Scientists Propose Novel Theory on Origin of Genetic Code
Alan Herbert, Scientific Supervisor of the HSE International Laboratory of Bioinformatics, has put forward a new explanation for one of biology's enduring mysteries—the origin of the genetic code. According to his publication in Biology Letters, the contemporary genetic code may have originated from self-organising molecular complexes known as ‘tinkers.’ The author presents this novel hypothesis based on an analysis of secondary DNA structures using the AlphaFold 3 neural network.
The genetic code is the 'alphabet' that underpins the functioning of all living systems on Earth. It dictates the content of an organism's 'instructions' and how they should be interpreted. The contemporary genetic code is composed of codons, each consisting of three nucleotides. These triplets encode amino acids, which are then involved in protein synthesis. Scientists have been studying the genetic code for over 70 years, yet one of the most important questions—how it originated—remains unanswered.
Professor Alan Herbert, Scientific Supervisor at the HSE International Laboratory of Bioinformatics, has put forward a new explanation for the origin of the genetic code. In his view, during evolution, flipons—DNA sequences capable of forming secondary structures—played a key role in the development of the contemporary genetic code.
The classical DNA molecule, as described by Francis Crick and James Watson, is a double helix that twists to the right. However, scientists have discovered alternative DNA structures, including Z-DNA, which twists to the left, as well as three-stranded and four-stranded sequences, and knot-like DNA structures known as i-motifs. These unusual structures arise under specific physiological conditions, and their type depends on the sequence and arrangement of nucleotides within the flipon itself. The simplest flipons are formed from repeating nucleotide sequences, leading to the assumption that such sequences were abundant in the so-called primordial soup.
Maria Poptsova
Using DeepMind's AlphaFold 3 neural network, Alan Herbert analysed the nature of the bonds between flipons and amino acids. 'It turns out that flipons formed from two-nucleotide repeats bind very effectively to simple peptides composed of two-amino acid repeats. It is precisely this correspondence that exists in the contemporary genetic code,' comments Maria Poptsova, Head of the HSE International Laboratory of Bioinformatics.
For example, the cytosine-guanine repeat CGCGCG forms Z-DNA, and the peptide with the arginine-alanine repeat RARARA binds effectively to this sequence. In the contemporary genetic code, the CGC codon corresponds to arginine, while the GCG codon corresponds to alanine. A detailed analysis of spatial interactions reveals that the strongest connection occurs between non-overlapping triplets: CGCGCG binds to RA.
In his publication, Alan Herbert examines numerous examples of the interaction between flipons formed from short repeats and peptides made up of amino acid repeats. It has been found that reactions leading to mutual chain elongation can also occur, especially in the presence of magnesium and zinc, which act as catalysts.
According to the study author, such complexes were once formed by special components—tinkers, as François Jacob called them. In Professor Herbert's work, structures composed of flipons and peptides serve as self-replicating tinkers. Tinkers used DNA as a template for protein synthesis, while proteins, in turn, facilitated the elongation of the DNA helix. As a result, a non-overlapping triplet code emerged: the odd number of bases enables the encoding of sequences from different amino acids, while the nature of bonds between flipons and amino acids dictates that each codon corresponds to only one amino acid.
'The role of flipons as tinkers in the early stages of biological evolution offers a radically new perspective on the origins of life. It is no exaggeration to say that if this theory is experimentally confirmed, our colleague Dr Herbert deserves the Nobel Prize,' explains Poptsova. 'The discovery of interactions between flipons and amino acids, in accordance with the contemporary genetic code table, proves that the emergence of the genetic code is not an accident but a natural outcome of evolution. Nature does not create anything from scratch; it develops new mechanisms using what is already available. Nature acts like a tinkerer who, when needing to quickly create something functional—but not necessarily reliable or durable—grabs whatever is at hand.'
Alan Herbert
'Overall, the proposed scheme does not require a DNA, RNA, or peptide world to explain life’s origins,' writes Alan Herbert in his article. 'Instead, the tinkers described are agents that promote this eventuality. They arise from the simple match between low-complexity nucleotide and simple peptide polymers, using metals to catalyse their initial replication. By spiking the prebiotic soup with copies of themselves, these tinkers quite naturally evolved a non-overlapping, triplet genetic code.'
In addition to advancing our understanding of life's origins, studying tinkers could lead to the development of new technologies, including artificial self-organising systems and self-healing materials. The tinkers’ ability to combine various chemical elements can be used for directed evolution of new biomolecules.
See also:
Mathematicians from HSE Campus in Nizhny Novgorod Prove Existence of Robust Chaos in Complex Systems
Researchers from the International Laboratory of Dynamical Systems and Applications at the HSE Campus in Nizhny Novgorod have developed a theory that enables a mathematical proof of robust chaotic dynamics in networks of interacting elements. This research opens up new possibilities for exploring complex dynamical processes in neuroscience, biology, medicine, chemistry, optics, and other fields. The study findings have been accepted for publication in Physical Review Letters, a leading international journal. The findings are available on arXiv.org.
Large Language Models No Longer Require Powerful Servers
Scientists from Yandex, HSE University, MIT, KAUST, and ISTA have made a breakthrough in optimising LLMs. Yandex Research, in collaboration with leading science and technology universities, has developed a method for rapidly compressing large language models (LLMs) without compromising quality. Now, a smartphone or laptop is enough to work with LLMs—there's no need for expensive servers or high-powered GPUs.
AI to Enable Accurate Modelling of Data Storage System Performance
Researchers at the HSE Faculty of Computer Science have developed a new approach to modelling data storage systems based on generative machine learning models. This approach makes it possible to accurately predict the key performance characteristics of such systems under various conditions. Results have been published in the IEEE Access journal.
Researchers Present the Rating of Ideal Life Partner Traits
An international research team surveyed over 10,000 respondents across 43 countries to examine how closely the ideal image of a romantic partner aligns with the actual partners people choose, and how this alignment shapes their romantic satisfaction. Based on the survey, the researchers compiled two ratings—qualities of an ideal life partner and the most valued traits in actual partners. The results have been published in the Journal of Personality and Social Psychology.
Trend-Watching: Radical Innovations in Creative Industries and Artistic Practices
The rapid development of technology, the adaptation of business processes to new economic realities, and changing audience demands require professionals in the creative industries to keep up with current trends and be flexible in their approach to projects. Between April and May 2025, the Institute for Creative Industries Development (ICID) at the HSE Faculty of Creative Industries conducted a trend study within the creative sector.
From Neural Networks to Stock Markets: Advancing Computer Science Research at HSE University in Nizhny Novgorod
The International Laboratory of Algorithms and Technologies for Network Analysis (LATNA), established in 2011 at HSE University in Nizhny Novgorod, conducts a wide range of fundamental and applied research, including joint projects with large companies: Sberbank, Yandex, and other leaders of the IT industry. The methods developed by the university's researchers not only enrich science, but also make it possible to improve the work of transport companies and conduct medical and genetic research more successfully. HSE News Service discussed work of the laboratory with its head, Professor Valery Kalyagin.
Children with Autism Process Sounds Differently
For the first time, an international team of researchers—including scientists from the HSE Centre for Language and Brain—combined magnetoencephalography and morphometric analysis in a single experiment to study children with Autism Spectrum Disorder (ASD). The study found that children with autism have more difficulty filtering and processing sounds, particularly in the brain region typically responsible for language comprehension. The study has been published in Cerebral Cortex.
HSE Scientists Discover Method to Convert CO₂ into Fuel Without Expensive Reagents
Researchers at HSE MIEM, in collaboration with Chinese scientists, have developed a catalyst that efficiently converts CO₂ into formic acid. Thanks to carbon coating, it remains stable in acidic environments and functions with minimal potassium, contrary to previous beliefs that high concentrations were necessary. This could lower the cost of CO₂ processing and simplify its industrial application—eg in producing fuel for environmentally friendly transportation. The study has been published in Nature Communications.
HSE Scientists Reveal How Staying at Alma Mater Can Affect Early-Career Researchers
Many early-career scientists continue their academic careers at the same university where they studied, a practice known as academic inbreeding. A researcher at the HSE Institute of Education analysed the impact of academic inbreeding on publication activity in the natural sciences and mathematics. The study found that the impact is ambiguous and depends on various factors, including the university's geographical location, its financial resources, and the state of the regional academic employment market. A paper with the study findings has been published in Research Policy.
Group and Shuffle: Researchers at HSE University and AIRI Accelerate Neural Network Fine-Tuning
Researchers at HSE University and the AIRI Institute have proposed a method for quickly fine-tuning neural networks. Their approach involves processing data in groups and then optimally shuffling these groups to improve their interactions. The method outperforms alternatives in image generation and analysis, as well as in fine-tuning text models, all while requiring less memory and training time. The results have been presented at the NeurIPS 2024 Conference.