The sensor detects and quantifies any traces of carbendazim, a fungicide in widespread use in Brazil despite being banned. Credit: José Luiz Bott Neto
Researchers at the University of São Paulo (USP) in Brazil have developed a kraft paper-based electrochemical sensor that can detect traces of pesticides in fruit and vegetables in real time when coupled to an electronic device. In an apple or cabbage, for example, it can detect carbendazim, a fungicide widely used in Brazil despite being banned.
The results are reported in an article published in the journal Food Chemistry.
“To find out whether a food sample contains traces of pesticides by conventional methods, you must grind up the sample and submit it to time-consuming chemical processes before any such substances can be detected. Wearable sensors like the one we developed for continuous monitoring of pesticides in agriculture and the food industry eliminate the need for these complex processes. Inspection is much easier, cheaper and reliable for a supermarket, restaurant or importer, for example,” said Osvaldo Novais de Oliveira Junior, penultimate author of the article and a professor at IFSC-USP.
The new device is highly sensitive and resembles the glucometers used by diabetics to measure blood sugar, except that the results of food scanning for pesticides are displayed on a smartphone. “In the tests we performed, its sensitivity was similar to the conventional method’s. Plus, it’s fast and inexpensive,” said José Luiz Bott Neto, corresponding author of the article and a postdoctoral fellow at IFSC-USP.
How it works
The device consists basically of a paper substrate modified with carbon ink and submitted to electrochemical treatment in an acid medium to activate carboxyl groups and make detection possible, Bott Neto explained.
“We use the silkscreen process to transfer carbon-conducting ink to a strip of kraft paper, thereby creating a device based on electrochemistry. It has three carbon electrodes and is immersed in an acidic solution to activate the carboxyl groups. In other words, oxygen atoms are added to the structure of the carbon electrode. When it comes into contact with a sample contaminated with carbendazim, the sensor induces an electrochemical oxidation reaction that permits detection of the fungicide. The quantity of carbendazim is measured via electrical current,” he said.
In developing the device, the researchers evaluated the stability and structure of the paper substrate. “The properties of the paper itself were an important part of our research,” said Thiago Serafim Martins, first author of the article and a postdoctoral fellow at IFSC-USP.
Best option
The researchers analyzed kraft paper and parchment, finding both types of paper to be stable enough to serve as a substrate for the sensor. However, the porousness of kraft paper conferred more sensitivity on the sensor and the carboxyl groups formed during electrochemical activation, Martins explained, adding that paper-based electrodes could be used in many applications.
“There are commercial electrodes made of plastic or ceramic material. We successfully developed electrochemical sensors based on paper, a much more malleable material and therefore potentially useful in many areas, not just on farms or in supermarkets, but also in healthcare, for example,” he said.
More information: Thiago S. Martins et al, Optimized paper-based electrochemical sensors treated in acidic media to detect carbendazim on the skin of apple and cabbage, Food Chemistry (2023). DOI: 10.1016/j.foodchem.2023.135429
Revealing the pattern between frontal polymerization and natural convection. Credit: The Grainger College of Engineering at University of Illinois Urbana-Champaign
A self-propagating chemical reaction can transform a liquid monomer into a solid polymer, and the interaction between the propagating front and the reaction’s natural convection leads to patterns in the resulting solid polymeric material. New University of Illinois Urbana-Champaign work has shown how the coupling between natural convection and frontal polymerization leads to those observed patterns.
This research was led by a unique team of researchers: Materials Science and Engineering professor Nancy Sottos, Aerospace Engineering professor Philippe Geubelle, and Mechanical Science and Engineering professor Leonardo Chamorro. A paper describing this research was recently published in Physical Review Letters.
Thermoset polymers and composite materials are used in a wide range of industries, but producing such materials requires their being cured at high temperatures in a slow and highly energy intensive process. Frontal polymerization to cure the materials is an attractive alternative approach that is significantly faster and more energy efficient.
In frontal polymerization, a self-propagating chemical front converts a liquid monomer into a solid polymer through a reaction that generates a significant amount of heat. Monomers are a simple class of molecular “building blocks” that can react to form larger molecules that are polymers. All of the energy needed to create the polymer is contained within the monomer itself, and to harness that energy, only a small stimulus is needed to kick off the reaction.
Because of instabilities, that self-propagating front doesn’t always move uniformly. Although it is ideal for the front to move smoothly and at a constant speed for applications like composite manufacturing and 3D printing, Geubelle says, “We’re actually very interested in these instabilities because they allow us to generate patterns in the material. That’s very exciting, because for some materials, these instabilities can lead to very different properties for the material.”
Geubelle explains that the team’s goal was “to understand, experimentally and computationally, the interaction between the front that is propagating in the monomer bath and the convection that takes place ahead of it, and how the interaction between the two can lead to patterns in the material.”
To visualize and characterize the polymerization front and the recirculation ahead of the front, the team had to design a clever mold that would allow them to make observations through both the top and the side. They constructed and used a glass mold that allowed for the observation of the front from the top and for a laser beam to enter from the side.
They then used particle image velocimetry (PIV) to characterize the velocity field. To use PIV, they needed to seed the fluid with small “tracer” particles that would follow the flow and would be tracked by a camera and illuminated by a laser sheet to visualize the patterns in the material. Chamorro says that particle selection was one of the challenges of this work. The team tried various kinds of particles before settling on silver-coated glass particles.
They were able to show that as the front propagates and transforms the liquid monomer into the solid polymer, the energy released generates convection. Convection is a process where heat is transferred by the movement of a heated fluid. Like water in the ocean, when a fluid is heated, it expands, and due to buoyancy, the hotter fluid rises because it is less dense, and colder fluid replaces it by sinking to the bottom because it is more dense. This process continues, creating a recirculating flow.
The polymerization process gives off a lot of heat, resulting in temperatures over 350° F. That heat generated during the transformation goes to the top of the surface. The researchers showed that this was a buoyancy-driven process, and that the recirculation associated with the heat of the reaction, along with the effect of gravity, leads to the formation of the patterning observed in the material and to the impact on the polymerization front. Thanks to the recirculation, the front tends to be inclined rather than perfectly vertical. That inclined front can result in a different speed or cooling effect and even a different patterning effect.
Sottos says the experiments revealed that the recirculation not only creates patterns inside the material that affects the material’s properties, but “it also creates surface patterns on the top of the material as well, because the monomer is getting pushed by the recirculating flow.”
The revealed mechanisms of the interaction between the polymerization front and the induced natural convection, and the resulting patterning, represent a deepened understanding of frontal polymerization that may be helpful in the future manufacture of polymeric materials.
Other authors on this work include Yuan Gao (postdoc, Beckman Institute and Aerospace Engineering); Justine Paul (graduate student, Beckman Institute and Material Science and Engineering); Manxin Chen (undergraduate student, Beckman Institute and Aerospace Engineering); and Liu Hong (graduate student, Mechanical Science and Engineering).
More information: Y. Gao et al, Buoyancy-Induced Convection Driven by Frontal Polymerization, Physical Review Letters (2023). DOI: 10.1103/PhysRevLett.130.028101
The Haber-Bosch (HB) process is one of the most important industrial chemical reactions. It combines nitrogen and hydrogen gases in the presence of an iron-based catalyst at high temperatures and pressures to produce ammonia fertilizer which helps provide food for over five billion people.
Over the decades, researchers have tried to bring down the reaction temperature of the HB process to increase the ammonia yield while reducing energy consumption. To this end, they have recently developed new catalysts based on other transition metals, such as ruthenium, cobalt, and nickel, which exhibit much higher catalytic activity than iron.
However, these catalysts preferentially adsorb hydrogen atoms onto their surface at low temperatures of 100–150oC, which reduces nitrogen adsorption and thus hampers ammonia production. This phenomenon, known as hydrogen poisoning, poses an obstacle to the low-temperature HB process.
In this light, researchers led by Professor Michikazu Hara of the Laboratory for Materials and Structures at Tokyo Institute of Technology (Tokyo Tech), have refocused on iron-based catalysts and modified them to produce ammonia at 100oC. Their work is all set to be published in the Journal of the American Chemical Society.
Prof. Hara explains the motivation behind the research. “Hydrogen poisoning is not strong for iron-based catalysts. Therefore, they may be used for the low-temperature HB process but only when combined with an appropriate promoter that increases their catalytic activity.” In this work, the researchers prepared metallic iron (Fe) nanoparticles on calcium hydride (CaH2) particles, with a mixture of barium oxide (BaO) and barium hydride (BaH2) deposited on them.
A set of experiments revealed that the iron nanoparticles interact strongly with the hydride ions of both hydrides. As a result, hydrogen atoms move from the hydrides to the nanoparticles and get desorbed as hydrogen gas, leaving behind electrons. The hydrides donate these electrons to the iron nanoparticles. It facilitates the breaking of nitrogen gas into atoms, resulting in enhanced catalytic activity for ammonia production even at low temperatures.
The BaH2–BaO/Fe/CaH2catalyst exhibited a turnover frequency of 0.23 s-1 at 100oC and 12.3 s-1 at 300oC under a moderate pressure of 0.9 MPa. These values, orders of magnitude higher than those for catalysts based on other transition metals, result from the ability of iron to prevent hydrogen poisoning by desorbing the adsorbed hydrogen atoms as hydrogen gas at low temperatures.
Discussing the future potential of their work, Prof. Hara observes, “The BaH2–BaO/Fe/CaH2 catalyst facilitates low-temperature HB process, which consumes less energy. As such, it can reduce the use of fossil fuels and potentially lower global carbon emissions. In addition, iron is abundant and inexpensive, which makes the HB process more sustainable.”
More information: Michikazu Hara et al, Low temperature ammonia synthesis on iron catalyst with an electron donor, Journal of the American Chemical Society (2023). DOI: 10.1021/jacs.2c13015
A ban by the European Union on a number of pigments used in tattoo inks has sparked a conversation around their composition and safety.
In this video, we dive into the science of these inks, explore the new ban and investigate how new pigments from the research world might expand the possibilities of tattoos from art to medical devices.
Manganese oxides are natural reactive minerals and widely spread in aquatic and terrestrial environments, affecting the fate of metals (such as As3+ and Cd2+) and organic pollutants (such as phenols and diclofenac) through adsorption and oxidation in sewage treatment. Usually, the manganese (III/IV) oxides in the environment are thought to be formed by the oxidation of dissolved Mn(II) through abiotic or biotic processes.
Oxidation of aqueous Mn(II) by dissolved oxygen is thermodynamically favored, but the kinetic is slow due to the high energy barrier of the reaction from dissolved Mn(II) to Mn(III/IV) oxides. The presence of microorganisms accelerates the oxidation rate, which is 4–5 orders of magnitude faster than the rate of abiotic chemical oxidation, therefore is considered as the initial source of manganese oxides in the environment.
Bacteria capable of catalyzing the oxidation of dissolved Mn(II) ions to undissolved Mn(III/IV) oxides are usually called manganese-oxidizing bacteria. The bacterial oxidation of Mn(II) ions are divided into direct and indirect ways, and the process catalyzed by enzymes on the surface of microorganisms is called direct oxidation. For indirect pathways, some bacteria can change their surrounding environmental conditions for Mn(II) oxidation (e.g., the pH and Eh).
Roseobacter clade has been demonstrated to oxidize Mn(II) by producing extracellular reactive oxygen species in recent studies. Do other bacteria clades have similar Mn(II) oxidation processes with Roseobacter? Is the Mn(II) oxidation closely relative to the physiological process of bacteria?
To answer these questions, Prof. Feng Zhao from Chinese Academy of Sciences and his team members explored the microbial manganese oxidation process under visible light by using coastal surface seawater microorganisms. The relationship between the transformation of soluble Mn(II) into insoluble Mn(III/IV) oxides by microorganisms and physiological role was analyzed. This study is published in Frontiers of Environmental Science & Engineering in 2023.
In this study, the research team found visible light greatly promotes the oxidation rate of Mn(II), and the average rate reaches 64 μmol/(L·d). The generated manganese oxides were then conducive to Mn(II) oxidation, thus the rapid manganese oxidation was the result of the combined action of biotic and abiotic, and biological function accounts for 88 % ± 4 %.
Extracellular superoxide produced by microorganisms induced by visible light is the decisive factor for the rapid manganese oxidation in our study. But the production of these superoxides does not require the presence of Mn(II) ions, the Mn(II) oxidation process was more like an unintentional side reaction, which did not affect the growth of microorganisms.
More than 70 % of heterotrophic microorganisms in nature are capable of producing superoxide, based on the oxidizing properties of free radicals, all these bacteria can participate in the geochemical cycle of manganese. What’s more, the superoxide oxidation pathway might be a significant natural source of manganese oxide.
This study revealed an essential pathway for bacterial manganese oxidation. Heterotrophic bacteria produce superoxide under visible light irradiation and oxidize Mn(II) ions in the surrounding environment, which is the main source of manganese oxides. The biogenerated Mn(III/IV) oxides can also oxidize Mn(II) ions indirectly through abiotic reactions under light illumination.
Many bacteria in the environment that produce superoxide actively or passively may also oxidize Mn(II) in this way, suggesting that the manganese oxidation pathway through superoxide is a common behavior in the environment. In light of the oxidation properties and semiconductor properties of manganese oxides, this research will provide new ideas for the treatment of environmental pollution.
More information: Fan Yang et al, Visible light induces bacteria to produce superoxide for manganese oxidation, Frontiers of Environmental Science & Engineering (2022). DOI: 10.1007/s11783-023-1619-y
New research led by Penn State reveals that mutations led to the stem of the SARS-CoV-2 spike protein becoming progressively tighter over time, which may have improved the virus’s ability to transmit through nasal droplets and infect host cells once in the body. Credit: Ganesh Anand, Penn State
Just as a tight core is a component of good physical fitness for humans, helping to stabilize our bodies, mutations that tightened the core of the SARS-CoV-2 spike protein in new variants may have increased the virus’s fitness.
New research led by Penn State reveals that the stem region of the spike protein became progressively tighter over time, and the team thinks this likely improved the virus’s ability to transmit through nasal droplets and infect host cells once in the body. The team said the stem region of the protein that emerged in the most recent omicron variants is as rigid as it can get, which could mean that newer vaccines may be effective for longer than the ones that targeted the original variant.
“We wanted to see how the spike protein morphed structurally as it evolved from the original wild-type strain of the virus, through the alpha, delta and most recently omicron variants,” said Ganesh Anand, associate professor of chemistry and of biochemistry and molecular biology, Penn State.
“We found that the spike protein was initially more flexible at the stem region, which is where the spike protein is bundled together, but over time, mutations caused the protein to become progressively tighter and more rigid, and we think it’s now as rigid as it can get. This is important because it means that vaccines that are developed to target the current variant with these rigid spike proteins are likely to be effective for much longer than previous vaccines against the more flexible wild-type strain.”
To study how the spike protein changed with each of the new variants, the team studied the virus in vitro (in a test tube) using a technique called amide hydrogen/deuterium exchange mass spectrometry.
Anand explained that the SARS-CoV-2 spike protein is composed of three chain molecules called monomers that are bound together to form a trimer. The spike protein is made up of two subunits, an S1 and S2 subunit. The S1 subunit contains a receptor binding domain while the S2 subunit contains the stem region responsible for bundling the trimer.
“It is analogous to a tree, with the stem forming the trunk and the receptor binding domain forming the branches,” said Anand.
The team’s results, which published in the journal eLife, revealed that the spike protein stem first became more rigid with the D614G mutation, which is common to all SARS-CoV-2 variants. The stem became progressively more twisted with the emergence of new mutations in subsequent variants, and the omicron BA.1 variant showed the largest magnitude increase in stabilization relative to preceding variants.
Why would the virus benefit from a tighter core?
“We did not study the virus in patients, so we cannot determine if the changes we observed in the spike protein directly affected the newer variants such as omicron’s ability to transmit more readily; however, we can say that the changes likely made the virus more fit, which could translate to better transmission,” said Anand.
“A tighter core could likely make the virus more stable in nasal droplets and faster at binding to and entering host cells. So, for example, what initially took about 11 days to develop an infection after exposure now takes only about four days.”
Anand noted that one of the reasons the vaccines have not been able to fully neutralize the virus is because they were generated against the spike protein of the original wild-type variant.
“The latest bivalent booster—which targets newer variants—helps, but people who never got this booster aren’t receiving this more targeted protection,” he said. “Future vaccines that focus specifically on omicron are likely to be effective for longer.”
Finally, Anand said that the spike protein has now become so tightly twisted that it is unlikely to structurally change further at the stem region.
“There are limits to how much it can tighten,” he said. “I think that we can have some cautious optimism, in that we’re not going to continuously have variants emerging, at least tightening is not going to be a mechanism.”
Other Penn State authors on the paper include chemistry graduate students Sean Braet, Theresa Buckley and Varun Venkatakrishnan. Kim-Marie Dam, postdoctoral research fellow, and Pamela Bjorkman, assistant professor of biology and biological engineering, Caltech, also are authors.
More information: Sean M Braet et al, Timeline of changes in spike conformational dynamics in emergent SARS-CoV-2 variants reveal progressive stabilization of trimer stalk with altered NTD dynamics, eLife (2023). DOI: 10.7554/eLife.82584
Overview of DIFFDOCK. Left: The model takes as input the separate ligand and protein structures. Center: Randomly sampled initial poses are denoised via a reverse diffusion over translational, rotational, and torsional degrees of freedom. Right:. The sampled poses are ranked by the confidence model to produce a final prediction and confidence score. Credit: arXiv (2022). DOI: 10.48550/arxiv.2210.01776
With the release of platforms like DALL-E 2 and Midjourney, diffusion generative models have achieved mainstream popularity, owing to their ability to generate a series of absurd, breathtaking, and often meme-worthy images from text prompts like “teddy bears working on new AI research on the moon in the 1980s.”
But a team of researchers at MIT’s Abdul Latif Jameel Clinic for Machine Learning in Health (Jameel Clinic) thinks there could be more to diffusion generative models than just creating surreal images—they could accelerate the development of new drugs and reduce the likelihood of adverse side effects.
A paper introducing this new molecular docking model, called DiffDock, will be presented at the 11th International Conference on Learning Representations. The model’s unique approach to computational drug design is a paradigm shift from current state-of-the-art tools that most pharmaceutical companies use, presenting a major opportunity for an overhaul of the traditional drug development pipeline.
Drugs typically function by interacting with the proteins that make up our bodies, or proteins of bacteria and viruses. Molecular docking was developed to gain insight into these interactions by predicting the atomic 3D coordinates with which a ligand (i.e., drug molecule) and protein could bind together.
While molecular docking has led to the successful identification of drugs that now treat HIV and cancer, with each drug averaging a decade of development time and 90 percent of drug candidates failing costly clinical trials (most studies estimate average drug development costs to be around $1 billion to over $2 billion per drug), it’s no wonder that researchers are looking for faster, more efficient ways to sift through potential drug molecules.
Currently, most molecular docking tools used for in-silico drug design take a “sampling and scoring” approach, searching for a ligand “pose” that best fits the protein pocket. This time-consuming process evaluates a large number of different poses, then scores them based on how well the ligand binds to the protein.
In previous deep-learning solutions, molecular docking is treated as a regression problem. In other words, “it assumes that you have a single target that you’re trying to optimize for and there’s a single right answer,” says Gabriele Corso, co-author and second-year MIT Ph.D. student in electrical engineering and computer science who is an affiliate of the MIT Computer Sciences and Artificial Intelligence Laboratory (CSAIL).
“With generative modeling, you assume that there is a distribution of possible answers—this is critical in the presence of uncertainty.”
“Instead of a single prediction as previously, you now allow multiple poses to be predicted, and each one with a different probability,” adds Hannes Stärk, co-author and first-year MIT Ph.D. student in electrical engineering and computer science who is an affiliate of the MIT Computer Sciences and Artificial Intelligence Laboratory (CSAIL). As a result, the model doesn’t need to compromise in attempting to arrive at a single conclusion, which can be a recipe for failure.
To understand how diffusion generative models work, it is helpful to explain them based on image-generating diffusion models. Here, diffusion models gradually add random noise to a 2D image through a series of steps, destroying the data in the image until it becomes nothing but grainy static. A neural network is then trained to recover the original image by reversing this noising process. The model can then generate new data by starting from a random configuration and iteratively removing the noise.
In the case of DiffDock, after being trained on a variety of ligand and protein poses, the model is able to successfully identify multiple binding sites on proteins that it has never encountered before. Instead of generating new image data, it generates new 3D coordinates that help the ligand find potential angles that would allow it to fit into the protein pocket.
This “blind docking” approach creates new opportunities to take advantage of AlphaFold 2 (2020), DeepMind’s famous protein folding AI model. Since AlphaFold 1’s initial release in 2018, there has been a great deal of excitement in the research community over the potential of AlphaFold’s computationally folded protein structures to help identify new drug mechanisms of action.
But state-of-the-art molecular docking tools have yet to demonstrate that their performance in binding ligands to computationally predicted structures is any better than random chance.
Not only is DiffDock significantly more accurate than previous approaches to traditional docking benchmarks, thanks to its ability to reason at a higher scale and implicitly model some of the protein flexibility, DiffDock maintains high performance, even as other docking models begin to fail.
In the more realistic scenario involving the use of computationally generated unbound protein structures, DiffDock places 22 percent of its predictions within 2 angstroms (widely considered to be the threshold for an accurate pose, 1Å corresponds to one over 10 billion meters), more than double other docking models barely hovering over 10 percent for some and dropping as low as 1.7 percent.
These improvements create a new landscape of opportunities for biological research and drug discovery. For instance, many drugs are found via a process known as phenotypic screening, in which researchers observe the effects of a given drug on a disease without knowing which proteins the drug is acting upon.
Discovering the mechanism of action of the drug is then critical to understanding how the drug can be improved and its potential side effects. This process, known as “reverse screening,” can be extremely challenging and costly, but a combination of protein folding techniques and DiffDock may allow performing a large part of the process in silico, allowing potential “off-target” side effects to be identified early on before clinical trials take place.
“DiffDock makes drug target identification much more possible. Before, one had to do laborious and costly experiments (months to years) with each protein to define the drug docking. But now, one can screen many proteins and do the triaging virtually in a day,” Tim Peterson, an assistant professor at the University of Washington St. Louis School of Medicine, says. Peterson used DiffDock to characterize the mechanism of action of a novel drug candidate treating aging-related diseases in a recent paper.
“There is a very ‘fate loves irony’ aspect that Eroom’s law—that drug discovery takes longer and costs more money each year—is being solved by its namesake Moore’s law—that computers get faster and cheaper each year—using tools such as DiffDock.”
The findings are published on the arXiv preprint server.
More information: Gabriele Corso et al, DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking, arXiv (2022). DOI: 10.48550/arxiv.2210.01776
Particle identification plot of ions implanted in AIDA. The black contour highlights the isotopes with Pn measured for the first time in this Letter. The heaviest isotope reported in this Letter is labeled for each element. Credit: Physical Review Letters (2022). DOI: 10.1103/PhysRevLett.129.172701
Models for how heavy elements are produced within stars have become more accurate thanks to measurements by RIKEN nuclear physicists of the probabilities that 20 neutron-rich nuclei will shed neutrons.
Stars generate energy by fusing the nuclei of light elements—first hydrogen nuclei and then progressively heavier nuclei, as the hydrogen and other lighter elements are sequentially consumed. But this process can only produce the first 26 elements up to iron.
Another process, known as rapid neutron capture, is thought to produce nuclei that are heavier than iron. As its name suggests, this process involves nuclei becoming larger by rapidly snatching up stray neutrons. It requires extremely high densities of neutrons and is thus thought to occur mainly during events such as mergers of neutron stars and supernova explosions.
The neutron-rich elements produced by rapid neutron capture can lose neutrons through another process known as beta-delayed neutron emission.
Ultimately, astrophysicists dream of developing models that can accurately reproduce the natural abundances of the elements in the Universe. To achieve this goal, they need to combine astrophysical observations with measurements on nuclei in the lab.
Now, Shunji Nishimura of the RIKEN Nishina Center for Accelerator-Based Science and his co-workers have measured the possibilities that 20 neutron-rich nuclei will emit one or two neutrons.
An illustration depicting two neutron stars merging. Such collisions are believed to be responsible for generating heavy elements by a process known as rapid neutron capture. Measurements by RIKEN researchers on neutron-rich nuclei have helped tighten models of element production by this process. Credit: National Science Foundation/Ligo/Sonoma State University/A. Simonnet/Science Photo Library
Using the RIKEN Radioactive Isotope Beam Factory—one of only a handful of facilities in the world capable of performing such measurements—the team accelerated large uranium nuclei to about 70% of the speed of light and smashed them into beryllium, which produced unstable nuclei by a fission reaction. They then measured the probabilities of neutron emission when these unstable nuclei decayed.
When the results were put into models that predict the abundances of the elements, they improved their agreement with the abundances observed in the solar system.
These measurements are important for tightening up theoretical models of element production, removing nearly 30% of their inherent uncertainty.
“While we still have a long way to go before we can determine the natural abundances of the elements, our measurements have helped close in on the fine structure in the region of elements near tin, which is determined by the so-called freeze-out time of rapid neutron capture,” explains Nishimura. “So we’re very close to having a good understanding of this part of the nuclei chart.”
The research is published in the journal Physical Review Letters.
The team now intends to investigate the impact of about 200 delayed neutrons on the production of elements up to bismuth by rapid neutron capture.
More information: V. H. Phong et al, β -Delayed One and Two Neutron Emission Probabilities Southeast of Sn132 and the Odd-Even Systematics in r -Process Nuclide Abundances, Physical Review Letters (2022). DOI: 10.1103/PhysRevLett.129.172701
Two ball mill chambers mixing chemicals during a solid-state, mechanochemical reaction. Credit: WPI-ICReDD
Chemists at Hokkaido University and the Institute for Chemical Reaction Design and Discovery (WPI-ICReDD) have developed the first high-performance catalyst specifically designed and optimized for solid-state, mechanochemical synthesis.
The team found that by attaching long polymer molecules to a metal catalyst, they could trap the catalyst in a fluid-phase, which enabled efficient reactivity at near room temperature. This approach, reported in the Journal of the American Chemical Society, could bring cost and energy savings if adapted for wide application in chemical research and industry.
Chemical synthetic reactions are usually performed in solution, where dissolved molecules can intermingle and react freely. In recent years, however, chemists have developed a process called mechanochemical synthesis, in which solid state crystals and powders are ground together. This approach is advantageous because it reduces the use of hazardous solvents and can allow reactions to proceed faster and at lower temperatures, saving energy costs. It can also be used for reactions between compounds that are difficult to dissolve in available solvents.
However, solid-state reactions occur in a very different environment than solution-based reactions. Previous studies found that palladium complex catalysts originally designed for use in solution often did not work sufficiently in solid-state mechanochemical reactions, and that high reaction temperatures were required. Using the unmodified palladium catalyst for solid-state reactions resulted in limited efficiency due to the tendency of palladium to aggregate into an inactive state. The team chose to embark in a new direction, designing a catalyst to overcome this mechanochemical problem of aggregation.
General reaction scheme using the polymer-chain modified palladium catalyst designed for mechanochemical reactions. Credit: Tamae Seo, Koji Kubota, Hajime Ito. Journal of the American Chemical Society. March 9, 2023
“We developed an innovative solution, linking palladium through a specially designed phosphine ligand to a large polymer molecule called polyethylene glycol,” researcher Hajime Ito explains.
The polyethylene glycol molecules form a region between the solid materials that behaves like a molecular-level fluid phase, where mechanochemical Suzuki-Miyaura cross-coupling reactions proceed much more efficiently and without the problematic aggregation of palladium. In addition to achieving significantly higher product yields, the reaction proceeded effectively near room temperature—the previously best-performing alternative required heating to 120°C. Similar cross-coupling reactions are widely used in research and the chemical industry.
“This is the first demonstration of a system that is specifically modified to harness the potential of palladium complex catalysts in the unique environment of a mechanochemical reaction,” says researcher Koji Kubota.
They believe it could be adapted for many other reactions, and also for catalysts using other elements from the transition metals of the periodic table.
The wider adoption of the process, and others like it, could eventually bring significant savings in costs and energy consumption in commercial chemical processes while allowing more environmentally friendly large-scale production of many useful chemicals.
More information: Tamae Seo et al, Mechanochemistry-Directed Ligand Design: Development of a High-Performance Phosphine Ligand for Palladium-Catalyzed Mechanochemical Organoboron Cross-Coupling, Journal of the American Chemical Society (2023). DOI: 10.1021/jacs.2c13543
Natural products containing pyrroloindoline moieties and the crocagin BGC. a, Structures of the calabar alkaloid (physostigmine) and naseseazine. b, Chemical structures of crocagins A (1) and B (2). c, Crocagin BGC found in Chondromyces crocatus CM c5. Genes encoding for putative biosynthetic proteins are shown in orange (dark orange is part of this study); predicted transport proteins, in blue; a regulatory protein, in gray; and the precursor peptide CgnA, in black, which is depicted below the BGC. CgnA is 21 amino acids long and consists of a leader peptide (gray) and a three-amino-acid core peptide (green). Relative sizes of genes and intergenic regions are approximate. Credit: Nature Chemistry (2023). DOI: 10.1038/s41557-023-01153-w
A mystery about how a chemical compound found in nature could be synthesized in the lab may have been solved, scientists say—a breakthrough that could unlock new developments in medicine.
Scientists from universities and research institutions in Scotland and Germany are behind the discovery, now published in the journal Nature Chemistry. The paper shows for the first time how three proteins are key to the production of alkaloid compounds called crocagins.
Alkaloids derived from natural sources have given us a wide range of vitally important medicines—morphine is perhaps the most famous example.
Pyrroloindolines are alkaloids that are produced naturally by some types of bacteria, fungi and plants, as well as the skin secretions of some types of frogs. Previous research has suggested that they have powerful bioactive properties, which could make them useful as antibiotics, antivirals, and even cancer treatments.
The work could pave the way for researchers to use the crocagin “scaffold”—the molecules’ core structure—as a starting point to search for new medicines based on the core structure of pyrroloindolines.
Crocagins are produced from a peptide that has been made by the ribosome, the same way most proteins in cells are made, and this peptide then gets modified by specialized enzymes.
These types of natural products, called ribosomally synthesized and post-translationally modified peptides (RiPPs) are increasingly valuable to researchers in applications including medicine and biotechnology.
Advances in gene sequencing and editing have made it possible to engineer RiPPs to safely harness those unique properties for new developments across a range of industries.
In the paper, the researchers describe how they unraveled the biochemical pathway that produces crocagins and showed how the core structure of the alkaloid crocagin can be synthesized from a precursor peptide, CgnA, by three enzymes, CgnB, CgnC and CgnE in one step.
They also used bioinformatic analysis techniques to find the genetic blueprints to make similar molecules in other bacteria.
Professor Jesko Koehnke, of the University of Glasgow’s School of Chemistry, led the research and is the paper’s corresponding author. He said, “It is very exciting to discover how we can turn a peptide into this kind of alkaloid, using the natural tools that evolution has provided, especially because it opens up the possibility of finding related molecules with bioactivities that could be useful in new applications.
“Pyrroloindolines are also not easy to synthesize in the lab, and hopefully our insights are going to contribute to different ways of making these molecules.
“This is an exciting discovery, and one that was several years in the making as we worked to learn more about the biochemical pathway involved in the process. It would not have been possible to decipher this pathway without my brilliant collaborators in the U.K. and Germany.
“We’ll continue to explore molecules related to crocagins that likely share the same core structure. We’re looking forward to seeing how other researchers build on the intriguing possibilities we’ve uncovered in this paper.”
More information: Sebastian Adam et al, Unusual peptide-binding proteins guide pyrroloindoline alkaloid formation in crocagin biosynthesis, Nature Chemistry (2023). DOI: 10.1038/s41557-023-01153-w
