet sit down at a computer and design a protein that binds another molecule and get it right first time; they have to make something that works to some degree, and then improve on it.<\/p>\n In part, that\u2019s because researchers are still working out the minutiae of protein folding. Baker notes, for instance, that Rosetta depends on its \u2018energy function\u2019, a model that estimates the energy associated with each structure. But just because the program says a molecule will assume a particular shape doesn\u2019t mean it actually will. Sharon Guffy, a protein scientist at biotechnology company Pairwise in Durham, North Carolina, who did her graduate work with Kuhlman, says she struggled to get Rosetta to correctly account for the electrical properties of zinc (and its impact on nearby side chains) when creating a metal-binding protein. \u201cIt cost me at least a month or so\u201d of coding and troubleshooting, she says.<\/p>\n At the University of California, San Francisco, Marco Mravic, a graduate student in the laboratory of protein engineer William DeGrado, focuses his research on membrane proteins \u2014 specifically, their assembly into larger complexes. He chose to study a cardiac protein called phospholamban, which comprises five identical membrane-spanning helices. What is it, Mravic wanted to know, that directs these helices to assemble so precisely?<\/p>\n Part of the problem was structural. Nobody actually knew what phospholamban looked like. Mravic ran a molecular-dynamics simulation of the protein, which suggested the complex splays open at one end like a banana peel. \u201cIt was like, this simulation doesn\u2019t look right,\u201d Mravic says. \u201cSo I just went into the molecule and \u2018fixed\u2019 it.\u201d<\/p>\n By changing two water-loving amino acids to more membrane-favourable residues, Mravic created a more tightly packed variant, which he demonstrated by solving the crystal structure. He then worked out the features that allowed that packing to occur, identifying what he calls a \u201csteric code\u201d \u2014 a configuration of four amino acids on the helix surface that allow key side chains to interlace like a zip. Mravic then used that code to design synthetic derivatives that adopt structures analogous to phospholamban6<\/a><\/sup>.<\/p>\n <\/p>\n Structural foundations<\/strong><\/p>\n Beyond the nuances of protein folding,\u00a0de novo<\/i>\u00a0design allows researchers to push the boundaries of what proteins can do. At the University of Birmingham, UK, for instance, chemist Anna Peacock studies metallopeptides \u2014 miniature proteins that bind metal ions. In biology, such molecules typically bind zinc, manganese or copper \u2014 \u201cthings that are found dissolved in seawater\u201d, she says. But other metals could enable different chemistry.<\/p>\n Peacock has used\u00a0de novo<\/i>\u00a0proteins as scaffolds to create molecules capable of binding gadolinium, complexes of which are commonly used as contrast agents for magnetic resonance imaging. She is also crafting enzymes that can use metals such as platinum or iridium to explore reactions not found in nature. \u201cI don\u2019t personally see the point in getting an artificial metalloprotein to do the same chemistry that an enzyme can already do,\u201d she says.<\/p>\n As each design goal is achieved, it becomes easier for others to emulate them. The Baker lab has even developed an online gaming interface to Rosetta, called FoldIt, that challenges players (few of whom are scientists) to create proteins\u00a0in silico<\/i>. In a study this year analysing their work7<\/a><\/sup>, the players delivered. They built novel designs \u201ccompletely from scratch\u201d, Baker says, including one fold that had never been seen before.<\/p>\n Few scientists have the time or expertise to design a protein from the ground up, of course; for them,\u00a0de novo<\/i>\u00a0designs are foundations to build upon. But in the Baker lab, the design work continues. With each success, the lab celebrates. For the postdocs and students who do the work, Baker says, the euphoria \u201clasts for quite a long time. For me, it lasts for a day or two, and then it wears off and I\u2019m like, okay, what are we gonna do next?\u201d<\/p>\n <\/p>\n <\/p>\n<\/div>\n Nature<\/span>\u00a0571<\/strong>, 585-587 (2019)<\/p>\n <\/p>\n <\/p>\n <\/p>\n (\uc6d0\ubb38: \uc5ec\uae30<\/a>\ub97c \ud074\ub9ad\ud558\uc138\uc694~)<\/p>\n <\/p>\n <\/p>\n <\/p>\n","protected":false},"excerpt":{"rendered":"![\"Cassie](\"\/\/media.nature.com\/w800\/magazine-assets\/d41586-019-02251-x\/d41586-019-02251-x_16920426.jpg\")
<\/div>\n<\/div>![\"A](\"\/\/media.nature.com\/w800\/magazine-assets\/d41586-019-02251-x\/d41586-019-02251-x_16920428.jpg\")
<\/div>\n<\/div>