cryo-EM
3D Animation Captures Viral Infection in Action
Posted on by Lawrence Tabak, D.D.S., Ph.D.
With the summer holiday season now in full swing, the blog will also swing into its annual August series. For most of the month, I will share with you just a small sampling of the colorful videos and snapshots of life captured in a select few of the hundreds of NIH-supported research labs around the country.
To get us started, let’s turn to the study of viruses. Researchers now can generate vast amounts of data relatively quickly on a virus of interest. But data are often displayed as numbers or two-dimensional digital images on a computer screen. For most virologists, it’s extremely helpful to see a virus and its data streaming in three dimensions. To do so, they turn to a technological tool that we all know so well: animation.
This research animation features the chikungunya virus, a sometimes debilitating, mosquito-borne pathogen transmitted mainly in developing countries in Africa, Asia and the Americas. The animation illustrates large amounts of research data to show how the chikungunya virus infects our cells and uses its specialized machinery to release its genetic material into the cell and seed future infections. Let’s take a look.
In the opening seconds, you see how receptor binding glycoproteins (light blue), which are proteins with a carbohydrate attached on the viral surface, dock with protein receptors (yellow) on a host cell. At five seconds, the virus is drawn inside the cell. The change in the color of the chikungunya particle shows that it’s coated in a vesicle, which helps the virus make its way unhindered through the cytoplasm.
At 10 seconds, the virus then enters an endosome, ubiquitous bubble-like compartments that transport material from outside the cell into the cytosol, the fluid part of the cytoplasm. Once inside the endosome, the acidic environment makes other glycoproteins (red, blue, yellow) on the viral surface change shape and become more flexible and dynamic. These glycoproteins serve as machinery that enables them to reach out and grab onto the surrounding endosome membrane, which ultimately will be fused with the virus’s own membrane.
As more of those fusion glycoproteins grab on, fold back on themselves, and form into hairpin-like shapes, they pull the membranes together. The animation illustrates not only the changes in protein organization, but the resulting effects on the integrity of the membrane structures as this dynamic process proceeds. At 53 seconds, the viral protein shell, or capsid (green), which contains the virus’ genetic instructions, is released back out into the cell where it will ultimately go on to make more virus.
This remarkable animation comes from Margot Riggi and Janet Iwasa, experts in visualizing biology at the University of Utah’s Animation Lab, Salt Lake City. Their data source was researcher Kelly Lee, University of Washington, Seattle, who collaborated closely with Riggi and Iwasa on this project. The final product was considered so outstanding that it took the top prize for short videos in the 2022 BioArt Awards competition, sponsored by the Federation of American Societies for Experimental Biology (FASEB).
The Lee lab uses various research methods to understand the specific shape-shifting changes that chikungunya and other viruses perform as they invade and infect cells. One of the lab’s key visual tools is cryo-electron microscopy (Cryo-EM), specifically cryo-electron tomography (cryo-ET). Cryto-ET enables complex 3D structures, including the intermediate state of biological reactions, to be captured and imaged in remarkably fine detail.
In a study in the journal Nature Communications [1] last year, Lee’s team used cryo-ET to reveal how the chikungunya virus invades and delivers its genetic cargo into human cells to initiate a new infection. While Lee’s cryo-ET data revealed stages of the virus entry process and fine structural details of changes to the virus as it enters a cell and starts an infection, it still represented a series of snapshots with missing steps in between. So, Lee’s lab teamed up with The Animation Lab to help beautifully fill in the gaps.
Visualizing chikungunya and similar viruses in action not only makes for informative animations, it helps researchers discover better potential targets to intervene in this process. This basic research continues to make progress, and so do ongoing efforts to develop a chikungunya vaccine [2] and specific treatments that would help give millions of people relief from the aches, pains, and rashes associated with this still-untreatable infection.
References:
[1] Visualization of conformational changes and membrane remodeling leading to genome delivery by viral class-II fusion machinery. Mangala Prasad V, Blijleven JS, Smit JM, Lee KK. Nat Commun. 2022 Aug 15;13(1):4772. doi: 10.1038/s41467-022-32431-9. PMID: 35970990; PMCID: PMC9378758.
[2] Experimental chikungunya vaccine is safe and well-tolerated in early trial, National Institute of Allergy and Infectious Diseases news release, April 27, 2020.
Links:
Chikungunya Virus (Centers for Disease Control and Prevention, Atlanta)
Global Arbovirus Initiative (World Health Organization, Geneva, Switzerland)
The Animation Lab (University of Utah, Salt Lake City)
Video: Janet Iwasa (TED Speaker)
Lee Lab (University of Washington, Seattle)
BioArt Awards (Federation of American Societies for Experimental Biology, Rockville, MD)
NIH Support: National Institute of General Medical Sciences; National Institute of Allergy and Infectious Diseases
Cryo-EM Scores Again
Posted on by Lawrence Tabak, D.D.S., Ph.D.
Human neurons are long, spindly structures, but if you could zoom in on their surfaces at super-high resolution, you’d see surprisingly large pores. They act as gated channels that open and close for ions and other essential molecules of life to pass in and out the cell. This rapid exchange of ions and other molecules is how neurons communicate, and why we humans can sense, think, move, and respond to the world around us [1].
Because these gated channels are so essential to neurons, mapping their precise physical structures at high-resolution has profound implications for informing future studies on the brain and nervous system. Good for us in these high-tech times that structural biologists keep getting better at imaging these 3D pores.
In fact, as just published in the journal Nature Communications [2], a team of NIH-supported scientists imaged the molecular structure of a gated pore of major research interest. The pore is called calcium homeostasis modulator 1 (CALHM1). Pictured below, you can view its 3D structure at near atomic resolution [2]. Keep in mind, this relatively large neuronal pore still measures approximately 50,000 times smaller than the width of a hair.
The structure comes from a research team led by Hiro Furukawa, Cold Spring Harbor Laboratory, Cold Spring Harbor, NY. He and his team relied on cryo-electron microscopy (cryo-EM) to produce the first highly precise 3D models of CALHM1.
Cryo-EM involves flash-freezing molecules in liquid ethane and bombarding them with electrons to capture their images with a special camera. When all goes well, cryo-EM can reveal the structure of intricate macromolecular complexes in a matter of weeks.
Furukawa’s team had earlier studied CALHM1 from chickens with cryo-EM [3], and their latest work reveals that the human version is quite similar. Eight copies of the CALHM1 protein assemble to form the circular channel. Each of the protein subunits has a flexible arm that allows it to reach into the central opening, which the researchers now suspect allows the channels to open and close in a highly controlled manner. The researchers have likened the channels’ eight flexible arms to the arms of an octopus.
The researchers also found that fatty molecules called phospholipids play a critical role in stabilizing and regulating the eight-part channel. They used simulations to demonstrate how pockets in the CALHM1 channel binds this phospholipid over cholesterol to shore up the structure and function properly. Interestingly, these phospholipid molecules are abundant in many healthy foods, such as eggs, lean meats, and seafood.
Researchers knew that an inorganic chemical called ruthenium red can block the function of the CALHM1 channel. They’ve now shown precisely how this works. The structural details indicate that ruthenium red physically lodges in and plugs up the channel.
These details also may be useful in future efforts to develop drugs designed to target and modify the function of these channels in helpful ways. For instance, on our tongues, the channel plays a role in our ability to perceive sweet, sour, or umami (savory) flavors. In our brains, studies show the abnormal function of CALHM1 may be implicated in the plaques that accumulate in the brains of people with Alzheimer’s disease.
There are far too many other normal and abnormal functions to mention here in this brief post. Suffice it to say, I’ll look forward to seeing what this enabling research yields in the years ahead.
References:
[1] On the molecular nature of large-pore channels. Syrjanen, J., Michalski, K., Kawate, T., and Furukawa, H. J Mol Biol. 2021 Aug 20;433(17):166994. DOI: 10.1016/j.jmb.2021.166994. Epub 2021 Apr 16. PMID: 33865869; PMCID: PMC8409005.
[2] Structure of human CALHM1 reveals key locations for channel regulation and blockade by ruthenium red. Syrjänen JL, Epstein M, Gómez R, Furukawa H. Nat Commun. 2023 Jun 28;14(1):3821. DOI: 10.1038/s41467-023-39388-3. PMID: 37380652; PMCID: PMC10307800.
[3] Structure and assembly of calcium homeostasis modulator proteins. Syrjanen JL, Michalski K, Chou TH, Grant T, Rao S, Simorowski N, Tucker SJ, Grigorieff N, Furukawa H. Nat Struct Mol Biol. 2020 Feb;27(2):150-159. DOI: 10.1038/s41594-019-0369-9. Epub 2020 Jan 27. PMID: 31988524; PMCID: PMC7015811.
Links:
Brain Basics: The Life and Death of a Neuron (National Institute of Neurological Disorders and Stroke/NIH)
Alzheimer’s Disease (National Institute on Aging/NIH)
Furukawa Lab (Cold Spring Harbor Lab, Cold Spring Harbor, NY)
NIH Support: National Institute of Neurological Disorders and Stroke; National Institute of Mental Health
Artificial Intelligence Accurately Predicts Protein Folding
Posted on by Dr. Francis Collins
Proteins are the workhorses of the cell. Mapping the precise shapes of the most important of these workhorses helps to unlock their life-supporting functions or, in the case of disease, potential for dysfunction. While the amino acid sequence of a protein provides the basis for its 3D structure, deducing the atom-by-atom map from principles of quantum mechanics has been beyond the ability of computer programs—until now.
In a recent study in the journal Science, researchers reported they have developed artificial intelligence approaches for predicting the three-dimensional structure of proteins in record time, based solely on their one-dimensional amino acid sequences [1]. This groundbreaking approach will not only aid researchers in the lab, but guide drug developers in coming up with safer and more effective ways to treat and prevent disease.
This new NIH-supported advance is now freely available to scientists around the world. In fact, it has already helped to solve especially challenging protein structures in cases where experimental data were lacking and other modeling methods hadn’t been enough to get a final answer. It also can now provide key structural information about proteins for which more time-consuming and costly imaging data are not yet available.
The new work comes from a group led by David Baker and Minkyung Baek, University of Washington, Seattle, Institute for Protein Design. Over the course of the pandemic, Baker’s team has been working hard to design promising COVID-19 therapeutics. They’ve also been working to design proteins that might offer promising new ways to treat cancer and other conditions. As part of this effort, they’ve developed new computational approaches for determining precisely how a chain of amino acids, which are the building blocks of proteins, will fold up in space to form a finished protein.
But the ability to predict a protein’s precise structure or shape from its sequence alone had proven to be a difficult problem to solve despite decades of effort. In search of a solution, research teams from around the world have come together every two years since 1994 at the Critical Assessment of Structure Prediction (CASP) meetings. At these gatherings, teams compete against each other with the goal of developing computational methods and software capable of predicting any of nature’s 200 million or more protein structures from sequences alone with the greatest accuracy.
Last year, a London-based company called DeepMind shook up the structural biology world with their entry into CASP called AlphaFold. (AlphaFold was one of Science’s 2020 Breakthroughs of the Year.) They showed that their artificial intelligence approach—which took advantage of the 170,000 proteins with known structures in a reiterative process called deep learning—could predict protein structure with amazing accuracy. In fact, it could predict most protein structures almost as accurately as other high-resolution protein mapping techniques, including today’s go-to strategies of X-ray crystallography and cryo-EM.
The DeepMind performance showed what was possible, but because the advances were made by a world-leading deep learning company, the details on how it worked weren’t made publicly available at the time. The findings left Baker, Baek, and others eager to learn more and to see if they could replicate the impressive predictive ability of AlphaFold outside of such a well-resourced company.
In the new work, Baker and Baek’s team has made stunning progress—using only a fraction of the computational processing power and time required by AlphaFold. The new software, called RoseTTAFold, also relies on a deep learning approach. In deep learning, computers look for patterns in large collections of data. As they begin to recognize complex relationships, some connections in the network are strengthened while others are weakened. The finished network is typically composed of multiple information-processing layers, which operate on the data to return a result—in this case, a protein structure.
Given the complexity of the problem, instead of using a single neural network, RoseTTAFold relies on three. The three-track neural network integrates and simultaneously processes one-dimensional protein sequence information, two-dimensional information about the distance between amino acids, and three-dimensional atomic structure all at once. Information from these separate tracks flows back and forth to generate accurate models of proteins rapidly from sequence information alone, including structures in complex with other proteins.
As soon as the researchers had what they thought was a reasonable working approach to solve protein structures, they began sharing it with their structural biologist colleagues. In many cases, it became immediately clear that RoseTTAFold worked remarkably well. What’s more, it has been put to work to solve challenging structural biology problems that had vexed scientists for many years with earlier methods.
RoseTTAFold already has solved hundreds of new protein structures, many of which represent poorly understood human proteins. The 3D rendering of a complex showing a human protein called interleukin-12 in complex with its receptor (above image) is just one example. The researchers have generated other structures directly relevant to human health, including some that are related to lipid metabolism, inflammatory conditions, and cancer. The program is now available on the web and has been downloaded by dozens of research teams around the world.
Cryo-EM and other experimental mapping methods will remain essential to solve protein structures in the lab. But with the artificial intelligence advances demonstrated by RoseTTAFold and AlphaFold, which has now also been released in an open-source version and reported in the journal Nature [2], researchers now can make the critical protein structure predictions at their desktops. This newfound ability will be a boon to basic science studies and has great potential to speed life-saving therapeutic advances.
References:
[1] Accurate prediction of protein structures and interactions using a three-track neural network. Baek M, DiMaio F, Anishchenko I, Dauparas J, Grishin NV, Adams PD, Read RJ, Baker D., et al. Science. 2021 Jul 15:eabj8754.
[2] Highly accurate protein structure prediction with AlphaFold. Jumper J, Evans R, Pritzel A, Green T, Senior AW, Kavukcuoglu K, Kohli P, Hassabis D. et al. Nature. 2021 Jul 15.
Links:
Structural Biology (National Institute of General Medical Sciences/NIH)
The Structures of Life (NIGMS)
Baker Lab (University of Washington, Seattle)
CASP 14 (University of California, Davis)
NIH Support: National Institute of Allergy and Infectious Diseases; National Institute of General Medical Sciences
What A Year It Was for Science Advances!
Posted on by Dr. Francis Collins
At the close of every year, editors and writers at the journal Science review the progress that’s been made in all fields of science—from anthropology to zoology—to select the biggest advance of the past 12 months. In most cases, this Breakthrough of the Year is as tough to predict as the Oscar for Best Picture. Not in 2020. In a year filled with a multitude of challenges posed by the emergence of the deadly coronavirus disease 2019 (COVID-2019), the breakthrough was the development of the first vaccines to protect against this pandemic that’s already claimed the lives of more than 360,000 Americans.
In keeping with its annual tradition, Science also selected nine runner-up breakthroughs. This impressive list includes at least three areas that involved efforts supported by NIH: therapeutic applications of gene editing, basic research understanding HIV, and scientists speaking up for diversity. Here’s a quick rundown of all the pioneering advances in biomedical research, both NIH and non-NIH funded:
Shots of Hope. A lot of things happened in 2020 that were unprecedented. At the top of the list was the rapid development of COVID-19 vaccines. Public and private researchers accomplished in 10 months what normally takes about 8 years to produce two vaccines for public use, with more on the way in 2021. In my more than 25 years at NIH, I’ve never encountered such a willingness among researchers to set aside their other concerns and gather around the same table to get the job done fast, safely, and efficiently for the world.
It’s also pretty amazing that the first two conditionally approved vaccines from Pfizer and Moderna were found to be more than 90 percent effective at protecting people from infection with SARS-CoV-2, the coronavirus that causes COVID-19. Both are innovative messenger RNA (mRNA) vaccines, a new approach to vaccination.
For this type of vaccine, the centerpiece is a small, non-infectious snippet of mRNA that encodes the instructions to make the spike protein that crowns the outer surface of SARS-CoV-2. When the mRNA is injected into a shoulder muscle, cells there will follow the encoded instructions and temporarily make copies of this signature viral protein. As the immune system detects these copies, it spurs the production of antibodies and helps the body remember how to fend off SARS-CoV-2 should the real thing be encountered.
It also can’t be understated that both mRNA vaccines—one developed by Pfizer and the other by Moderna in conjunction with NIH’s National Institute of Allergy and Infectious Diseases—were rigorously evaluated in clinical trials. Detailed data were posted online and discussed in all-day meetings of an FDA Advisory Committee, open to the public. In fact, given the high stakes, the level of review probably was more scientifically rigorous than ever.
First CRISPR Cures: One of the most promising areas of research now underway involves gene editing. These tools, still relatively new, hold the potential to fix gene misspellings—and potentially cure—a wide range of genetic diseases that were once to be out of reach. Much of the research focus has centered on CRISPR/Cas9. This highly precise gene-editing system relies on guide RNA molecules to direct a scissor-like Cas9 enzyme to just the right spot in the genome to cut out or correct a disease-causing misspelling.
In late 2020, a team of researchers in the United States and Europe succeeded for the first time in using CRISPR to treat 10 people with sickle cell disease and transfusion-dependent beta thalassemia. As published in the New England Journal of Medicine, several months after this non-heritable treatment, all patients no longer needed frequent blood transfusions and are living pain free [1].
The researchers tested a one-time treatment in which they removed bone marrow from each patient, modified the blood-forming hematopoietic stem cells outside the body using CRISPR, and then reinfused them into the body. To prepare for receiving the corrected cells, patients were given toxic bone marrow ablation therapy, in order to make room for the corrected cells. The result: the modified stem cells were reprogrammed to switch back to making ample amounts of a healthy form of hemoglobin that their bodies produced in the womb. While the treatment is still risky, complex, and prohibitively expensive, this work is an impressive start for more breakthroughs to come using gene editing technologies. NIH, including its Somatic Cell Genome Editing program, continues to push the technology to accelerate progress and make gene editing cures for many disorders simpler and less toxic.
Scientists Speak Up for Diversity: The year 2020 will be remembered not only for COVID-19, but also for the very public and inescapable evidence of the persistence of racial discrimination in the United States. Triggered by the killing of George Floyd and other similar events, Americans were forced to come to grips with the fact that our society does not provide equal opportunity and justice for all. And that applies to the scientific community as well.
Science thrives in safe, diverse, and inclusive research environments. It suffers when racism and bigotry find a home to stifle diversity—and community for all—in the sciences. For the nation’s leading science institutions, there is a place and a calling to encourage diversity in the scientific workplace and provide the resources to let it flourish to everyone’s benefit.
For those of us at NIH, last year’s peaceful protests and hashtags were noticed and taken to heart. That’s one of the many reasons why we will continue to strengthen our commitment to building a culturally diverse, inclusive workplace. For example, we have established the NIH Equity Committee. It allows for the systematic tracking and evaluation of diversity and inclusion metrics for the intramural research program for each NIH institute and center. There is also the recently founded Distinguished Scholars Program, which aims to increase the diversity of tenure track investigators at NIH. Recently, NIH also announced that it will provide support to institutions to recruit diverse groups or “cohorts” of early-stage research faculty and prepare them to thrive as NIH-funded researchers.
AI Disentangles Protein Folding: Proteins, which are the workhorses of the cell, are made up of long, interconnected strings of amino acids that fold into a wide variety of 3D shapes. Understanding the precise shape of a protein facilitates efforts to figure out its function, its potential role in a disease, and even how to target it with therapies. To gain such understanding, researchers often try to predict a protein’s precise 3D chemical structure using basic principles of physics—including quantum mechanics. But while nature does this in real time zillions of times a day, computational approaches have not been able to do this—until now.
Of the roughly 170,000 proteins mapped so far, most have had their structures deciphered using powerful imaging techniques such as x-ray crystallography and cryo–electron microscopy (cryo-EM). But researchers estimate that there are at least 200 million proteins in nature, and, as amazing as these imaging techniques are, they are laborious, and it can take many months or years to solve 3D structure of a single protein. So, a breakthrough certainly was needed!
In 2020, researchers with the company Deep Mind, London, developed an artificial intelligence (AI) program that rapidly predicts most protein structures as accurately as x-ray crystallography and cryo-EM can map them [2]. The AI program, called AlphaFold, predicts a protein’s structure by computationally modeling the amino acid interactions that govern its 3D shape.
Getting there wasn’t easy. While a complete de novo calculation of protein structure still seemed out of reach, investigators reasoned that they could kick start the modeling if known structures were provided as a training set to the AI program. Utilizing a computer network built around 128 machine learning processors, the AlphaFold system was created by first focusing on the 170,000 proteins with known structures in a reiterative process called deep learning. The process, which is inspired by the way neural networks in the human brain process information, enables computers to look for patterns in large collections of data. In this case, AlphaFold learned to predict the underlying physical structure of a protein within a matter of days. This breakthrough has the potential to accelerate the fields of structural biology and protein research, fueling progress throughout the sciences.
How Elite Controllers Keep HIV at Bay: The term “elite controller” might make some people think of video game whizzes. But here, it refers to the less than 1 percent of people living with human immunodeficiency virus (HIV) who’ve somehow stayed healthy for years without taking antiretroviral drugs. In 2020, a team of NIH-supported researchers figured out why this is so.
In a study of 64 elite controllers, published in the journal Nature, the team discovered a link between their good health and where the virus has inserted itself in their genomes [3]. When a cell transcribes a gene where HIV has settled, this so-called “provirus,” can produce more virus to infect other cells. But if it settles in a part of a chromosome that rarely gets transcribed, sometimes called a gene desert, the provirus is stuck with no way to replicate. Although this discovery won’t cure HIV/AIDS, it points to a new direction for developing better treatment strategies.
In closing, 2020 presented more than its share of personal and social challenges. Among those challenges was a flood of misinformation about COVID-19 that confused and divided many communities and even families. That’s why the editors and writers at Science singled out “a second pandemic of misinformation” as its Breakdown of the Year. This divisiveness should concern all of us greatly, as COVID-19 cases continue to soar around the country and our healthcare gets stretched to the breaking point. I hope and pray that we will all find a way to come together, both in science and in society, as we move forward in 2021.
References:
[1] CRISPR-Cas9 gene editing for sickle cell disease and β-thalassemia. Frangoul H et al. N Engl J Med. 2020 Dec 5.
[2] ‘The game has changed.’ AI triumphs at protein folding. Service RF. Science. 04 Dec 2020.
[3] Distinct viral reservoirs in individuals with spontaneous control of HIV-1. Jiang C et al. Nature. 2020 Sep;585(7824):261-267.
Links:
COVID-19 Research (NIH)
2020 Science Breakthrough of the Year (American Association for the Advancement of Science, Washington, D.C)
Caught on Camera: Neutralizing Antibodies Interacting with SARS-CoV-2
Posted on by Dr. Francis Collins
As this long year enters its final month, there is good reason to look ahead to 2021 with optimism that the COVID-19 pandemic will finally be contained. The Food and Drug Administration is now reviewing the clinical trial data of the Pfizer and Moderna vaccines to ensure their safety and efficacy. If all goes well, emergency use authorization could come very soon, allowing immunizations to begin.
Work also continues on developing better therapeutics against SARS-CoV-2, the novel coronavirus that causes COVID-19. Though we’ve learned a great deal about this coronavirus in a short time, structural biologists continue to produce more detailed images that reveal more precisely where and how to target SARS-CoV-2. This research often involves neutralizing antibodies that circulate in the blood of most people who’ve recovered from COVID-19. The study of such antibodies and how they interact with SARS-CoV-2 offers critical biological clues into how to treat and prevent COVID-19.
A recent study in the journal Nature brings more progress, providing the most in-depth analysis yet of how human neutralizing antibodies physically grip SARS-CoV-2 to block it from binding to our cells [1]. To conduct this analysis, a team of NIH-supported structural biologists, led by postdoc Christopher Barnes and Pamela Björkman, California Institute of Technology, Pasadena, used the power of cryo-electron microscopy (cryo-EM) to capture complex molecular interactions at near-atomic scale.
People infected with SARS-CoV-2 (or any foreign substance, for that matter) generate thousands of different versions of attack antibodies. Some of these antibodies are very good at sticking to the coronavirus, while others attach only loosely. Barnes used cryo-EM to capture highly intricate pictures of eight different human neutralizing antibodies bound tightly to SARS-CoV-2. Each of these antibodies, which had been isolated from patients a few weeks after they developed symptoms of COVID-19, had been shown in lab tests to be highly effective at blocking infection.
The researchers mapped all physical interactions between several human neutralizing antibodies and SARS-CoV-2’s spike protein that stud its surface. The virus uses these spiky extensions to infect a human cell by grabbing on to the angiotensin-converting enzyme 2 (ACE2) receptor. The molecular encounter between the coronavirus and ACE2 takes place via one or more of a trio of three protein domains, called receptor-binding domains (RBDs), that jut out from its spikes. RBDs flap up and down in the fluid surrounding cells, “reaching up” to touch and enter, or “laying down” to hide from an infected person’s antibodies and immune cells. Only an “up” RBD can attach to ACE2 and get into a cell.
Taken together with other structural information known about SARS-CoV-2, Barnes’ cryo-EM snapshots revealed four different types of shapes, or classes, of antibody-spike combinations. These high-resolution molecular views show that human neutralizing antibodies interact in many different ways with SARS-CoV-2: blocking access to either one or more RBDs in their “up” or “down” positions.
These results tell us a number of things, including underscoring why strategies that combine multiple types of antibodies in an “antibody cocktail” might likely offer broader protection against infection than using just a single type of antibody. Indeed, that approach is currently being tested in patients with COVID-19.
The findings also provide a molecular guide for custom-designing synthetic antibodies in the lab to foil SARS-CoV-2. As one example, Barnes and his team observed that one antibody completely locked all three RBDs into closed (“down”) positions. As you might imagine, scientists might want to copy that antibody type when designing an antibody-based drug or vaccine.
It is tragic that hundreds of thousands of people have died from this terrible new disease. Yet the immune system helps most to recover. Learning as much as we possibly can from those individuals who’ve been infected and returned to health should help us understand how to heal others who develop COVID-19, as well as inform precision design of additional vaccines that are molecularly targeted to this new foe.
While we look forward to the arrival of COVID-19 vaccines and their broad distribution in 2021, each of us needs to remember to practice the three W’s: Wear a mask. Watch your distance (stay 6 feet apart). Wash your hands often. In parallel with everyone adopting these critical public health measures, the scientific community is working harder than ever to meet this moment, doing everything possible to develop safe and effective ways of treating and preventing COVID-19.
Reference:
[1] SARS-CoV-2 neutralizing antibody structures inform therapeutic strategies. Barnes CO, Jette CA, Abernathy ME, et al. Nature. 2020 Oct 12. [Epub ahead of print].
Links:
Coronavirus (COVID-19) (NIH)
Combat COVID (U.S. Department of Health and Human Services, Washington, D.C.)
Freezing a Moment in Time: Snapshots of Cryo-EM Research (National Institute of General Medical Sciences/NIH)
Björkman Lab (California Institute of Technology, Pasadena)
NIH Support: National Institute of General Medical Sciences; National Institute of Allergy and Infectious Diseases
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