Supramolecular chemistry: Self-constructed folded macrocycles with low symmetry

Molecules that are made up of multiple repeating subunits, known as monomers, which may vary or not in their chemical structure, are classified as macromolecules or polymers. Examples exist in nature, including proteins and nucleic acids, which are at the heart of all biological systems. Proteins not only form the basis of structural elements in cells, they also serve as enzymes — which catalyze essentially all of the myriad of chemical transformations that take place in living systems. In contrast, nucleic acids such as DNA and RNA serve as informational macromolecules. DNA stores the cell’s genetic information, which is selectively copied into RNA molecules that provide the blueprints for the synthesis of proteins. In addition, long chains comprised of sugar units provide energy reserves in the form of glycogen, which is stored in the liver and the muscles. These diverse classes of polymeric molecules all have one feature in common: They spontaneously fold into characteristic spatial conformations, for example the famous DNA double helix, which in most cases are essential for their biochemical functions.

Professor Ivan Huc (Department of Pharmacy, LMU) studies aspects of the self-organization processes that enable macromolecules to adopt defined folded shapes. The molecular structures found in nature provide him with models, whose properties he tries to reproduce in the laboratory with non-natural molecules that are neither proteins, nucleic acids or sugar-like. More specifically, he uses the tools of synthetic chemistry to elucidate the underlying principles of self-organization — by constructing molecules that are expressly designed to fold into predetermined shapes. Beginning with monomers that his group has developed, he sets out to produce what he calls ‘foldamers’, by assembling the monomers one by one to generate a folded macromolecule.

Structures with low degrees of symmetry

“The normal way to get the complex structure of proteins is to use different types of monomers, called amino acids,” as Huc reports. “And the normal method to connect different amino acids in the the correct order is to link them one by one.” The sequence of amino acids contains the folding information that allows different protein sequences to fold in different ways.

“But we discovered something unexpected and spectacular,” comments Huc. He and his colleagues in Munich, Groningen, Bordeaux and Berlin used organic, sulfur-containing monomers to spontaneously get cyclic macromolecules with a complex shape, as illustrated by their low degree of symmetry, without requiring a specific sequence. The macromolecules self-synthesize — no further conditions are necessary. “We only put one monomer type in a flask and wait,” Huc says. “This is typical for a polymerization reaction, but polymers from a single monomer usually don´t adopt complex shapes and don’t stop growing at a precise chain length.”

To further control the reaction, the scientists also used either a small guest molecule or a metal ion. The regulator binds within the growing macromolecule and causes monomers to arrange themselves around it. By choosing a regulator with the appropriate characteristics, the authors of the new study were able to produce structures with a predetermined number of subunits. The cyclic macromolecules exhibited low levels of symmetry. Some consisted of either 13, 17 or 23 subunits. Since 13, 17 and 23 are prime numbers, the corresponding folded shapes exhibit low degrees of symmetry.

A model for biological and industrial processes

Interest in the elucidation of such mechanisms is not restricted to the realm of basic research. Huc and his colleagues hope that their approach will lead to the fabrication of designer plastics. Conventional polymers usually consist of mixtures of molecules that vary in length (i.e. the number of monomers they contain). This heterogeneity has an impact on their physical properties. Hence, the ability to synthesize polymer chains of an exact length and/or geometry is expected to lead to materials with novel and interesting behaviors.

Furthermore, foldamers like those that have now been synthesized show close structural resemblances to biopolymers. They therefore offer an ideal model system in which to study the properties of proteins. Every protein is made up of a defined linear (i.e. unbranched) sequence of amino acids, which constitutes its ‘primary structure’. But most amino-acid chains fold into local substructures such as helically coiled stretches, or parallel strands that can form sheets. These units represent the protein’s secondary structure. The term ‘tertiary structure’ is applied to the fully folded single chain. This in turn can interact with other chains to form a functional unit or quaternary structure.

Huc’s ultimate goal is to mimic complex biological mechanisms using structurally defined, synthetic precursors. He wants to understand how, for example, enzymes fold into the correct, biologically active conformation following their synthesis in cells. Molecules whose properties can be precisely controlled in the laboratory provide ideal models with which to work out the answers and perhaps to go beyond enzymes themselves.

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Chemistry: How nitrogen is transferred by a catalyst

Catalysts with a metal-nitrogen bond can transfer nitrogen to organic molecules. In this process short-lived molecular species are formed, whose properties critically determine the course of the reaction and product formation. The key compound in a catalytic nitrogen-atom transfer reaction has now been analysed in detail by chemists. The detailed understanding of this reaction will allow for the design of catalysts tailored for specific reactions.

The development of new drugs or innovative molecular materials with new properties requires specific modification of molecules. Selectivity control in these chemical transformations is one of the main goals of catalysis. This is particularly true for complex molecules with multiple reactive sites in order to avoid unnecessary waste for improved sustainability. The selective insertion of individual nitrogen atoms into carbon-hydrogen bonds of target molecules is, for instance, a particularly interesting goal of chemical synthesis. In the past, these kinds of nitrogen transfer reactions were postulated based on quantum-chemical computer simulations for molecular metal complexes with individual nitrogen atoms bound to the metal. These highly reactive intermediates have, however, previously escaped experimental observation. A closely entangled combination of experimental and theoretical studies is thus indispensable for detailed analysis of these metallonitrene key intermediates and, ultimately, the exploitation of catalytic nitrogen-atom transfer reactions.

Chemists in the groups of Professor Sven Schneider, University of Göttingen, and Professor Max Holthausen, Goethe University Frankfurt, in collaboration with the groups of Professor Joris van Slagern, University of Stuttgart and Professor Bas de Bruin, University of Amsterdam, have now been able for the first time to directly observe such a metallonitrene, measure it spectroscopically and provide a comprehensive quantum-chemical characterization. To this end, a platinum azide complex was transformed photochemically into a metallonitrene and examined both magnetometrically and using photo-crystallography. Together with theoretical modelling, the researchers have now provided a detailed report on a very reactive metallonitrene diradical with a single metal-nitrogen bond. The group was furthermore able to show how the unusual electronic structure of the platinum metallonitrene allows the targeted insertion of the nitrogen atom into, for example, C-H bonds of other molecules.

Professor Max Holthausen explains: “The findings of our work significantly extend the basic understanding of chemical bonding and reactivity of such metal complexes, providing the basis for a rational synthesis planning.” Professor Sven Schneider says: “These insertion reactions allow the use of metallonitrenes for the selective synthesis of organic nitrogen compounds through catalyst nitrogen atom transfer. This work therefore contributes to the development of novel ‘green’ syntheses of nitrogen compounds.”

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Researchers use artificial intelligence language tools to decode molecular movements

By applying natural language processing tools to the movements of protein molecules, University of Maryland scientists created an abstract language that describes the multiple shapes a protein molecule can take and how and when it transitions from one shape to another.

A protein molecule’s function is often determined by its shape and structure, so understanding the dynamics that control shape and structure can open a door to understanding everything from how a protein works to the causes of disease and the best way to design targeted drug therapies. This is the first time a machine learning algorithm has been applied to biomolecular dynamics in this way, and the method’s success provides insights that can also help advance artificial intelligence (AI). A research paper on this work was published on October 9, 2020, in the journal Nature Communications.

“Here we show the same AI architectures used to complete sentences when writing emails can be used to uncover a language spoken by the molecules of life,” said the paper’s senior author, Pratyush Tiwary, an assistant professor in UMD’s Department of Chemistry and Biochemistry and Institute for Physical Science and Technology. “We show that the movement of these molecules can be mapped into an abstract language, and that AI techniques can be used to generate biologically truthful stories out of the resulting abstract words.”

Biological molecules are constantly in motion, jiggling around in their environment. Their shape is determined by how they are folded and twisted. They may remain in a given shape for seconds or days before suddenly springing open and refolding into a different shape or structure. The transition from one shape to another occurs much like the stretching of a tangled coil that opens in stages. As different parts of the coil release and unfold, the molecule assumes different intermediary conformations.

But the transition from one form to another occurs in picoseconds (trillionths of a second) or faster, which makes it difficult for experimental methods such as high-powered microscopes and spectroscopy to capture exactly how the unfolding happens, what parameters affect the unfolding and what different shapes are possible. The answers to those questions form the biological story that Tiwary’s new method can reveal.

Tiwary and his team applied Newton’s laws of motion — which can predict the movement of atoms within a molecule — with powerful supercomputers, including UMD’s Deepthought2, to develop statistical physics models that simulate the shape, movement and trajectory of individual molecules.

Then they fed those models into a machine learning algorithm, like the one Gmail uses to automatically complete sentences as you type. The algorithm approached the simulations as a language in which each molecular movement forms a letter that can be strung together with other movements to make words and sentences. By learning the rules of syntax and grammar that determine which shapes and movements follow one another and which don’t, the algorithm predicts how the protein untangles as it changes shape and the variety of forms it takes along the way.

To demonstrate that their method works, the team applied it to a small biomolecule called riboswitch, which had been previously analyzed using spectroscopy. The results, which revealed the various forms the riboswitch could take as it was stretched, matched the results of the spectroscopy studies.

“One of the most important uses of this, I hope, is to develop drugs that are very targeted,” Tiwary said. “You want to have potent drugs that bind very strongly, but only to the thing that you want them to bind to. We can achieve that if we can understand the different forms that a given biomolecule of interest can take, because we can make drugs that bind only to one of those specific forms at the appropriate time and only for as long as we want.”

An equally important part of this research is the knowledge gained about the language processing system Tiwary and his team used, which is generally called a recurrent neural network, and in this specific instance a long short-term memory network. The researchers analyzed the mathematics underpinning the network as it learned the language of molecular motion. They found that the network used a kind of logic that was similar to an important concept from statistical physics called path entropy. Understanding this opens opportunities for improving recurrent neural networks in the future.

“It is natural to ask if there are governing physical principles making AI tools successful,” Tiwary said. “Here we discover that, indeed, it is because the AI is learning path entropy. Now that we know this, it opens up more knobs and gears we can tune to do better AI for biology and perhaps, ambitiously, even improve AI itself. Anytime you understand a complex system such as AI, it becomes less of a black-box and gives you new tools for using it more effectively and reliably.”

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Researchers develop tools to sharpen 3D view of large RNA molecules

University of Maryland scientists have developed a method to determine the structures of large RNA molecules at high resolution. The method overcomes a challenge that has limited 3D analysis and imaging of RNA to only small molecules and pieces of RNA for the past 50 years.

The new method, which expands the scope of nuclear magnetic resonance (NMR) spectroscopy, will enable researchers to understand the shape and structure of RNA molecules and learn how they interact with other molecules. The insights provided by this technology could lead to targeted RNA therapeutic treatments for disease. The research paper on this work was published in the journal Science Advances on October 7, 2020.

“The field of nuclear magnetic resonance spectroscopy has been stuck looking at things that are small, say 35 RNA building blocks or nucleotides. But most of the interesting things that are biologically and medically relevant are much bigger, 100 nucleotides or more,” said Kwaku Dayie, a professor of chemistry and biochemistry at UMD and senior author of the paper. “So, being able to break down the log jam and look at things that are big is very exciting. It will allow us to peek into these molecules and see what is going on in a way we haven’t been able to do before.”

In NMR spectroscopy, scientists direct radio waves at a molecule, exciting the atoms and “lighting up” the molecule. By measuring changes in the magnetic field around the excited atoms — the nuclear magnetic resonance — scientists can reconstruct characteristics such as the shape, structure and motion of the molecule. The data this produces can then be used to generate images, much like MRI images seen in medicine.

Ordinarily, NMR signals from the many atoms in a biological molecule such as RNA overlap with each other, making analysis very difficult. However, in the 1970s, scientists learned to biochemically engineer RNA molecules to work better with NMR by replacing the hydrogen atoms with magnetically active fluorine atoms. In relatively small molecules of RNA consisting of 35 or fewer nucleotides, the fluorine atoms light up readily when hit with radio waves and remain excited long enough for high-resolution analysis. But as RNA molecules get larger, the fluorine atoms light up only briefly, then quickly lose their signal. This has prevented high-resolution 3D analysis of larger RNA molecules.

Previous work by others had shown that fluorine continued to produce a strong signal when it was next to a carbon atom containing six protons and seven neutrons (C-13). So, Dayie and his team developed a relatively easy method to change the naturally occurring C-12 in RNA (which has 6 protons and 6 neutrons) to C-13 and install a fluorine atom (F-19) directly next to it.

Dayie and his team first demonstrated that their method could produce data and images equal to current methods by applying it to pieces of RNA from HIV containing 30 nucleotides, which had been previously imaged. They then applied their method to pieces of Hepatitis B RNA containing 61 nucleotides — nearly double the size of previous NMR spectroscopy possible for RNA.

Their method enabled the researchers to identify sites on the hepatitis B RNA where small molecules bind and interact with the RNA. That could be useful for understanding the effect of potential therapeutic drugs. The next step for the researchers is to analyze even larger RNA molecules.

“This work allows us to expand what can be brought into focus,” Dayie said. “Our calculations tell us that, in theory, we can look at really big things, like a part of the ribosome, which is the molecular machine that synthesizes proteins inside cells.”

By understanding the shape and structure of a molecule, scientists can better understand its function and how it interacts with its environment. What’s more, this technology will enable scientists to see the 3D structure as it changes, because RNA molecules in particular change shape frequently. This knowledge is key to developing therapeutics that narrowly target disease-specific molecules without affecting healthy cell functions.

“The hope is that if researchers know the nooks and crannies in a molecule that is dysfunctional, then they can design drugs that fill the nooks and crannies to take it out of commission,” Dayie said. “And if we can follow these molecules as they change shape and structure, then their response to potential drugs will be a little bit more predictable, and designing drugs that are effective can be more efficient.”

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Using laser to cool polyatomic molecule

After firing the lasers and bombarding the molecules with light, the scientists gathered around the camera to check the results. By seeing how far these cold molecules expanded they would know almost instantly whether they were on the right track or not to charting new paths in quantum science by being the first to cool (aka slow down) a particularly complex, six-atom molecule using nothing but light.

“When we started out on the project we were optimistic but were not sure that we would see something that would show a very dramatic effect,” said Debayan Mitra, a postdoctoral researcher in Harvard’s Doyle Research Group. “We thought that we would need more evidence to prove that we were actually cooling the molecule, but then when we saw the signal, it was like, ‘Yeah, nobody will doubt that.’ It was big and it was right there.”

The study led by Mitra and graduate student Nathaniel B. Vilas is the focus of a new paper published in Science. In it, the group describes using a novel method combining cryogenic technology and direct laser light to cool the nonlinear polyatomic molecule calcium monomethoxide (CaOCH3) to just above absolute zero.

The scientists believe their experiment marks the first time such a large complex molecule has been cooled using laser light and say it unlocks new avenues of study in quantum simulation and computation, particle physics, and quantum chemistry.

“These kinds of molecules have structure that is ubiquitous in chemical and biological systems,” said John M. Doyle, the Henry B. Silsbee Professor of Physics and senior author on the paper. “Controlling perfectly their quantum states is basic research that could shed light on fundamental quantum processes in these building blocks of nature.”

The use of lasers to control atoms and molecules — the eventual building-blocks of a quantum computer — has been used since the 1960s and has since revolutionized atomic, molecular, and optical physics.

The technique essentially works by firing a laser at them, causing the atoms and molecules to absorb the photons from the light and recoil in the opposite direction. This eventually slows them down and even stops them in their tracks. When this happens quantum mechanics becomes the dominant way to describe and study their motion.

“The idea is that on one end of the spectrum there are atoms that have very few quantum states,” Doyle said. Because of this, these atoms are easy to control with light since they often remain in the same quantum state after absorbing and emitting light, he said. “With molecules they have motion that does not occur in atoms — vibrations and rotations. When the molecule absorbs and emits light this process can sometimes make the molecule spin around or vibrate internally. When this happens, it is now in a different quantum state and absorbing and emitting light no longer works [to cool it]. We have to ‘calm the molecule down,’ get rid of its extra vibration before it can interact with the light the way we want.”

Scientists — including those from the Doyle Group which is part of the Harvard Department of Physics and a member of the Harvard-MIT Center for Ultracold Atoms — have been able to cool a number of molecules using light, such as diatomic and triatomic molecules which each have two or three atoms.

Polyatomic molecules, on the other hand, are much more complex and have proven much more difficult to manipulate because of all the vibrations and rotations.

To get around this, the group used a method they pioneered to cool diatomic and triatomic molecules. Researchers set up up a sealed cryogenic chamber where they cooled helium to below four Kelvin (that’s close to 450 degrees below zero in Fahrenheit). This chamber essentially acts as a fridge. It’s this fridge where the scientists created the molecule CaOCH3. Right off the bat, it was already moving at a much slower velocity than it would normally, making it ideal for further cooling.

Next came the lasers. They turned on two beams of light coming at the molecule from opposing directions. These counterpropagating lasers prompted a reaction known as Sisyphus cooling. Mitra says the name is fitting since in Greek mythology Sisyphus is punished by having to roll a giant boulder up a hill for eternity, only for it to roll back down when he nears the top.

The same principle happens here with molecules, Mitra said. When two identical laser beams are firing in opposite directions, they form a standing wave of light. There are places where the light is less intense and there are places where it is stronger. This wave is what forms a metaphorical hill for the molecules.

The “molecule starts at the bottom of a hill formed by the counter-propagating laser beams and it starts climbing that hill just because it has some kinetic energy in it and as it climbs that hill, slowly, the kinetic energy that was its velocity gets converted into potential energy and it slows down and slows down and slows down until it gets to the top of the hill where it’s the slowest,” he said.

At that point, the molecule moves closer to a region where the light intensity is high, where it will more likely absorb a photon and rolls back down to the opposite side. “All they can do is keep doing this again and again and again,” Mitra said.

By looking at images from cameras placed outside the sealed chamber, the scientists then inspect how much a cloud of these molecules expands as it travels through the system. The smaller the width of the cloud, the less kinetic energy it has — therefore the colder it is.

Analyzing the data further, they saw just how cold. They took it from 22 milikelvin to about 1 milikelvin. In other words, just a few thousandths of a decimal above absolute zero.

In the paper, the scientists lay out ways get the molecule even colder and lay out some of the doors it opens in a range of modern physical and chemical research frontiers. The scientists explain, the study is a proof of concept that their method could be used to cool other carefully chosen complex molecules to help advance quantum science.

“What we did here is sort of extending the state of the art,” Mitra said. “It’s always been debated whether we would ever have technology that will be good enough to control complex molecules at the quantum level. This particular experiment is just a stepping stone.”

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Researchers develop a yeast-based platform to boost production of rare natural molecules

Many modern medicines, including analgesics and opioids, are derived from rare molecules found in plants and bacteria. While they are effective against a host of ailments, a number of these molecules have proven to be difficult to produce in large quantities. Some are so labour intensive that it is uneconomical for pharmaceutical companies to produce them in sufficient amounts to bring them to market.

In a new study published in Nature Communications, Vincent Martin outlines a method to synthesize complex bioactive molecules much more quickly and efficiently.

One of the principal ingredients in this new technique developed by the biology professor and Concordia University Research Chair in Microbial Engineering and Synthetic Biology is simple baker’s yeast.

The single-cell organism has cellular processes that are similar to those of humans, giving biologists an effective substitute in drug development research. Using cutting-edge synthetic biology approaches, Martin and his colleagues in Berkeley, California were able to produce a large amount of benzylisoquinoline alkaloid (BIA) to synthesize an array of natural and new-to-nature chemical structures in a yeast-based platform.

This, he says, can provide a blueprint for the large-scale production of thousands of products, including the opioid analgesics morphine and codeine. The same is true for opioid antagonists naloxone and naltrexone, used to treat overdose and dependence.

A long journey from gene to market

Martin has been working toward this outcome for most of the past two decades. He began with researching the genetic code plants use to produce the molecules used as drugs by the pharmaceutical industry. Then came transplanting their genes and enzymes into yeast to see if production was possible outside a natural setting. The next step is industrial production.

“We showed in previous papers that we can get milligrams of these molecules fairly easily, but you’re only going to be able to commercialize the process if you get grams of it,” Martin explains. “In principle, we now have a technology platform where we can produce them on that scale.”

This, he says, can have huge implications for a country like Canada, which has to import most of the rare molecules used in drugs from overseas. That’s especially relevant now, in the midst of a global pandemic, when fragile supply chains are at risk of being disrupted.

“To me, this really highlights the importance of finding alternative biotech-type processes that can be developed into a homemade, Canadian pharmaceutical industry,” he adds. “Many of the ingredients we use today are not very difficult to make. But if we don’t have a reliable supply process in Canada, we have a problem.”

Healthy savings

Martin admits he is curious to see where the technology leads us. He believes researchers can and will use the new platform for the commercialization and discovery of new drugs.

“We demonstrate that by using this platform, we can start building what is called new-to-nature molecules,” he says. “By experimenting with enzymes and genes and the way we grow things, we can begin making these into tools that can be used in the drug discovery process. We can access a whole new structural space.”

This study was financially supported by a Natural Sciences and Engineering Research Council of Canada (NSERC) Industrial Biocatalysis Grant, an NSERC Discovery Grant and by River Stone Biotech ApS.

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Materials provided by Concordia University. Original written by Patrick Lejtenyi. Note: Content may be edited for style and length.

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Large molecules need more help to travel through a nuclear pore into the cell nucleus

A new study in the field of biophysics has revealed how large molecules are able to enter the nucleus of a cell. A team led by Professor Edward Lemke of Johannes Gutenberg University Mainz (JGU) has thus provided important insights into how some viruses, for example, can penetrate into the nucleus of a cell, where they can continue to proliferate and infect others. They have also demonstrated that the efficiency of transport into a cell decreases as the size of the molecules increases and how corresponding signals on the surface can compensate for this.

“We have been able to gain new understanding of the transport of large biostructures, which helped us develop a simple model that describes how this works,” said Lemke, a specialist in the field of biophysical chemistry. He is Professor of Synthetic Biophysics at JGU and Adjunct Director of the Institute of Molecular Biology (IMB) in Mainz.

Nuclear localization signals facilitate rapid entry

A typical mammalian cell has about 2,000 nuclear pores, which act as passageways from the cell cytoplasm into the cell nucleus and vice versa. These pores in the nuclear envelope act as gatekeepers that control access and deny entry to larger molecules of around five nanometers in diameter and greater. Molecules that have certain nuclear localization sequences on their surface can bind to structures within nuclear pores, allowing them to enter into the nucleus rapidly. “Nuclear pores are remarkable in the diversity of cargoes they can transport. They import proteins and viruses into the nucleus and export ribonucleic acids and proteins into the cell cytoplasm,” explained Lemke, describing the function of these pores. “Despite the fundamental biological relevance of the process, it has always been an enigma how large cargoes greater than 15 nanometers are efficiently transported, particularly in view of the dimensions and structures of nuclear pores themselves.”

With this is mind and as part of their project, the researchers designed a set of large model transport cargoes. These were based on capsids, i.e., protein “shells” in viruses that enclose the viral genome. The cargo models ranging from 17 to 36 nanometers in diameter were then fluorescently labeled, allowing them to be observed on their way through cells. Capsid models without nuclear localization signals on their surface remained in the cell cytoplasm and did not enter the cell nucleus. As the number of nuclear localization signals increased, the accumulation of the model capsid in the nucleus became more efficient. But even more interestingly, the researchers found that the larger the capsid, the greater was the number of nuclear localization signals needed to enable efficient transport into the nucleus.

The research team looked at a range of capsids of various viruses including the hepatitis B capsid, the largest cargo used in this study. But even increasing the number of nuclear localization signals to 240 did not result in the transport of this capsid into the nucleus. This corresponds with the results of earlier studies of the hepatitis B virus that have indicated that only the mature infectious virus is capable of passage through a nuclear pore into the nucleus.

Cooperation enabled the development of a mathematical model

In cooperation with Professor Anton Zilman of the University of Toronto in Canada, a mathematical model was developed to shed light on the transport mechanism and to establish the main factors determining the efficiency of transport. “Our simple two-parameter biophysical model has recreated the requirements for nuclear transport and revealed key molecular determinants of the transport of large biological cargoes on cells,” concluded first author Giulia Paci, who carried out the study as part of her PhD thesis at the European Molecular Biology Laboratory (EMBL) in Heidelberg.

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Advance in programmable synthetic materials

Artificial molecules could one day form the information unit of a new type of computer or be the basis for programmable substances. The information would be encoded in the spatial arrangement of the individual atoms — similar to how the sequence of base pairs determines the information content of DNA, or sequences of zeros and ones form the memory of computers.

Researchers at the University of California, Berkeley, and Ruhr-Universität Bochum (RUB) have taken a step towards this vision. They showed that atom probe tomography can be used to read a complex spatial arrangement of metal ions in multivariate metal-organic frameworks.

Metal-organic frameworks (MOFs) are crystalline porous networks of multi-metal nodes linked together by organic units to form a well-defined structure. To encode information using a sequence of metals, it is essential to be first able to read the metal arrangement. However, reading the arrangement was extremely challenging. Recently, the interest in characterizing metal sequences is growing because of the extensive information such multivariate structures would be able to offer.

Fundamentally, there was no method to read the metal sequence in MOFs. In the current study, the research team has successfully done so by using atom probe tomography (APT), in which the Bochum-based materials scientist Tong Li is an expert. The researchers chose MOF-74, made by the Yaghi group in 2005, as an object of interest. They designed the MOFs with mixed combinations of cobalt, cadmium, lead, and manganese, and then decrypted their spatial structure using APT.

Li, professor and head of the Atomic-Scale Characterisation research group at the Institute for Materials at RUB, describes the method together with Dr. Zhe Ji and Professor Omar Yaghi from UC Berkeley in the journal Science, published online on August 7, 2020.

Just as sophisticated as biology

In the future, MOFs could form the basis of programmable chemical molecules: for instance, an MOF could be programmed to introduce an active pharmaceutical ingredient into the body to target infected cells and then break down the active ingredient into harmless substances once it is no longer needed. Or MOFs could be programmed to release different drugs at different times.

“This is very powerful, because you are basically coding the behavior of molecules leaving the pores,” Yaghi said.

They could also be used to capture CO2 and, at the same time, convert the CO2 into a useful raw material for the chemical industry.

“In the long term, such structures with programmed atomic sequences can completely change our way of thinking about material synthesis,” write the authors. “The synthetic world could reach a whole new level of precision and sophistication that has previously been reserved for biology.”

The work was supported by the Center of Excellence for Nanomaterials and Clean Energy Applications at King Abdulaziz City for Science and Technology.

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New sequencing technology will help scientists decipher disease mechanisms

New technologies capable of sequencing single molecules in fine detail will help scientists better understand the mechanisms of rare nucleotides thought to play an important role in the progression of some diseases.

A review paper, led by a scientist at the University of Birmingham, describes how emerging sequencing technologies will transform our understanding of these molecules, ultimately leading to new drug targets. The paper is published in the journal Trends in Biotechnology.

Expression of genes to make protein involves making a messenger RNA molecule. Although RNA, like DNA consist of the four nucleotides, some of them carry decorations called the epitranscriptome. These modified nucleotides are important additions to the genetic code whose functions are little understood, but have been linked to disease such as obesity, cancer and neurological disorders.

Although the importance of the epitranscriptome is recognized, its detection is difficult and comes with high error rates.

Scientist have been interested in these rare modified nucleotides since their discovery more than 40 years ago, but they had been very difficult to examine in specific genes due to technical difficulties. However, their importance has been recognized, because many human parasites and viruses have them. Even more, some viruses including coronavirus SARS-CoV2 have their own RNA modification enzymes, originally acquired from their hosts, but then adapted to their needs.

Until recently, the study of these modified nucleotides has been limited because they occur so rarely, and existing technologies have not been sufficiently fine-tuned to detect the modifications.

The new technology, developed by Oxford Nanopore Technologies, is promising to overcome current sequencing limitations, with highly selective sequencing capabilities. By identifying specific nucleotide targets associated with particular diseases, drug developers will be able to start to investigate inhibitor drugs that can interfere with the molecules and influence the progression of the disease.

Lead author of this multinational study, Dr Matthias Soller from the University of Birmingham, UK, says: “These modified nucleotides are particularly hard to detect and previously it was impossible to examine their occurrence in the entire genome with high confidence.”

First author and Schmidt Science Fellow Dr Ina Anreiter, University of Toronto, Canada, adds: “Previously, it was only possible to look at one modification at a time, but there a more than just one and they likely hiding a yet to discover code.

“This new technology will really enable a step-change in how we approach modified nucleotides, giving us a ‘real-time’ topographic map of where the molecules are within the genome, and how frequently they occur. This will be really important in instructing further research into their function and providing us with new insights into how these molecules lead to human disease.”

Dr Soller added: “There is plenty of work still to be done to further develop these sequencing devices, including improving the machine-learning capability for interpreting the sequencing signals, but progress is happening rapidly and I think we will be seeing some very exciting results emerging from this technology.”

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Etching the road to a hydrogen economy using plasma jets

Hydrogen is a clean energy source that can be produced by splitting water molecules with light. However, it is currently impossible to achieve this on a large scale. In a recent breakthrough, scientists developed a novel method that uses plasma discharge in solution to improve the performance of the photocatalyst in the water-splitting reaction. This opens doors to exploring a number of photocatalysts that can help scale-up this reaction.

The ever-worsening global environmental crisis, coupled with the depletion of fossil fuels, has motivated scientists to look for clean energy sources. Hydrogen (H2) can serve as an eco-friendly fuel, and hydrogen generation has become a hot research topic. While no one has yet found an energy-efficient and affordable way to produce hydrogen on a large scale, progress in this field is steady and various techniques have been proposed.

One such technique involves using light and catalysts (materials that speed up reactions) to split water (H2O) into hydrogen and oxygen. The catalysts have crystalline structures and the ability to separate charges at the interfaces between some of their sides. When light hits the crystal at certain angles, the energy from the light is absorbed into the crystal, causing certain electrons to become free from their original orbits around atoms in the material. As an electron leaves its original place in the crystal, a positively charged vacancy, known as a hole, is created in the structure. Generally, these “excited” states do not last long, and free electrons and holes eventually recombine.

This is the case with bismuth vanadate (BiVO4) crystal catalysts as well. BiVO4 has been recently explored for water-splitting reactions, given its promise as a material in which charge-separation can occur upon excitation with visible light. The quick recombination of pairs of charged entities (“carriers”) is a disadvantage because carriers must separately partake in reactions that break up water.

In a recent study published in Chemical Engineering Journal, scientists from the Photocatalysis International Research Center at Tokyo University of Science, Japan, together with scientists from Northeast Normal University in China, developed a novel method to improve the charge-separation characteristics of decahedral (ten-sided) BiVO4 crystal catalysts. Prof Terashima, lead scientist in the study, explains, “Recent studies have shown that carriers can be generated and separated at the interfaces between the different faces of certain crystals. In the case of BiVO4, however, the forces that separate carriers are too weak for electron-hole pairs that are generated slightly away from the interfaces. Therefore, carrier separation in BiVO4 decahedrons called for further improvements, which motivated us to carry out this study.”

In the technique they propose, BiVO4 nanocrystals are exposed to what is called “solution plasma discharge,” a highly charged jet of energetic matter that is produced by applying high voltages between two terminals submerged in water. The plasma discharge removes some vanadium (V) atoms from the surface of specific faces of the crystals, leaving vanadium vacancies. These vacancies act as “electron traps” that facilitate the increased separation of carriers. Because these vacancies are in greater number on the eight side faces of the decahedron, electrons are trapped on these faces while holes accumulate on the top and bottom faces. This increased charge separation results in better catalytic performance of the BiVO4 nanocrystals, thereby improving its water splitting performance.

This study represents a novel use of solution plasma discharge to enhance the properties of crystals. Prof Akira Fujishima, co-author of the paper, says, “Our work has inspired us to reconsider other crystals that are apparently ineffective for water splitting. It provides a promising strategy using solution plasma to ‘activate’ them.” The use of solution-plasma discharge has many advantages over using conventional gaseous plasma that make it far more attractive from both technical and economic standpoints. Prof Xintong Zhang from Northeast Normal University, China, remarks, “Unlike gaseous plasma, which has to be generated in closed chambers, solution plasma can be generated in an open reactor at room temperature and in a normal air atmosphere. In addition, by working with crystal powders in a solution, it becomes more convenient to change the parameters of the process, and it is also easier to scale up.”

This study hopefully takes us one step closer to an efficient way of producing hydrogen so that we can finally do without fossil fuels and other energy sources that are harmful to our planet. Further commenting on the promise of this study, Prof Terashima says, “If efficient hydrogen energy can be produced using sunlight and water, two of the most abundant resources on earth, a dream clean society could be realized.”

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Materials provided by Tokyo University of Science. Note: Content may be edited for style and length.

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