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Powering DNA strand-displacement reactions with a continuous flow reactor
Living systems require a sustained supply of energy and nutrients to survive. These nutrients are ingested, transformed into low-energy waste products, and excreted. In contrast, synthetic DNA strand-displacement reactions typically run within closed systems provided with a finite initial supply of reactants. Once the reactants are consumed, all net reactions halt and the system ceases to function. In the study, we ran DNA strand-displacement reactions in a continuous flow reactor, infusing fresh reactants and withdrawing waste, enabling the system to dynamically update its outputs in response to changing inputs. Running DNA strand-displacement reactions inside of continuous flow reactors allows the system to be re-used for multiple rounds of computation, which could enable the execution of more elaborate information processing tasks, including single-rail negation and sequential logic circuits.
Computer simulation of initial events in the biochemical mechanisms of DNA damage
Understanding the systematic and quantitative correlation between the physical events of energy deposition by ionizing radiation and the ensuing chemical and biochemical processes leading to DNA damage is one of the goals in radiation research. Significant progress has been made toward achieving the stated goal by using theoretical modeling techniques. These techniques are strongly dependent on computer simulation procedures. A review of such techniques with details of various stages of simulation development, including a comparison with available experimental data, is presented in this article.
AlphaBeta: computational inference of epimutation rates and spectra from high-throughput DNA methylation data in plants
Stochastic changes in DNA methylation (i.e., spontaneous epimutations) contribute to methylome diversity in plants. Here, we describe AlphaBeta, a computational method for estimating the precise rate of such stochastic events using pedigree-based DNA methylation data as input. We demonstrate how AlphaBeta can be employed to study transgenerationally heritable epimutations in clonal or sexually derived mutation accumulation lines, as well as somatic epimutations in long-lived perennials. Application of our method to published and new data reveals that spontaneous epimutations accumulate neutrally at the genome-wide scale, originate mainly during somatic development and that they can be used as a molecular clock for age-dating trees.
Structure of an anti-HIV-1 hammerhead ribozyme complex with a 17-mer DNA substrate analog of HIV-1 gag RNA and a mechanism for the cleavage reaction: 750 MHz NMR and computer experiments
The structure of an anti-HIV-1 ribozyme-DNA abortive substrate complex was investigated by 750 MHz NMR and computer modeling experiments. The ribozyme was a chimeric molecule with 30 residues-18 DNA nucleotides, and 12 RNA residues in the conserved core. The DNA substrate analog had 17 residues. The chimeric ribozyme and the DNA substrate formed a shortened ribozyme-abortive substrate complex of 47 nucleotides with two DNA stems (stems I and III) and a loop consisting of the conserved core residues. Circular dichroism spectra showed that the DNA stems assume A-family conformation at the NMR concentration and a temperature of 15 degrees C, contrary to the conventional wisdom that DNA duplexes in aqueous solution populate entirely in the B-form. It is proposed that the A-family RNA residues at the core expand the A-family initiated at the core into the DNA stems because of the large free energy requirement for the formation of A/B junctions. Assignments of the base H8/H6 protons and H1' of the 47 residues were made by a NOESY walk. In addition to the methyl groups of all T's, the imino resonances of stems I and III and AH2's were assigned from appropriate NOESY walks. The extracted NMR data along with available crystallographic data, were used to derive a structural model of the complex. Stems I and III of the final model displayed a remarkable similarity to the A form of DNA; in stem III, a GC base pair was found to be moving into the floor of the minor groove defined by flanking AT pairs; data suggest the formation of a buckled rhombic structure with the adjacent pair; in addition, the base pair at the interface of stem III and the loop region displayed deformed geometry. The loop with the catalytic core, and the immediate region of the stems displayed conformational multiplicity within the NMR time scale. A catalytic mechanism for ribozyme action based on the derived structure, and consistent with biochemical data in the literature, is proposed. The complex between the anti HIV-1 gag ribozyme and its abortive DNA substrate manifests in the detection of a continuous track of A.T base pairs; this suggests that the interaction between the ribozyme and its DNA substrate is stronger than the one observed in the case of the free ribozyme where the bases in stem I and stem III regions interact strongly with the ribozyme core region (Sarma, R. H., et al. FEBS Letters 375, 317-23, 1995). The complex formation provides certain guidelines in the design of suitable therapeutic ribozymes. If the residues in the ribozyme stem regions interact with the conserved core, it may either prevent or interfere with the formation of a catalytically active tertiary structure.
Combinatorial-Entropy-Driven Aggregation in DNA-Grafted Nanoparticles
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The 'Biologically-Inspired Computing' Column
The field of Biology changed dramatically in 1953, with the determination by Francis Crick and James Dewey Watson of the double helix structure of DNA. This discovery changed Biology for ever, allowing the sequencing of the human genome, and the emergence of a "new Biology" focused on DNA, genes, proteins, data, and search. Computational Biology and Bioinformatics heavily rely on computing to facilitate research into life and development. Simultaneously, an understanding of the biology of living organisms indicates a parallel with computing systems: molecules in living cells interact, grow, and transform according to the "program" dictated by DNA. Moreover, paradigms of Computing are emerging based on modelling and developing computer-based systems exploiting ideas that are observed in nature. This includes building into computer systems self-management and self-governance mechanisms that are inspired by the human body's autonomic nervous system, modelling evolutionary systems analogous to colonies of ants or other insects, and developing highly-efficient and highly-complex distributed systems from large numbers of (often quite simple) largely homogeneous components to reflect the behaviour of flocks of birds, swarms of bees, herds of animals, or schools of fish. This new field of "Biologically-Inspired Computing", often known in other incarnations by other names, such as: Autonomic Computing, Pervasive Computing, Organic Computing, Biomimetics, and Artificial Life, amongst others, is poised at the intersection of Computer Science, Engineering, Mathematics, and the Life Sciences. Successes have been reported in the fields of drug discovery, data communications, computer animation, control and command, exploration systems for space, undersea, and harsh environments, to name but a few, and augur much promise for future progress.
Plant Bioengineering Atlas: A Knowledge Graph of Genes, DNA Constructs, and Plant Traits.
Plant bioengineering has generated tens of thousands of genotype-to-phenotype relationships, but this knowledge remains fragmented across narrative literature and difficult to use computationally. Inconsistent descriptions of DNA constructs, host species, and traits, including variable species names, omitted regulatory elements, and inconsistent gene symbols, impede data reuse, comparative analysis, and design-build-test-learn cycles. Here, we present the Plant Bioengineering Atlas, a literature-mined, ontology-grounded knowledge base assembled using an artificial intelligence (AI)-aided extraction pipeline. A large language model parsed open-access primary research articles to generate structured, provenance-anchored records of engineered genes, modification types, promoter-gene-terminator constructs, host species, target traits, and reported phenotypes, with every record traceable to its source. The current release contains 14,358 curated records encompassing 6,998 distinct genes across 436 plant species from 6,452 papers published between 2000 and 2026. Corpus analysis reveals that experiments are concentrated in a small group of model and crop species, disease and pathogen resistance is the most frequently engineered trait class, and constitutive regulatory parts (particularly the CaMV 35S promoter and NOS terminator) remain pervasive. Two in five records omit one or both flanking regulatory elements (i.e., promoter and terminator), while only 23.4% describe cassettes in which both elements resolve to named part classes, exposing a systematic reproducibility gap. We organize these data into a knowledge graph linking genes, constructs, species, and traits; provide access through an interactive web portal; and propose an AI-compatible documentation standard for AI-ready reporting. The Plant Bioengineering Atlas provides a foundation for data-driven hypothesis generation and AI-aided plant biodesign.
Mechanism of DNA origami folding elucidated by mesoscopic simulations
Abstract Many experimental and computational efforts have sought to understand DNA origami folding, but the time and length scales of this process pose significant challenges. Here, we present a mesoscopic model that uses a switchable force field to capture the behavior of single- and double-stranded DNA motifs and transitions between them, allowing us to simulate the folding of DNA origami up to several kilobases in size. Brownian dynamics simulations of small structures reveal a hierarchical folding process involving zipping into a partially folded precursor followed by crystallization into the final structure. We elucidate the effects of various design choices on folding order and kinetics. Larger structures are found to exhibit heterogeneous staple incorporation kinetics and frequent trapping in metastable states, as opposed to more accessible structures which exhibit first-order kinetics and virtually defect-free folding. This model opens an avenue to better understand and design DNA nanostructures for improved yield and folding performance.
DNA Recombinase Proteins, their Function and Structure in the Active Form, a Computational Study
Homologous recombination is a crucial sequence of reactions in all cells for the repair of double strand DNA (dsDNA) breaks. While it was traditionally considered as a means for generating genetic diversity, it is now known to be essential for restart of collapsed replication forks that have met a lesion on the DNA template (Cox et al., 2000). The central stage of this process requires the presence of the DNA recombinase protein, RecA in bacteria, RadA in archaea, or Rad51 in eukaryotes, which leads to an ATP-mediated DNA strand-exchange process. Despite many years of intense study, some aspects of the biochemical mechanism, and structure of the active form of recombinase proteins are not well understood. Our theoretical study is an attempt to shed light on the main structural and mechanistic issues encountered on the RecA of the e-coli, the RecA of the extremely radio resistant Deinococcus Radiodurans (promoting an inverse DNA strand-exchange repair), and the homolog human Rad51. The conformational changes are analyzed for the naked enzymes, and when they are linked to ATP and ADP. The average structures are determined over 2ns time scale of Langevian dynamics using a collision frequency of 1.0 ps(sup -1). The systems are inserted in an octahedron periodic box with a 10 Angstrom buffer of water molecules explicitly described by the TIP3P model. The corresponding binding free energies are calculated in an implicit solvent using the Poisson-Boltzmann solvent accessible surface area, MM-PBSA model. The role of the ATP is not only in stabilizing the interaction RecA-DNA, but its hydrolysis is required to allow the DNA strand-exchange to proceed. Furthermore, we extended our study, using the hybrid QM/MM method, on the mechanism of this chemical process. All the calculations were performed using the commercial code Amber 9.
Computational Model of the Modulation of Gene Expression Following DNA Damage
High linear energy transfer (LET) radiation, such as heavy ions or neutrons, has an increased biological effectiveness compared to X rays for gene mutation, genomic instability, and carcinogenesis. In the traditional paradigm, mutations or chromosomal aberrations are causative of late effects. However, in recent years experimental evidence has demonstrated the important role of the description of the modification of gene expression by radiation in understanding the mechanisms of radiation action. In this report, approaches are discussed to the mathematical description of mRNA and protein expression kinetics following DNA damage. Several hypotheses for models of radiation modulation of protein expression are discussed including possible non-linear processes that evolve from the linear dose responses that follow the initial DNA damage produced by radiation.
A computer aided thermodynamic approach for predicting the formation of Z-DNA in naturally occurring sequences
The ease with which a particular DNA segment adopts the left-handed Z-conformation depends largely on the sequence and on the degree of negative supercoiling to which it is subjected. We describe a computer program (Z-hunt) that is designed to search long sequences of naturally occurring DNA and retrieve those nucleotide combinations of up to 24 bp in length which show a strong propensity for Z-DNA formation. Incorporated into Z-hunt is a statistical mechanical model based on empirically determined energetic parameters for the B to Z transition accumulated to date. The Z-forming potential of a sequence is assessed by ranking its behavior as a function of negative superhelicity relative to the behavior of similar sized randomly generated nucleotide sequences assembled from over 80,000 combinations. The program makes it possible to compare directly the Z-forming potential of sequences with different base compositions and different sequence lengths. Using Z-hunt, we have analyzed the DNA sequences of the bacteriophage phi X174, plasmid pBR322, the animal virus SV40 and the replicative form of the eukaryotic adenovirus-2. The results are compared with those previously obtained by others from experiments designed to locate Z-DNA forming regions in these sequences using probes which show specificity for the left-handed DNA conformation.
Space Radiation Effects on Human Cells: Modeling DNA Breakage, DNA Damage Foci Distribution, Chromosomal Aberrations and Tissue Effects
Future long-tem space travel will face challenges from radiation concerns as the space environment poses health risk to humans in space from radiations with high biological efficiency and adverse post-flight long-term effects. Solar particles events may dramatically affect the crew performance, while Galactic Cosmic Rays will induce a chronic exposure to high-linear-energy-transfer (LET) particles. These types of radiation, not present on the ground level, can increase the probability of a fatal cancer later in astronaut life. No feasible shielding is possible from radiation in space, especially for the heavy ion component, as suggested solutions will require a dramatic increase in the mass of the mission. Our research group focuses on fundamental research and strategic analysis leading to better shielding design and to better understanding of the biological mechanisms of radiation damage. We present our recent effort to model DNA damage and tissue damage using computational models based on the physics of heavy ion radiation, DNA structure and DNA damage and repair in human cells. Our particular area of expertise include the clustered DNA damage from high-LET radiation, the visualization of DSBs (DNA double strand breaks) via DNA damage foci, image analysis and the statistics of the foci for different experimental situations, chromosomal aberration formation through DSB misrepair, the kinetics of DSB repair leading to a model-derived spectrum of chromosomal aberrations, and, finally, the simulation of human tissue and the pattern of apoptotic cell damage. This compendium of theoretical and experimental data sheds light on the complex nature of radiation interacting with human DNA, cells and tissues, which can lead to mutagenesis and carcinogenesis later in human life after the space mission.
Biological Information Signal Processor
Biological Information Signal Processor (BISP) is computing system analyzing data on deoxyribonucleic acid (DNA) sequences for molecular genetic analysis. Includes coprocessors, specialized microprocessors complementing present and future computers by performing rapidly most-time-consuming DNA-sequence-analyzing functions, establishing relationships (alignments) between both global sequences and defining patterns in multiple sequences. Also includes state-of-art software and data-base systems on both conventional and parallel computer systems to augment analytical abilities of developmental coprocessors.
Coarse-Grained Simulations for the Characterization and Optimization of Hybrid Protein–DNA Nanostructures
We present here the combination of experimental and computational modeling tools for the design and characterization of protein–DNA hybrid nanostructures. Our work incorporates several features in the design of these nanostructures: (1) modeling of the protein–DNA linker identity and length; (2) optimizing the design of protein–DNA cages to account for mechanical stresses; (3) probing the incorporation efficiency of protein–DNA conjugates into DNA nanostructures. The modeling tools were experimentally validated using structural characterization methods like cryo-TEM and AFM. Our method can be used for fitting low-resolution electron density maps when structural insights cannot be deciphered from experiments, as well as enable in-silico validation of nanostructured systems before their experimental realization. Finally, these tools will facilitate the design of complex hybrid protein–DNA nanostructures that seamlessly integrate the two different biomolecules.
Long-range correlation properties of coding and noncoding DNA sequences: GenBank analysis
An open question in computational molecular biology is whether long-range correlations are present in both coding and noncoding DNA or only in the latter. To answer this question, we consider all 33301 coding and all 29453 noncoding eukaryotic sequences--each of length larger than 512 base pairs (bp)--in the present release of the GenBank to dtermine whether there is any statistically significant distinction in their long-range correlation properties. Standard fast Fourier transform (FFT) analysis indicates that coding sequences have practically no correlations in the range from 10 bp to 100 bp (spectral exponent beta=0.00 +/- 0.04, where the uncertainty is two standard deviations). In contrast, for noncoding sequences, the average value of the spectral exponent beta is positive (0.16 +/- 0.05) which unambiguously shows the presence of long-range correlations. We also separately analyze the 874 coding and the 1157 noncoding sequences that have more than 4096 bp and find a larger region of power-law behavior. We calculate the probability that these two data sets (coding and noncoding) were drawn from the same distribution and we find that it is less than 10(-10). We obtain independent confirmation of these findings using the method of detrended fluctuation analysis (DFA), which is designed to treat sequences with statistical heterogeneity, such as DNA's known mosaic structure ("patchiness") arising from the nonstationarity of nucleotide concentration. The near-perfect agreement between the two independent analysis methods, FFT and DFA, increases the confidence in the reliability of our conclusion.
Computational Study on Full-length Human Ku70 with Double Stranded DNA: Dynamics, Interactions and Functional Implications
The Ku70/80 heterodimer is the first repair protein in the initial binding of double-strand break (DSB) ends following DNA damage, and is a component of nonhomologous end joining repair, the primary pathway for DSB repair in mammalian cells. In this study we constructed a full-length human Ku70 structure based on its crystal structure, and performed 20 ns conventional molecular dynamic (CMD) simulations on this protein and several other complexes with short DNA duplexes of different sequences. The trajectories of these simulations indicated that, without the topological support of Ku80, the residues in the bridge and C-terminal arm of Ku70 are more flexible than other experimentally identified domains. We studied the two missing loops in the crystal structure and predicted that they are also very flexible. Simulations revealed that they make an important contribution to the Ku70 interaction with DNA. Dislocation of the previously studied SAP domain was observed in several systems, implying its role in DNA binding. Targeted molecular dynamic (TMD) simulation was also performed for one system with a far-away 14bp DNA duplex. The TMD trajectory and energetic analysis disclosed detailed interactions of the DNA-binding residues during the DNA dislocation, and revealed a possible conformational transition for a DSB end when encountering Ku70 in solution. Compared to experimentally based analysis, this study identified more detailed interactions between DNA and Ku70. Free energy analysis indicated Ku70 alone is able to bind DNA with relatively high affinity, with consistent contributions from various domains of Ku70 in different systems. The functional implications of these domains in the processes of Ku heterodimerization and DNA damage recognition and repair can be characterized in detail based upon this analysis.
Quantum-parallel vectorized data encodings and computations on trapped-ion and transmon QPUs
Compact data representations in quantum systems are crucial for the development of quantum algorithms for data analysis. In this study, we present two innovative data encoding techniques, known as QCrank and QBArt, which exhibit significant quantum parallelism via uniformly controlled rotation gates. The QCrank method encodes a series of real-valued data as rotations on data qubits, resulting in increased storage capacity. On the other hand, QBArt directly incorporates a binary representation of the data within the computational basis, requiring fewer quantum measurements and enabling well-established arithmetic operations on binary data. We showcase various applications of the proposed encoding methods for various data types. Notably, we demonstrate quantum algorithms for tasks such as DNA pattern matching, Hamming weight computation, complex value conjugation, and the retrieval of a binary image with 384 pixels, all executed on the Quantinuum trapped-ion QPU. Furthermore, we employ several cloud-accessible QPUs, including those from IBMQ and IonQ, to conduct supplementary benchmarking experiments.