Anticancer prodrugs have attracted significant attention from the medical and scientific communities in recent years because of their potential to improve treatment precision while reducing side effects. These drugs are engineered to remain inactive until they are activated at specific sites or under particular physiological conditions within the body, at which point they release their therapeutic effect.

A couple of decades after the discovery of systems that could selectively target DNA, we're starting to see the first therapies based on gene editing. One challenge these developments have faced is safety. While we can make them pretty specific to the gene we want edited, the human genome is very large, and even rare DNA sequences can appear a couple of times by chance.

As a result, all the original gene-editing systems had known rates of what are called off-target effects, in which they simply edit the wrong sequence. This may be a low-probability event, but edit enough cells—and therapies generally have to edit many—and errors become inevitable.

A lot of effort has gone into finding ways to minimize or eliminate off-target edits. In a recent issue of Nature, researchers described modifying the AI protein-folding software AlphaFold to help identify key areas of gene-editing proteins responsible for off-target effects. Those areas were then modified to reduce the problems.

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© Anton Vierietin

A couple of decades after the discovery of systems that could selectively target DNA, we're starting to see the first therapies based on gene editing. One challenge these developments have faced is safety. While we can make them pretty specific to the gene we want edited, the human genome is very large, and even rare DNA sequences can appear a couple of times by chance.

As a result, all the original gene-editing systems had known rates of what are called off-target effects, in which they simply edit the wrong sequence. This may be a low-probability event, but edit enough cells—and therapies generally have to edit many—and errors become inevitable.

A lot of effort has gone into finding ways to minimize or eliminate off-target edits. In a recent issue of Nature, researchers described modifying the AI protein-folding software AlphaFold to help identify key areas of gene-editing proteins responsible for off-target effects. Those areas were then modified to reduce the problems.

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© Anton Vierietin

A new way of converting stubborn plastic waste into high-value chemicals using only water and oxygen has been developed by an international team of scientists.

Sugars are key biomolecules in living organisms, as they form the backbone of DNA and RNA and play a fundamental role in metabolic processes. In theories of the origin of life, sugars are also essential for the synthesis of the first nucleic acids. Despite their importance, one of the major questions in origin-of-life research is how the first sugars formed on Earth, since laboratory experiments show that they do not form in enough quantities under prebiotic conditions. Sugars such as ribose and glucose have previously been detected in meteorite and asteroid samples, suggesting that some of these molecules may have originated in the primordial molecular cloud from which our Solar System formed. However, until now, no sugar had ever been directly detected in the interstellar medium.

An international team led by Centro de Astrobiología (CAB, CSIC-INTA) researcher Izaskun Jiménez-Serra has now identified ¹ the first sugar in interstellar space: erythrulose. This molecule is the only possible four-carbon ketose, and on Earth it is commonly found in raspberries and sunless tanning products. Erythrulose was detected toward the molecular cloud G+0.693−0.027, located near the centre of our Galaxy, the Milky Way. The discovery was made possible by ultra-sensitive, broadband spectroscopic surveys carried out with the 40-m Yebes radio telescope and the 30-m telescope of the Institute for Radio Astronomy in the Millimeter Range (IRAM).

The team identified 12 spectral lines matching the laboratory spectrum of erythrulose measured at the University of the Basque Country. The study also shows that this sugar is at least eight times more abundant than similar three-carbon sugars, none of which were detected in the same region. “This finding was unexpected, as the prevailing view in astrochemistry is that interstellar molecules grow in size through the sequential addition of carbon atoms”, says Izaskun Jimenez-Serra.

Working in collaboration with chemists from the University of Extremadura and Radboud University (the Netherlands), the CAB team discovered that erythrulose can form within interstellar ices from simpler two-carbon alcohols and aldehydes.

Based on the abundance of erythrulose measured in the G+0.693−0.027 molecular cloud, the researchers estimate that between 0.5 and 50 million tonnes of this sugar could have reached Earth’s surface during the Late Heavy Bombardment, which occurred approximately 4.1 to 3.8 billion years ago. The presence of erythrulose in interstellar space therefore provides an alternative source of sugars that may have contributed to the emergence of the first metabolic and replication processes on the early Earth.

“The detection of erythrulose is very exciting because it opens up the possibility of discovering in space other sugars such as ribose, which is part of RNA, and other important molecules for the origin of life,” says Carlos Briones, co-author of the study.

The post Sugar in interstellar space appeared first on Mapping Ignorance.

Enzymes and other biomolecules are often anchored onto solid materials so they can be reused, purified more easily, and made more stable, a strategy biotechnology has relied on since industrial-scale immobilized enzymes first appeared in chemical manufacturing in the mid-twentieth century. Immobilized enzymes today drive processes from food and pharmaceutical production to biosensors and medical diagnostics. Fixing a biomolecule in place, however, is not as simple as gluing it down. The exact spot where it attaches, the direction it faces, and how much freedom it retains to move can all change how well it works. Testing every possible arrangement in the laboratory is slow and costly, which is why computer simulation has become such a valuable complement to experiments.

The Martini force field

One of the main tools for this kind of study is molecular dynamics simulation, which calculates how atoms move over time by applying the basic laws of physics. Simulating every single atom of a protein, its surrounding water, and a supporting material gives rich detail, but is extremely demanding on computing power, especially when many attachment geometries need comparing. A widely used shortcut is coarse-grained modeling, in which small clusters of atoms are grouped into single, simplified particles. This keeps the essential physical behavior of the system while making the calculations far cheaper. The most established coarse-grained approach for biological molecules is the Martini force field, first developed in 2004 to describe fatty, membrane-forming molecules and later extended to proteins and, more recently, to a more accurate third generation of the model. Martini has since become a standard tool for simulating large biological assemblies that would otherwise be out of reach.

Introducing MartiniSurf

A team of researchers now introduces MartiniSurf ¹, an open-source software package that automates the preparation of these coarse-grained simulations for biomolecules attached to surfaces. Building such a system by hand normally involves several separate programs and many manual steps, which makes it hard to reproduce results or compare different setups fairly. MartiniSurf instead combines the whole process into a single, streamlined workflow. Starting from the structure of a protein or a DNA strand, it converts the molecule into its coarse-grained form, builds a model of the supporting surface, positions the molecule in a chosen orientation, adds water and dissolved ions, and produces all the files needed to run the simulation with GROMACS, a molecular dynamics program that has been developed and refined for decades. Because every step is controlled by explicit settings rather than manual adjustments, two researchers using the same settings should obtain the same starting system, making comparisons across studies far more reliable.

Restraining forces or linkers

A central feature of the software is its flexibility in representing how a biomolecule is attached. In one mode, selected regions of the molecule are held near the surface through simple restraining forces, without modeling the physical connector itself. In another mode, an explicit molecular linker is placed between the biomolecule and the surface, so that the linker’s own length and flexibility can influence the simulation. Because the properties of such linkers are known to affect how active and stable an attached enzyme remains, this second option offers a more realistic picture whenever the necessary coarse-grained description of the linker is available.

Variety of supporting surfaces

The supporting surfaces themselves can also be varied widely. The software can generate simple flat reference surfaces or draw on previously developed coarse-grained models of real materials such as graphene, graphite, carbon nanotubes, and agarose-like gels, the type of porous material commonly used to immobilize enzymes in the laboratory. Properties such as surface chemistry, electric charge, particle spacing, and added chemical groups can all be adjusted. Recent studies have shown that surfaces built without care can cause water molecules near the interface to line up in unrealistic, almost frozen patterns, an artifact rather than genuine physical behavior. The software includes options that let users introduce controlled irregularity into the surface to reduce this problem, while staying consistent with the wider Martini modeling framework.

In practice

To demonstrate how the approach works in practice, the study presents examples involving both proteins and DNA. For an enzyme attached to an agarose-like surface, the software reproduces several different attachment arrangements, including a complete system containing the enzyme together with its natural helper molecule and reaction substrate. These examples show how changing the attachment point or adding chemical groups to the surface can be explored systematically, without needing to reconstruct every model from scratch by hand.

The approach is also extended to DNA tethered to a graphene-like surface, comparing an electrically neutral surface with a positively charged one. The coarse-grained simulations reproduce the same general behavior previously reported in much more computationally demanding all-atom studies: the DNA strand remains mostly upright above the neutral surface but bends progressively toward the surface when it carries a positive charge, drawn in by electrostatic attraction. This comparison is not meant to reproduce exact experimental values, but rather to confirm that the automated setup captures the right physical trends, providing a check on the reliability of the workflow.

Reproducibility

Every simulation generated by the software automatically records the settings, software versions, and modeling choices used to build it, so that another researcher can repeat or directly compare a given calculation later. Importantly, the software does not introduce new physical models or new force-field parameters of its own. Instead, it draws on already validated Martini tools and organizes them into a consistent, automated pipeline.

Overall, MartiniSurf addresses a practical bottleneck in computational chemistry rather than proposing a new simulation method. By automating the construction of surface-bound protein and DNA systems, it makes coarse-grained molecular dynamics studies faster to set up, easier to reproduce, and simpler to scale across many attachment geometries. This kind of tool should make it easier to systematically study how surface properties, attachment geometry, and molecular flexibility shape the behavior of immobilized biomolecules, supporting the design of better catalysts, biosensors, and other biotechnology applications.

Author: César Tomé López is a science writer and the editor of Mapping Ignorance

Disclaimer: Parts of this article may have been copied verbatim or almost verbatim from the referenced research paper/s.

The post Overcoming bottlenecks in bio-interface simulations: The MartiniSurf Approach appeared first on Mapping Ignorance.

Researchers have captured the first atomic-level views of human SMUG1, a key enzyme involved in repairing damaged DNA. Every cell in your body is constantly battling damage to its DNA. Now, scientists have captured the first atomic level images of a key human repair enzyme in action, revealing how cells identify and remove some of [...]

A surprising backup pathway allows cells to make a crucial amino acid when their primary machinery fails. For decades, biologists believed cells had only one way to access a molecule they cannot live without. New research suggests they were wrong. Scientists at Montana State University have uncovered a previously unknown cellular survival pathway that allows [...]

In a groundbreaking advance that bridges molecular biology and evolutionary science, researchers at The University of Osaka have unveiled a novel methodology to resurrect ancestral proteins, specifically rhodopsins, enabling direct experimental investigation of these ancient molecules. This work, published in ACS Omega, outlines an innovative sequence reconstruction technique that integrates structural information and attentively accounts for insertions and deletions in protein sequences — a crucial improvement over conventional alignment methods that struggle with highly variable protein domains.

Microbial rhodopsins constitute a diverse family of membrane-embedded proteins with critical biological functions, ranging from ion transport to photoreception. Despite sharing a common structural feature of seven transmembrane helices, these proteins exhibit remarkable functional diversity, largely attributed to extensive variation in their extramembrane domains. Traditional sequence alignment algorithms fall short in tracing their evolutionary trajectories, as they typically do not handle complex insertions and deletions (indels) effectively, especially in variable regions outside of transmembrane segments.

Addressing these challenges, the team led by Haruto Ishikawa and Yasuhisa Mizutani developed ConsistASR, a structure-guided and indel-aware sequence reconstruction pipeline. This approach leverages three-dimensional structural insight to inform sequence alignment, thereby improving the accuracy of reconstructing full-length ancestral rhodopsin proteins. By carefully modeling sequence variability in extramembrane domains, the researchers were able to faithfully infer ancestral sequences that maintain key structural and functional attributes.

Focusing on two subfamilies of microbial rhodopsins—schizorhodopsins and heliorhodopsins—the study successfully resurrected their ancestral versions and expressed these proteins in Escherichia coli. The functional assays revealed that the ancestral schizorhodopsin exhibited light-driven proton pumping activity, consistent with its modern descendants, whereas the ancestral heliorhodopsin lacked ion transport activity, perfectly aligning with the known characteristics of extant heliorhodopsins.

Notably, the ancestral schizorhodopsin protein exhibited the expected spectral properties and stability, signifying correct folding within the bacterial membrane environment. This functional proof of concept not only validates the reconstruction pipeline but also opens a window into the evolutionary dynamics that have shaped rhodopsin diversification over time. The ability to experimentally produce and assay these ancient proteins allows scientists to study evolutionary adaptations at a molecular level with unprecedented precision.

The significance of this work extends beyond just the rhodopsin family. The ConsistASR platform provides a powerful toolkit that can be generalized to reconstruct other ancestral proteins characterized by variable length sequences and complex indels. Such reconstructions are invaluable for evolutionary biology, synthetic biology, and protein engineering, providing empirical insights into how proteins have evolved to acquire new functions and properties.

This innovative integration of sequence, structural, and functional analysis reflects a broader trend in molecular evolution research, where computational biology synergizes with experimental validation to overcome traditional obstacles. As the genomic and structural databases continue to expand, methods like ConsistASR could revolutionize our understanding of protein evolution and functionality by enabling direct interrogation of ancient biomolecules.

The study also tackles a fundamental evolutionary biology question—how functional diversity arises within a protein family while preserving core structural frameworks. By showing that ancestral proteins can be reconstructed in full length and retain distinct biophysical and functional profiles, the research provides direct empirical evidence for evolutionary trajectories that have resulted in contemporary diversity.

Moreover, the expression of these ancestral rhodopsins in bacterial hosts exemplifies how modern synthetic biology tools can resurrect and characterize long-extinct molecular functions. This not only informs evolutionary theory but also offers potential applications in biotechnology, where ancestral proteins might possess unique stability or functional features suitable for industrial or medical purposes.

In practical terms, illuminating the evolutionary path of microbial rhodopsins aids in comprehending microbial adaptation to various ecological niches, given these proteins’ pivotal role in light-driven energy conversion and environmental sensing. Ancestral protein resurrection thus provides a tangible bridge connecting molecular structure, evolution, and ecological function.

The research was supported by the Japan Society for the Promotion of Science and involved meticulous data analysis strategies, combining phylogenetics, structural biology, and bioinformatics. It underscores the multidisciplinary nature of modern biological discovery, illustrating that resolving complex biological problems often requires integrating diverse scientific perspectives and technologies.

Ultimately, this powerful approach reinvigorates the field of ancestral protein research by not only surmounting critical technical obstacles but also by delivering concrete functional data that validate hypotheses about ancient protein behavior. The availability of the ConsistASR workflow to the broader scientific community encourages collaborative exploration of protein evolution and engineering, heralding a new era of experimentally validated molecular paleobiology.

Subject of Research:
Not applicable

Article Title:
Resurrecting Full-length Ancestral Schizorhodopsins and Heliorhodopsins with Structure-guided, Indel-aware Sequence Reconstruction

News Publication Date:
8-Jun-2026

Web References:
https://doi.org/10.1021/acsomega.6c03010

Image Credits:
Haruto Ishikawa

Keywords:
Molecular biology, Biomolecules, Amino acids, Biomolecular structure, Domain organization, Bacterial proteins, Ancient proteins, Membrane proteins, Extracellular domains

Researchers have created a smart wound dressing that can sense when harmful bacteria are present and respond by releasing antibiotics only when needed. Biomedical engineers at Brown University have created a wound dressing that releases antibiotics only when harmful bacteria are detected. In a new study, the team found that the material may quickly eliminate [...]

Tea choice significantly changes kombucha’s chemistry, flavor, and antioxidant potential, with green and oolong teas showing the strongest biological activity. Kombucha has surged in popularity worldwide in recent years, but researchers are looking beyond its flavor to better understand its chemistry and possible health-related properties. A team from the Wrocław University of Environmental and Life [...]

Scientists have uncovered evidence that tiny microbes living inside fish may be helping shape the chemistry of the world’s oceans. The new study, led by former graduate student Anthony Bonacolta at the University of Miami Rosenstiel School of Marine, Atmospheric, and Earth Science, suggests that bacteria in fish intestines may work together with their hosts [...]

For decades, scientists have understood that plants can release volatile organic compounds—essentially airborne chemical signals—to attract the natural enemies of the things that eat them, like caterpillars. What we didn’t know was exactly how a plant translates the physical act of being eaten into a specific, predator-summoning distress signal.

“[One] thing we didn’t know is how the plant detects the caterpillar in the first place,” says Adam Steinbrenner, a biologist at the University of Washington. Now, after years of experimenting with common bean plants in the lab and in the agricultural fields of Oaxaca, Mexico, Steinbrenner’s team pinpointed a single immune receptor that orchestrates its anti-caterpillar defense system.

Drooling caterpillars

When an herbivorous insect like a caterpillar feeds on a plant, it introduces its saliva straight into the plant's damaged tissues. This saliva contains biological clues called HAMPs: herbivore-associated molecular patterns. One of the HAMPs molecules is a peptide called inceptin, and there’s an 11-amino acid fragment of inceptin named In11, as well. Both of them turn out to be a fragment of the ATP synthase found in chloroplasts—basically a piece of one of the plant’s own proteins. As the caterpillar ingests the leaf, its gut enzymes chop up the plant's cellular engines and their pieces, including In11, are regurgitated back onto the leaf’s surface, albeit at extremely small concentrations.

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Life on Earth has a peculiar property – many biological molecules have a handedness, or a “chirality.” DNA twists one way and not the other, and all the rest of life must fit to this reality. In a new paper, researchers say they know why: It all comes down to physics! The answer could change our understanding of life across the universe. Let’s take a look.

© <p>ThoughtCo / Hilary Allison</p>