If accurate, such an estimator could computationally demonstrate binding affinity and thus prevent experimental researchers from needing to investigate millions of chemical compounds. The work could substantially reduce the cost and time associated with developing new drugs.

“We developed a theoretical framework for estimating ligand-protein binding,” said Mahmoud Moradi, associate professor of chemistry and biochemistry in the Fulbright College of Arts and Sciences. “The proposed method assigns an effective energy to the ligand at every grid point in a coordinate system, which has its origin at the most likely location of the ligand when it is in its bound state.”

A ligand is a substance — an ion or molecule — such as a drug that binds to another molecule, such as a protein, to form a complex system that may cause or prevent a biological function.

Moradi’s research focuses on computational simulations of diseases, including coronavirus. For this project, he collaborated with Suresh Thallapuranam, professor of biochemistry and the Cooper Chair of Bioinformatics Research.

Moradi and Thallapuranam used biased simulations — as well as non-parametric re-weighting techniques to account for the bias — to create a binding estimator that was computationally efficient and accurate. They then used a mathematically robust technique called orientation quaternion formalism to further describe the ligand’s conformational changes as it bound to targeted proteins.

The researchers tested this approach by estimating the binding affinity between human fibroblast growth factor 1 — a specific signaling protein — and heparin hexasaccharide 5, a popular medication.

The project was conceived because Moradi and Thallapuranam were studying human fibroblast growth factor 1 protein and its mutants in the absence and presence of heparin. They found strong qualitative agreement between simulations and experimental results.

“When it came to binding affinity, we knew that the typical methods we had at our disposal would not work for such a difficult problem,” Moradi said. “This is why we decided to develop a new method. We had a joyous moment when the experimental and computational data were compared with each other, and the two numbers matched almost perfectly.”

The researchers’ work was published in Nature Computational Science.

Moradi previously received attention for developing computational simulations of the behavior of SARS-CoV-2 spike proteins prior to fusion with human cell receptors. SARS-CoV-2 is the virus that causes COVID-19.

Like all living organisms, pathogens want to thrive. Aside from cellular reproduction, though, the best future for them lies in moving from host to host. Think of each host as Stevenson’s eggs, unwittingly waiting to be, if not broken, certainly cracked. Meaning ill. That’s why pathogens — from conjunctivitis, commonly known as pink eye, or a common cold or a disease as severe as COVID-19 — make their hosts sick: Spread is sometimes only made possible by expulsion via swollen red eyes; ,coughing or sneezing, or passing through bodily fluids, according to Virginia Tech biologist Dana Hawley.

“For a pathogen, ‘spreading’ is their key form of reproduction. And when we think about why pathogens make their hosts sick, it’s long been a mystery, because making a host sick or making your host die is superficially not a good way for a pathogen to be able to spread. A very sick host will stay home and not interact as much as others, which means less spread potential for a pathogen,” said Hawley, a professor in the Department of Biological Sciences, part of the Virginia Tech College of Science.

But here’s the caveat: “Making your hosts feel ill can be important for getting some of the copies of yourself out of the host you are infecting and into another. So there is a trade-off for the pathogen,” Hawley said. “Making your host feel sick means that host may not interact with as many other hosts as they normally would — this is bad for the pathogen — but when they do have interactions, a very sick host that is coughing or has swollen eyes is going to be much more likely to spread whatever pathogen it has in its body. This isgoodfor the pathogen.”

Using songbirds, a type known as finches, whose populations are affected by a pink-eye disease in nature, Hawley and a team of researchers from Virginia Tech and the University of Memphis in Tennessee have shown just how easily these pathogens — in this case, a form of conjunctivitis common in birds, but harmless to humans — spread. And they did it without having the pink eye pathogen itself spread from bird to bird.

Instead, the team used UV fluorescent powder coatings and tracked thatand not the pathogen. During the experiment, birds were divided up into three groups: not ill, mildly ill, and strongly ill, all with conjunctivitis, and each bird was housed with four healthy flockmates. By applying a powder coating around the outer eye of each bird, but not inside the eye, the researchers could track how much powder was spread to flockmates from birds that were strongly, mildly, or not ill with pink eye.

“We weren’t actually tracing the spread of conjunctivitis. We were tracing the spread of powder as a model for the likely spread of conjunctivitis,” said Hawley, who is also an affiliated member of the Virginia Tech Fralin Life Sciences Institute’s Global Change Center and its Center for Emerging, Zoonotic, and Arthropod-borne Pathogens, about the study, published today in the journal Royal Society Open Science.

During the study, birds were kept in large-flight cages, sharing feeders and potentially spreading powder to cage mates. Feeder surfaces are one main avenue of the powder’s travel, according to the study.

There were some surprises along the way, Hawley said. The finches experiencing the strongest conjunctivitis symptoms were far less likely to eat but nonetheless spread the powder at a higher rate than the mildly ill birds who spent more time feeding.

“In our study system, the benefits of making your host sicker by increasing eye swelling outweighed the cost of making the finches feed and interact less,” Hawley said. “So overall, this pathogen is going to likely evolve to causemore harm to birds in nature so that it can spread at a higher rate, but up to some limit, because if the pathogen kills a bird immediately, the pathogen doesn’t have a chance to spread at all.”

The human factor

What does all this mean for humans and the spread of a common cold or COVID-19 at a doctor’s office or the cinema, or the spread of conjunctivitis amongst young children at a nursery school or day care?

The mantra of “stay home if you’re sick” still applies more than ever, according to Hawley. This study suggests that symptoms will make the spread of anything you are infected with much more likely. And wear a face mask — and not just for potential spread of COVID. “Wearing masks when you are coughing from any illness can likely go a long way in preventing disease spread,” Hawley said. “For pink eye, keeping kids isolated is going to be key because young children are just not going to be able to wash their hands or avoid touching each other — speaking from experience as a parent.”

Evolution plays another part. Again, pathogens are living organisms and prone to the rules of life, including evolution. “This goes back to the idea that everyone hoped that COVID would evolve to become milder over time,” Hawley said. “Our study shows that the pressures on pathogens are complicated. On the one hand, being mild is good for pathogens if it keeps your host out and about and in others’ company — good for spread, but on the other hand, being mild may mean that none of the pathogen makes it out of the host and into another because your host isn’t coughing or depositing as much pathogen onto hands or other surfaces. So pathogens are in many cases going to be favored to make us sick.”

In other words, for humans, common sense actions can prevent us from being those proverbial eggs spoken of by Stevenson.

Co-authors on the paper include Courtney A. Thomason, a former postdoctoral associate at Virginia Tech from January 2015 to October 2017, who is now at the Tennessee Department of Environment and Conservation; Matt Aberle, who earned a master’s degree in biological sciences in 2018 and is now a wildlife biologist with Oregon Department of Forestry; and Richard Brown, who graduated with a bachelor’s degree in wildlife conservation from the Virginia Tech College of Natural Resources and Environment in 2017 and is now a master’s student at George Mason University; as well as James S. Adelman, an assistant professor at the University of Memphis.

Funding for the study came from two National Science Foundation grants and additional funding from the National Institute of General Medical Sciences, the latter part of the National Institutes for Health.

On Jan. 11 at the 241st meeting of the American Astronomical Society in Seattle, a team led by scientists at the University of Washington and the Center for Computational Astrophysics will unveil results using the Panchromatic Hubble Andromeda Treasury Triangulum Extended Region — or PHATTER — survey. The endeavor is giving astrophysicists their first in-depth look at the distinct populations of stars that make up the Triangulum galaxy.

Researchers discovered that this satellite galaxy, a close companion of the much larger Andromeda galaxy, has two drastically different structures depending on the age of the stars.

“The youngest stars and the oldest stars in the Triangulum galaxy — which we can separate out using multiple wavelength filters on the Hubble Space Telescope — are organized very differently,” said Adam Smercina, a postdoctoral researcher at the UW. “This is surprising. For a lot of galaxies, like the Milky Way and Andromeda, the stars are distributed roughly consistently, regardless of their age. That is not the case with Triangulum.”

At about 61,000 light years across, Triangulum is the third-largest galaxy in our local group, after Andromeda and our own Milky Way. In lower-resolution images it has a “flocculent” structure — with many small spiral arms radiating out from a well-defined center.

For the PHATTER survey, the Hubble Space Telescope obtained hundreds of high-resolution images of different sections of the Triangulum galaxy in 108 orbits over the course of more than a year. The team tiled these smaller-section images together to create a comprehensive, high-resolution dataset for Triangulum that for the first time showed the galaxy’s individual stars over a large region in its center.

Thanks to Hubble’s array of filters, researchers could also separate those stars by age. The distribution of younger, massive stars — those less than 1 billion years in age — were roughly in line with the “flocculent” pattern, for which the Triangulum is so renowned. But its older, redder stars are distributed in a very different pattern: two spiral arms radiating out from a rectangular bar at the galaxy’s center.

“This was a largely unknown and hidden feature of the Triangulum galaxy that was very difficult to see without this kind of detailed survey,” said Smercina.

Old stars make up the majority of Triangulum’s mass, but are dimmer than their younger counterparts, according to Smercina. That could explain why the “flocculent” pattern prevails in low-resolution images of the galaxy.

The survey team also does not know why young and old stars have such divergent distributions in Triangulum. Satellite galaxies in general are an eclectic bunch, and many questions remain about their formation and evolution. Satellite galaxies come in many different shapes and can be molded by interactions with their parent galaxies. The Milky Way’s largest satellite galaxy, the Large Magellanic Cloud, for example, is similar in size and mass to Triangulum, but has an irregular and globular shape due to its proximity to our own galaxy.

The PHATTER survey’s on-going analysis should shed light on how these types of galaxies form and interact with their larger neighbors. The team plans to follow up on these initial findings by tracing the history of star formation in Triangulum, comparing different sections of the galaxy.

“A major goal of the PHATTER survey was to generate the kind of detailed, high-resolution data on this prominent satellite galaxy that will allow us to examine its structure in depth, trace its history of star formation and compare what we see to theories of galaxy formation and evolution,” said Smercina. “We’re already finding surprises.”

Other team members include Julianne Dalcanton, director of the Center for Computational Astrophysics in New York, a UW professor of astronomy and principal investigator of the PHATTER project; UW research associate professor of astronomy Benjamin Williams; UW doctoral student Meredith Durbin; and Margaret Lazzarini, a postdoctoral researcher at Caltech.

It can be hard to remember, or for some to even imagine, what life was like before most of us carried around a dynamic mapping platform in our back pocket. Being able to quickly map out the most efficient route by car, bike, or foot has become second nature. What if the same principle of having an easily accessible and easy-to-use tool could be applied to mapping energy infrastructure?

The Geospatial Energy Mapper (GEM) is a comprehensive, interactive online mapping tool that can help identify areas across the country that are suitable for wind, solar and more. First publicly launched in 2013 as the Energy Zones Mapping Tool (EZMT), GEM has been redesigned, rebranded and reengineered. GEM is hosted by the U.S. Department of Energy’s (DOE) Argonne National Laboratory with funding from the DOE’s Office of Electricity.

“In GEM we applied lessons learned from almost 10 years hosting the EZMT, including making it easier to learn and use, updating the software architecture, and choosing a name fitting its current scope of uses,” said Jim Kuiper, principal geospatial engineer and GEM technical coordinator.

GEM offers an extensive catalog of mapping data. This includes energy resources and infrastructure, and other information that might influence energy infrastructure siting decisions. With over 190 different mapping layers — including demographics, boundaries and utilities — users can locate areas for clean power generation, electric vehicle charging stations and more.

One of the new features is mapping themes, which allow the map to be rapidly set up for a particular focus, like solar, wind or electric vehicles. This new feature helps users quickly load multiple layers related to a particular technology or resource without having to manually browse the mapping catalog and add individual layers to the map.

With GEMs modeling capabilities, users can generate a customized suitability map or “heat map.” This map shows which geographical areas in the United States are favorable for the development of certain energy resources and infrastructures. GEM includes preconfigured models for over 40 types of energy infrastructure. Land-based wind turbines or utility-scale photovoltaic solar are two examples. This provides a convenient starting point that users can then easily customize.

“Choosing where to build utility-scale renewable energy development is a tremendously important decision with effects that reverberate beyond the generation of electricity,” said Michael Levin, a GEM user and Ph.D. student studying renewable energy landscapes at Columbia University. ?”GEM not only makes energy suitability maps public but allows for the user to customize the model used to produce such a map.”

GEM has nearly 100 modeling criteria to choose from. Population density, proximity to nearest substation, slope, wildfire risk and low-income household percentage are just a few examples. Nine types of energy resources can be analyzed for clean energy resource development. They include biomass, coal (with carbon capture and sequestration), geothermal, natural gas, nuclear, solar, storage, water and wind.

GEM is expected to have a diverse community of users much like the EZMT. The tool has been used by planners and regulators at all levels of government. For instance, Kentucky’s Office of Energy Policy used the EZMT for prototyping their Solar Site Suitability on Reclaimed Mine Lands tool. Other users include private industry, public service commissions and regional transmission organizations. Finally, national laboratories, educational institutions, energy and natural resource non-profit organizations, and private individuals have all been EZMT users.

Story Source:

Materials provided by DOE/Argonne National Laboratory. Original written by Marguerite Huber. Note: Content may be edited for style and length.

The two stars are so close that it takes them less than one Earth day to revolve around each other. In other words, each star’s “year” lasts just 20.5 hours.

The newly discovered system, named LP 413-53AB, is composed of a pair of ultracool dwarfs, a class of very low-mass stars that are so cool that they emit their light primarily in the infrared, making them completely invisible to the human eye. They are nonetheless one of the most common types of stars in the universe.

Previously, astronomers had only detected three short-period ultracool dwarf binary systems, all of which are relatively young — up to 40 million years old. LP 413-53AB is estimated to be billions of years old — similar age to our sun — but has an orbital period that is at least three times shorter than the all ultracool dwarf binaries discovered so far.

“It’s exciting to discover such an extreme system,” said Chih-Chun “Dino” Hsu, a Northwestern astrophysicist who led the study. “In principle, we knew these systems should exist, but no such systems had been identified yet.”

Hsu will present this research during a press briefing at the 241st Meeting of the American Astronomical Society in Seattle. “Discovery of the shortest-period ultracool dwarf binary” will take place at 2:15 p.m. PST on Tuesday, Jan. 10, as part of a session on “Stars and Their Activity.”

Hsu is a postdoctoral researcher in physics and astronomy at Northwestern’s Weinberg College of Arts and Sciences and a member of Northwestern’s Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA). He began this study while a Ph.D. student at UC San Diego, where he was advised by Professor Adam Burgasser.

The team first discovered the strange binary system while exploring archival data. Hsu developed an algorithm that can model a star based on its spectral data. By analyzing the spectrum of light emitted from a star, astrophysicists can determine the star’s chemical composition, temperature, gravity and rotation. This analysis also shows the star’s motion as it moves toward and away from the observer, known as radial velocity.

When examining the spectral data of LP 413-53AB, Hsu noticed something strange. Early observations caught the system when the stars were roughly aligned and their spectral lines overlapped, leading Hsu to believe it was just one star. But as the stars moved in their orbit, the spectral lines shifted in opposite directions, splitting into pairs in later spectral data. Hsu realized there were actually two stars locked into an incredibly tight binary.

Using powerful telescopes at the W.M. Keck Observatory, Hsu decided to observe the phenomenon for himself. On March 13, 2022, the team turned the telescopes toward the constellation Taurus, where the binary system is located, and observed it for two hours. Then, they followed up with more observations in July, October and December.

“When we were making this measurement, we could see things changing over a couple of minutes of observation,” Burgasser said. “Most binaries we follow have orbit periods of years. So, you get a measurement every few months. Then, after a while, you can piece together the puzzle. With this system, we could see the spectral lines moving apart in real time. It’s amazing to see something happen in the universe on a human time scale.”

The observations confirmed what Hsu’s model predicted. The distance between the two stars is about 1% of the distance between the Earth and the sun. “This is remarkable, because when they were young, something like 1 million years old, these stars would have been on top of each other,” said Burgasser.

The team speculates that the stars either migrated toward each other as they evolved, or they could have come together after the ejection of a third — now lost — stellar member. More observations are needed to test these ideas.

Hsu also said that by studying similar star systems researchers can learn more about potentially habitable planets beyond Earth. Ultracool dwarfs are much fainter and dimmer than the sun, so any worlds with liquid water on their surfaces — a crucial ingredient to form and sustain life — would need to be much closer to the star. However, for LP 413-53AB, the habitable zone distance happens to be the same as the stellar orbit, making it impossible to form habitable planets in this system.

“These ultracool dwarfs are neighbors of our sun,” Hsu said. “To identify potentially habitable hosts, it’s helpful to start with our nearby neighbors. But if close binaries are common among ultracool dwarfs, there may be few habitable worlds to be found.”

To fully explore these scenarios, Hsu, Burgasser and their collaborators hope to pinpoint more ultracool dwarf binary systems to create a full data sample. New observational data could help strengthen theoretical models for binary-star formation and evolution. Until now, however, finding ultracool binary stars has remained a rare feat.

“These systems are rare,” said Chris Theissen, study co-author and a Chancellor’s Postdoctoral Fellow at UC San Diego. “But we don’t know whether they are rare because they rarely exist or because we just don’t find them. That’s an open-ended question. Now we have one data point that we can start building on. This data had been sitting in the archive for a long time. Dino’s tool will enable us to look for more binaries like this.”