Polish Academy of Sciences

ESPOO, Finland, May 15, 2024 /PRNewswire/ -- A groundbreaking study, published in the scientific journal Advanced Materials, on 6 May 2024 , led by researchers of VTT Technical Research Centre of Finland, introduces a transformative approach that integrates synthetic biology with advanced machine learning and computational techniques to significantly accelerate the development of new biomaterials. This method reduces the material development timeline from years to mere minutes, promising rapid advancements in medical and industrial applications. "By leveraging the power of AI and synthetic biology, we have managed to fine tune and dramatically speed up the design process of new protein-based materials, allowing for the rapid development of biomaterials with tailored functionalities, achieving what used to take years in just months, with the potential to further reduce this time to minutes," says Pezhman Mohammadi, VTT's Senior Research Scientist and the head of the study. By utilising machine learning algorithms, VTT's research team was able to efficiently sift through thousands of protein structures to pinpoint the most promising candidates for laboratory synthesis. Accelerating high-demand applications, such as smart materials The new high-performance, protein-based biomaterials developed through this method are expected to replace fossil-based materials and bring game-changing properties for high-demand applications, such as medicinal injectables and smart materials to name a few. The research showcased the effective use of hybrid biomimetic and de novo design strategies, combining insights from nature's own design capabilities to create innovative materials from scratch. "Synthetic biology enables production of complicated structures present in nature. Through this approach, we are not only replicating the extraordinary properties of natural materials but also enhancing them to meet specific functional needs, going one step beyond the evolution. The ability to quickly produce materials with customised properties opens new horizons for innovation in biotechnology and materials science," says Pezhman. The publication in Advanced Materials marks a significant milestone in the multidisciplinary field of material biotechnology and showcases the potential of integrated sciences in solving complex global challenges. The research team, including collaborators from VTT, the Polish Academy of Sciences, Temple University, Nanyang Technological University and Aalto University, brings diverse expertise in biology, chemistry, physics, data science, machine learning, AI and computational science. Together, they continue to refine these innovative techniques and expand their applications in the near future. "As we move forward, we envision that the fusion of biotechnology, biorefinery processes, automation, synthetic biology, as well as the pivotal roles of machine learning and AI - all underpinned by biointelligence - will dramatically transform manufacturing. This comprehensive approach enables the rapid, precise design and production of biomaterials, leveraging automation to streamline and scale operations efficiently. Convergence of all these technologies not only accelerates innovation but also enables a radical shift towards more customised, sustainable production methods across various sectors, which offer tailored solutions with minimal environmental impact, revolutionising industry practices," says Pezhman. The study, titled Accelerated Engineering of ELP-based materials through Hybrid Biomimetic-De Novo predictive moledular design and published in Advanced Materials on 6 May, 2024, demonstrates how the collaboration of experts from diverse fields, including synthetic biology, artificial intelligence, molecular dynamics simulation and more, has led to the creation of new biomaterials that are both sustainable and highly functional. Further information VTT Technical Research Centre of Finland Mohammadi Pezhman, Senior Research Scientist [email protected], tel. +358 401637835 Further information on VTT: Paula Bergqvist, Senior Specialist, Communications +358 20 722 5161, [email protected] This information was brought to you by Cision The following files are available for download: SOURCE VTT Info

Cryptocurrency is usually 'mined' through the blockchain by asking a computer to perform a complicated mathematical problem in exchange for tokens of cryptocurrency. But now a team of chemists have repurposed this process, asking computers to instead generate the largest network ever created of chemical reactions which may have given rise to prebiotic molecules on early Earth. Cryptocurrency is usually "mined" through the blockchain by asking a computer to perform a complicated mathematical problem in exchange for tokens of cryptocurrency. But in research appearing in the journal Chem on January 24, a team of chemists have repurposed this process, asking computers to instead generate the largest network ever created of chemical reactions which may have given rise to prebiotic molecules on early Earth. This work indicates that at least some primitive forms of metabolism might have emerged without the involvement of enzymes, and it shows the potential to use blockchain to solve problems outside the financial sector that would otherwise require the use of expensive, hard to access supercomputers. "At this point we can say we exhaustively looked for every possible combination of chemical reactivity that scientists believe to had been operative on primitive Earth," says senior author Bartosz A. Grzybowski of the Korea Institute for Basic Science and the Polish Academy of Sciences. To generate this network, the researchers chose a set of starting molecules likely present on early Earth, including water, methane, and ammonia, and set rules about which reactions could occur between different types of molecules. They then translated this information into a language understandable by computers and used the blockchain to calculate which reactions would occur over multiple expansions of a giant reaction network. "The computer takes the primordial molecules and the accepted prebiotic chemistries. We coded it into the machine, and then we released it onto the world," says Grzybowski. Grzybowski's team worked with chemists and computer-specialists at Allchemy, a company that uses AI for chemical synthesis planning, to generate the network using Golem, a platform that orchestrates portions of the calculations over hundreds of computers across the world, which receive cryptocurrency in exchange for computing time. The resulting network, termed NOEL for the Network of Early Life, started off with over 11 billion reactions, which the team narrowed down to 4.9 billion plausible reactions. NOEL contains parts of well-known metabolic pathways like glycolysis, close mimics of the Krebs cycle, which organisms use to generate energy, and syntheses of 128 simple biotic molecules like sugars and amino acids. Curiously, of the 4.9 billion reactions generated, only hundreds of reaction cycles could be called "self-replicating," which means that the molecules produce additional copies of themselves. Self-replication has been postulated to be central to the emergence of life, but the vast majority of its known manifestations require complex macromolecules like enzymes. "Our results mean that with only small molecules present, self-amplification is a rare event. I don't think that this type of self-replication was operative on primitive earth, before larger molecular structures were somehow formed," says Grzybowski. "We see emergence of primitive metabolism, but we don't see self-replication, so maybe self-replication appeared later in evolution." "If you asked me two years ago, I'd be thinking we'd need years for this type of work," says Grzybowski. "But for a fraction of the cost, in two or three months, we finished a task of 10 billion reactions, 100k times bigger than we did previously." This work not only advances what we know about early prebiotic chemistry, but it also demonstrates how science can be made more accessible to researchers at smaller universities and institutions. "Our system of education is based on elite universities mostly in the western world. It's very hard for the developing world to even compete with these universities because they don't have access to supercomputers," says Grzybowski. "But if you can distribute computing in this way for a fraction of the cost, you can give other people opportunities to play." While the network generated in this work was performed on hundreds of computers around the world, Grzybowski suggests that this method can be used at institutions without having to pay out cryptocurrency tokens to the computers performing the calculations. "With a platform like Golem you can connect your institution's network and harness the entire idle power of its computers to perform calculations," says Grzybowski. "You could create this computing infrastructure without any capital expenditure." Grzybowski hopes that repurposing the blockchain in this way can revolutionize the way we perform large scale calculations across the world and change how we see the value of cryptocurrency. "I hope people in computer science can figure out how can we tokenize cryptocurrencies in some way that can benefit global science," says Grzybowski. "Maybe society could be happier about using cryptocurrencies, if you could tell people that in the process we could discover new laws of biology or some new cancer drug," says Grzybowski.

Researchers have used fossil evidence to engineer a soft robotic replica of pleurocystitids, a marine organism that existed nearly 450 million years ago and is believed to be one of the first echinoderms capable of movement using a muscular stem. Researchers in the Department of Mechanical Engineering at Carnegie Mellon University, in collaboration with paleontologists from Spain and Poland, used fossil evidence to engineer a soft robotic replica of pleurocystitid, a marine organism that existed nearly 450 million years ago and is believed to be one of the first echinoderms capable of movement using a muscular stem. Published today in The Proceedings of the National Academy of Science (PNAS), the research seeks to broaden modern perspective of animal design and movement by introducing a new a field of study -- Paleobionics -- aimed at using Softbotics, robotics with flexible electronics and soft materials, to understand the biomechanical factors that drove evolution using extinct organisms. "Softbotics is another approach to inform science using soft materials to construct flexible robot limbs and appendages. Many fundamental principles of biology and nature can only fully be explained if we look back at the evolutionary timeline of how animals evolved. We are building robot analogues to study how locomotion has changed," said Carmel Majidi, lead author and Professor of Mechanical Engineering at Carnegie Mellon University. With humans' time on earth representing only 0.007% of the planet's history, the modern-day animal kingdom that influences understanding of evolution and inspires today's mechanical systems is only a fraction of all creatures that have existed through history. Using fossil evidence to guide their design and a combination of 3D printed elements and polymers to mimic the flexible columnar structure of the moving appendage, the team demonstrated that pleurocystitids were likely able to move over the sea bottom by means of a muscular stem that pushed the animal forward. Despite the absence of a current day analogue (echinoderms have since evolved to include modern day starfish and sea urchins), pleurocystitids have been of interest to paleontologists due to their pivotal role in echinoderm evolution. The team determined that wide sweeping movements were likely the most effective motion and that increasing the length of the stem significantly increased the animals' speed without forcing it to exert more energy. "Researchers in the bio-inspired robotics community need to pick and choose important features worth adopting from organisms," explained Richard Desatnik, PhD candidate and co-first author. "Essentially, we have to decide on good locomotion strategies to get our robots moving. For example, would a starfish robot really need to use 5 limbs for locomotion or can we find a better strategy?" added Zach Patterson, CMU alumnus and co-first author. Now that the team has demonstrated that they can use Softbotics to engineer extinct organisms, they hope to explore other animals, like the first organism that could travel from sea to land -- something that can't be studied in the same way using conventional robot hardware. "Bringing a new life to something that existed nearly 500 million years ago is exciting in and of itself, but what really excites us about this breakthrough is how much we will be able to learn from it," said Phil LeDuc, co-author, and Professor of Mechanical Engineering at Carnegie Mellon University. "We aren't just looking at fossils in the ground, we are trying to better understand life through working with amazing paleontologists." Additional collaborators include Przemyslaw Gorzelak, Institute of Paleobiology, Polish Academy of Sciences, and Samuel Zamora, The Geological and Mining Institute of Spain.