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DeepMind AI solves 50-year-old biology problem in breakthrough advance
The Google-owned company developed a system that can reliably predict the 3D shapes of proteins.

- Scientists have long been puzzled by how specific chains of amino acids go on to form three-dimensional proteins.
- DeepMind developed a system that's able to predict "protein folding" in a fraction of the time of human experiments, and with unprecedented accuracy.
- The achievement could greatly improve drug research and development, as well as bioengineering pursuits.
In 1994, a group of scientists created a competition to solve one of the most perplexing problems in biology: how do proteins fold themselves into 3D shapes, which then carry out fundamental processes within living organisms?
The answer to this 50-year-old question could revolutionize many scientific pursuits, from accelerating and improving drug development, to creating better biofuels. But the competition, called Critical Assessment of Protein Structure Prediction (CASP), went decades without a solution.
Then artificial intelligence got into the mix.
DeepMind, a U.K.-based AI company, essentially solved the long-standing problem in the most recent competition, CASP14. The company outperformed the other teams by magnitudes, predicting the shapes of proteins with accuracy rates never before achieved by humans.
"This is a big deal," John Moult, a computational biologist who co-founded CASP, told Nature. "In some sense the problem is solved."
Credit: DeepMind
In the biennial competition, teams analyze around 100 proteins with the goal of predicting their eventual 3D shape. A protein's shape determines its function. For example, a protein can become an antibody that binds to foreign particles to protect, an enzyme that carries out chemical reactions, or a structural component that supports cells.
Proteins start as a string of hundreds of amino acids. Within a protein, pairs of amino acids can interact in numerous ways, and these particular interactions determine the final shape of the protein. But given the sheer number of possible interactions, it's incredibly difficult to predict a protein's physical shape. Difficult, but not impossible.
Since CASP began, scientists have been able to predict the shape of some simple proteins with reasonable accuracy. CASP is able to verify the accuracy of these predictions by comparing them to the actual shape of proteins, which it obtains through the unpublished results of lab experiments.
But these experiments are difficult, often taking months or years of hard work. The shapes of some proteins have eluded scientists for decades. As such, it's hard to overstate the value of having an AI that's able to churn out this work in just hours, or even minutes.
In 2018, DeepMind, which was acquired by Google in 2014, startled the scientific community when its AlphaFold algorithm won the CASP13 contest. AlphaFold was able to predict protein shapes by "training" itself on vast amounts of data on known amino acid strings and their corresponding protein shapes.
In other words, AlphaFold learned that particular amino acid configurations—say, distances between pairs, angles between chemical bonds—signaled that the protein would likely take a particular shape. AlphaFold then used these insights to predict the shapes of unmapped proteins. AlphaFold's performance in the 2018 contest was impressive, but not reliable enough to consider the problem of "protein folding" solved.
Credit: DeepMind
In the latest contest, DeepMind used an updated version of AlphaFold. It combines the previous deep-learning strategy with a new "attention algorithm" that accounts for physical and geometric factors. Here's how DeepMind describes it:
"A folded protein can be thought of as a 'spatial graph,' where residues are the nodes and edges connect the residues in close proximity. This graph is important for understanding the physical interactions within proteins, as well as their evolutionary history."
"For the latest version of AlphaFold, used at CASP14, we created an attention-based neural network system, trained end-to-end, that attempts to interpret the structure of this graph, while reasoning over the implicit graph that it's building. It uses evolutionarily related sequences, multiple sequence alignment (MSA), and a representation of amino acid residue pairs to refine this graph."
CASP measures prediction accuracy through the "Global Distance Test (GDT)", which ranges from 0-100. The new version of AlphaFold scored a median of 92.4 GDT for all targets.
Given that the specific ways in which proteins take shape can shed light on how diseases form, AlphaFold could greatly accelerate disease research and drug development. And while it's too late for the system to help with COVID-19, DeepMind says that protein structure prediction could be "useful in future pandemic response efforts."
Still, scientists have much to learn about predicting protein structures, and while AlphaFold has proven faster and more accurate than human experiments, the system isn't 100 percent accurate. But DeepMind's achievement signals that AI may become a surprisingly powerful tool in unlocking key mysteries in biology and beyond.
"For all of us working on computational and machine learning methods in science, systems like AlphaFold demonstrate the stunning potential for AI as a tool to aid fundamental discovery," DeepMind wrote. "Just as 50 years ago Anfinsen laid out a challenge far beyond science's reach at the time, there are many aspects of our universe that remain unknown. The progress announced today gives us further confidence that AI will become one of humanity's most useful tools in expanding the frontiers of scientific knowledge, and we're looking forward to the many years of hard work and discovery ahead!"
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‘Designer baby’ book trilogy explores the moral dilemmas humans may soon create
How would the ability to genetically customize children change society? Sci-fi author Eugene Clark explores the future on our horizon in Volume I of the "Genetic Pressure" series.
- A new sci-fi book series called "Genetic Pressure" explores the scientific and moral implications of a world with a burgeoning designer baby industry.
- It's currently illegal to implant genetically edited human embryos in most nations, but designer babies may someday become widespread.
- While gene-editing technology could help humans eliminate genetic diseases, some in the scientific community fear it may also usher in a new era of eugenics.
Tribalism and discrimination
<p>One question the "Genetic Pressure" series explores: What would tribalism and discrimination look like in a world with designer babies? As designer babies grow up, they could be noticeably different from other people, potentially being smarter, more attractive and healthier. This could breed resentment between the groups—as it does in the series.</p><p>"[Designer babies] slowly find that 'everyone else,' and even their own parents, becomes less and less tolerable," author Eugene Clark told Big Think. "Meanwhile, everyone else slowly feels threatened by the designer babies."</p><p>For example, one character in the series who was born a designer baby faces discrimination and harassment from "normal people"—they call her "soulless" and say she was "made in a factory," a "consumer product." </p><p>Would such divisions emerge in the real world? The answer may depend on who's able to afford designer baby services. If it's only the ultra-wealthy, then it's easy to imagine how being a designer baby could be seen by society as a kind of hyper-privilege, which designer babies would have to reckon with. </p><p>Even if people from all socioeconomic backgrounds can someday afford designer babies, people born designer babies may struggle with tough existential questions: Can they ever take full credit for things they achieve, or were they born with an unfair advantage? To what extent should they spend their lives helping the less fortunate? </p>Sexuality dilemmas
<p>Sexuality presents another set of thorny questions. If a designer baby industry someday allows people to optimize humans for attractiveness, designer babies could grow up to find themselves surrounded by ultra-attractive people. That may not sound like a big problem.</p><p>But consider that, if designer babies someday become the standard way to have children, there'd necessarily be a years-long gap in which only some people are having designer babies. Meanwhile, the rest of society would be having children the old-fashioned way. So, in terms of attractiveness, society could see increasingly apparent disparities in physical appearances between the two groups. "Normal people" could begin to seem increasingly ugly.</p><p>But ultra-attractive people who were born designer babies could face problems, too. One could be the loss of body image. </p><p>When designer babies grow up in the "Genetic Pressure" series, men look like all the other men, and women look like all the other women. This homogeneity of physical appearance occurs because parents of designer babies start following trends, all choosing similar traits for their children: tall, athletic build, olive skin, etc. </p><p>Sure, facial traits remain relatively unique, but everyone's more or less equally attractive. And this causes strange changes to sexual preferences.</p><p>"In a society of sexual equals, they start looking for other differentiators," he said, noting that violet-colored eyes become a rare trait that genetically engineered humans find especially attractive in the series.</p><p>But what about sexual relationships between genetically engineered humans and "normal" people? In the "Genetic Pressure" series, many "normal" people want to have kids with (or at least have sex with) genetically engineered humans. But a minority of engineered humans oppose breeding with "normal" people, and this leads to an ideology that considers engineered humans to be racially supreme. </p>Regulating designer babies
<p>On a policy level, there are many open questions about how governments might legislate a world with designer babies. But it's not totally new territory, considering the West's dark history of eugenics experiments.</p><p>In the 20th century, the U.S. conducted multiple eugenics programs, including immigration restrictions based on genetic inferiority and forced sterilizations. In 1927, for example, the Supreme Court ruled that forcibly sterilizing the mentally handicapped didn't violate the Constitution. Supreme Court Justice Oliver Wendall Holmes wrote, "… three generations of imbeciles are enough." </p><p>After the Holocaust, eugenics programs became increasingly taboo and regulated in the U.S. (though some states continued forced sterilizations <a href="https://www.uvm.edu/~lkaelber/eugenics/" target="_blank">into the 1970s</a>). In recent years, some policymakers and scientists have expressed concerns about how gene-editing technologies could reanimate the eugenics nightmares of the 20th century. </p><p>Currently, the U.S. doesn't explicitly ban human germline genetic editing on the federal level, but a combination of laws effectively render it <a href="https://academic.oup.com/jlb/advance-article/doi/10.1093/jlb/lsaa006/5841599#204481018" target="_blank" rel="noopener noreferrer">illegal to implant a genetically modified embryo</a>. Part of the reason is that scientists still aren't sure of the unintended consequences of new gene-editing technologies. </p><p>But there are also concerns that these technologies could usher in a new era of eugenics. After all, the function of a designer baby industry, like the one in the "Genetic Pressure" series, wouldn't necessarily be limited to eliminating genetic diseases; it could also work to increase the occurrence of "desirable" traits. </p><p>If the industry did that, it'd effectively signal that the <em>opposites of those traits are undesirable. </em>As the International Bioethics Committee <a href="https://academic.oup.com/jlb/advance-article/doi/10.1093/jlb/lsaa006/5841599#204481018" target="_blank" rel="noopener noreferrer">wrote</a>, this would "jeopardize the inherent and therefore equal dignity of all human beings and renew eugenics, disguised as the fulfillment of the wish for a better, improved life."</p><p><em>"Genetic Pressure Volume I: Baby Steps"</em><em> by Eugene Clark is <a href="http://bigth.ink/38VhJn3" target="_blank">available now.</a></em></p>Designer uses AI to bring 54 Roman emperors to life
It's hard to stop looking back and forth between these faces and the busts they came from.
Meet Emperors Augustus, left, and Maximinus Thrax, right
- A quarantine project gone wild produces the possibly realistic faces of ancient Roman rulers.
- A designer worked with a machine learning app to produce the images.
- It's impossible to know if they're accurate, but they sure look plausible.
How the Roman emperors got faced
<a href="https://payload.cargocollective.com/1/6/201108/14127595/2K-ENGLISH-24x36-Educational_v8_WATERMARKED_2000.jpg" ><img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNDQ2NDk2MS9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTYyOTUzMzIxMX0.OwHMrgKu4pzu0eCsmOUjybdkTcSlJpL_uWDCF2djRfc/img.jpg?width=980" id="775ca" class="rm-shortcode" data-rm-shortcode-id="436000b6976931b8320313478c624c82" data-rm-shortcode-name="rebelmouse-image" alt="lineup of emperor faces" data-width="1440" data-height="963" /></a>Credit: Daniel Voshart
<p>Voshart's imaginings began with an AI/neural-net program called <a href="https://www.artbreeder.com" target="_blank">Artbreeder</a>. The freemium online app intelligently generates new images from existing ones and can combine multiple images into…well, who knows. It's addictive — people have so far used it to generate nearly 72.7 million images, says the site — and it's easy to see how Voshart fell down the rabbit hole.</p><p>The Roman emperor project began with Voshart feeding Artbreeder images of 800 busts. Obviously, not all busts have weathered the centuries equally. Voshart told <a href="https://www.livescience.com/ai-roman-emperor-portraits.html" target="_blank" rel="noopener noreferrer">Live Science</a>, "There is a rule of thumb in computer programming called 'garbage in garbage out,' and it applies to Artbreeder. A well-lit, well-sculpted bust with little damage and standard face features is going to be quite easy to get a result." Fortunately, there were multiple busts for some of the emperors, and different angles of busts captured in different photographs.</p><p>For the renderings Artbreeder produced, each face required some 15-16 hours of additional input from Voshart, who was left to deduce/guess such details as hair and skin coloring, though in many cases, an individual's features suggested likely pigmentations. Voshart was also aided by written descriptions of some of the rulers.</p><p>There's no way to know for sure how frequently Voshart's guesses hit their marks. It is obviously the case, though, that his interpretations look incredibly plausible when you compare one of his emperors to the sculpture(s) from which it was derived.</p><p>For an in-depth description of Voshart's process, check out his posts on <a href="https://medium.com/@voshart/photoreal-roman-emperor-project-236be7f06c8f" target="_blank">Medium</a> or on his <a href="https://voshart.com/ROMAN-EMPEROR-PROJECT" target="_blank" rel="noopener noreferrer">website</a>.</p><p>It's fascinating to feel like you're face-to-face with these ancient and sometimes notorious figures. Here are two examples, along with some of what we think we know about the men behind the faces.</p>Caligula
<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNDQ2NDk4Mi9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTY3MzQ1NTE5NX0.LiTmhPQlygl9Fa9lxay8PFPCSqShv4ELxbBRFkOW_qM/img.jpg?width=980" id="7bae0" class="rm-shortcode" data-rm-shortcode-id="ce795c554490fe0a36a8714b86f55b16" data-rm-shortcode-name="rebelmouse-image" data-width="992" data-height="558" />One of numerous sculptures of Caligula, left
Credit: Rogers Fund, 1914/Wikimedia Commons/Daniel Voshart
<p><span style="background-color: initial;"><a href="https://en.wikipedia.org/wiki/Caligula" target="_blank">Caligula</a></span> was the third Roman Emperor, ruling the city-state from AD 37 to 41. His name was actually Gaius Caesar Augustus Germanicus — Caligula is a nickname meaning "Little Boot."</p><p>One of the reputed great madmen of history, he was said to have made a horse his consul, had conversations with the moon, and to have ravaged his way through his kingdom, including his three sisters. Caligula is known for extreme cruelty, terrorizing his subjects, and accounts suggest he would deliberately distort his face to surprise and frighten people he wished to intimidate.</p><p>It's <a href="https://www.history.com/news/7-things-you-may-not-know-about-caligula" target="_blank">not totally clear</a> if Caligula was as over-the-top as history paints him, but that hasn't stopped Hollywood from churning out some <a href="https://www.imdb.com/title/tt0080491/" target="_blank" rel="noopener noreferrer">howlers</a> in his name.</p><p>A 1928 journal, <a href="https://www.jstor.org/stable/4172009" target="_blank">Studies in Philology</a>, noted that contemporary descriptions of Caligula depicted him as having a "head misshapen, eyes and temples sunken," and "eyes staring and with a glare savage enough to torture." In some sculptures not shown above, his head <em>is</em> a bit acorn-shaped. </p>Nero
<img type="lazy-image" data-runner-src="https://assets.rebelmouse.io/eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpbWFnZSI6Imh0dHBzOi8vYXNzZXRzLnJibC5tcy8yNDQ2NTAwMC9vcmlnaW4uanBnIiwiZXhwaXJlc19hdCI6MTY1NTQ2ODU0NX0.AgYuQZzRQCanqehSI5UeakpxU8fwLagMc_POH7xB3-M/img.jpg?width=980" id="a8825" class="rm-shortcode" data-rm-shortcode-id="9e0593d79c591c97af4bd70f3423885e" data-rm-shortcode-name="rebelmouse-image" data-width="992" data-height="558" />One of numerous sculptures of Nero, left
Credit: Bibi_Saint-Pol/Wikimedia Commons/Daniel Voshart
<p>There's a good German word for the face of <a href="https://en.wikipedia.org/wiki/Nero" target="_blank" rel="noopener noreferrer">Nero</a>, that guy famous for fiddling as Rome burned. It's "<a href="https://www.urbandictionary.com/define.php?term=Backpfeifengesicht" target="_blank">backpfeifengesicht</a>." Properly named Nero Claudius Caesar Augustus Germanicus, he was Rome's fifth emperor. He ruled from AD 54 until his suicide in AD 68.</p><p>Another Germanicus-family gem, Nero's said to have murdered his own mother, Agrippa, as well as (maybe) his second wife. As for the fiddling, he <em>was</em> a lover of music and the arts, and there are stories of his charitability. And, oh yeah, he may have set the fire as an excuse to rebuild the city center, making it his own.</p><p>While it may not be the most historically sound means of assessing an historical personage, Voshart's imagining of Nero does suggest an over-indulged, entitled young man. Backpfeifengesicht.</p>Archaeologists identify contents of ancient Mayan drug containers
Scientists use new methods to discover what's inside drug containers used by ancient Mayan people.
A Muna-type paneled flask with distinctive serrated-edge decoration from AD 750-900.
- Archaeologists used new methods to identify contents of Mayan drug containers.
- They were able to discover a non-tobacco plant that was mixed in by the smoking Mayans.
- The approach promises to open up new frontiers in the knowledge of substances ancient people consumed.
PARME staff archaeologists excavating a burial site at the Tamanache site, Mérida, Yucatan.
Credit: WSU
Ten “keys to reality” from a Nobel-winning physicist
To understand ourselves and our place in the universe, "we should have humility but also self-respect," Frank Wilczek writes in a new book.
This is your brain on political arguments
Debating is cognitively taxing but also important for the health of a democracy—provided it's face-to-face.
