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Results for “DNA descriptors”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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5 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

GMFOLD: Subgraph matching for high-throughput DNA-aptamer secondary structure classification and machine learning interpretability

Aptamers are oligonucleotide receptors that bind to their targets with high affinity. Here, we consider aptamers comprised of single-stranded DNA that undergo target-binding-induced conformational changes, giving rise to unique secondary and tertiary structures. Given a specific aptamer primary sequence, there are well-established computational tools (notably mfold) to predict the secondary structure via free energy minimization algorithms. While mfold generates secondary structures for individual sequences, there is a need for a high-throughput process whereby thousands of DNA structures can be predicted in real-time for use in an interactive setting, when combined with aptamer selections that generate candidate pools that are too large to be experimentally interrogated. We developed a new Python code for high-throughput aptamer secondary structure determination (GMfold). GMfold uses subgraph matching methods to group aptamer candidates by secondary structure similarities. We also improve an open-source code, SeqFold, to incorporate subgraph matching concepts. We represent each secondary structure as a lowest-energy bipartite subgraph matching of the DNA graph to itself. These new tools enable thousands of DNA sequences to be compared based on their secondary structures, using machine-learning algorithms. This process is advantageous when analyzing sequences that arise from aptamer selections via systematic evolution of ligands by exponential enrichment (SELEX). This work is a building block for future machine-learning-informed DNA-aptamer selection processes to identify aptamers with improved target affinity and selectivity and advance aptamer biosensors and therapeutics.

Aptamer↗
NASA NTRS1992

Numerical classification of coding sequences

DNA sequences coding for protein may be represented by counts of nucleotides or codons. A complete reading frame may be abbreviated by its base count, e.g. A76C158G121T74, or with the corresponding codon table, e.g. (AAA)0(AAC)1(AAG)9 ... (TTT)0. We propose that these numerical designations be used to augment current methods of sequence annotation. Because base counts and codon tables do not require revision as knowledge of function evolves, they are well-suited to act as cross-references, for example to identify redundant GenBank entries. These descriptors may be compared, in place of DNA sequences, to extract homologous genes from large databases. This approach permits rapid searching with good selectivity.

Non-NASA Center↗
DOE OSTI2023

Quantum biological insights into CRISPR-Cas9 sgRNA efficiency from explainable-AI driven feature engineering

Abstract CRISPR-Cas9 tools have transformed genetic manipulation capabilities in the laboratory. Empirical rules-of-thumb have been developed for only a narrow range of model organisms, and mechanistic underpinnings for sgRNA efficiency remain poorly understood. This work establishes a novel feature set and new public resource, produced with quantum chemical tensors, for interpreting and predicting sgRNA efficiency. Feature engineering for sgRNA efficiency is performed using an explainable-artificial intelligence model: iterative Random Forest (iRF). By encoding quantitative attributes of position-specific sequences for Escherichia coli sgRNAs, we identify important traits for sgRNA design in bacterial species. Additionally, we show that expanding positional encoding to quantum descriptors of base-pair, dimer, trimer, and tetramer sequences captures intricate interactions in local and neighboring nucleotides of the target DNA. These features highlight variation in CRISPR-Cas9 sgRNA dynamics between E. coli and H. sapiens genomes. These novel encodings of sgRNAs enhance our understanding of the elaborate quantum biological processes involved in CRISPR-Cas9 machinery.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2012

Calculation of the Frequency Distribution of the Energy Deposition in DNA Volumes by Heavy Ions

Radiation quality effects are largely determined by energy deposition in small volumes of characteristic sizes less than 10 nm representative of short-segments of DNA, the DNA nucleosome, or molecules initiating oxidative stress in the nucleus, mitochondria, or extra-cellular matrix. On this scale, qualitatively distinct types of molecular damage are possible for high linear energy transfer (LET) radiation such as heavy ions compared to low LET radiation. Unique types of DNA lesions or oxidative damages are the likely outcome of the energy deposition. The frequency distribution for energy imparted to 1-20 nm targets per unit dose or particle fluence is a useful descriptor and can be evaluated as a function of impact parameter from an ions track. In this work, the simulation of 1-Gy irradiation of a cubic volume of 5 micron by: 1) 450 (1)H(+) ions, 300 MeV; 2) 10 (12)C(6+) ions, 290 MeV/amu and 3) (56)Fe(26+) ions, 1000 MeV/amu was done with the Monte-Carlo simulation code RITRACKS. Cylindrical targets are generated in the irradiated volume, with random orientation. The frequency distribution curves of the energy deposited in the targets is obtained. For small targets (i.e. <25 nm size), the probability of an ion to hit a target is very small; therefore a large number of tracks and targets as well as a large number of histories are necessary to obtain statistically significant results. This simulation is very time-consuming and is difficult to perform by using the original version of RITRACKS. Consequently, the code RITRACKS was adapted to use multiple CPU on a workstation or on a computer cluster. To validate the simulation results, similar calculations were performed using targets with fixed position and orientation, for which experimental data are available [5]. Since the probability of single- and double-strand breaks in DNA as function of energy deposited is well know, the results that were obtained can be used to estimate the yield of DSB, and can be extended to include other targeted or non-target effects.

Plante, Ianik↗
DOE OSTI2022

The impact of G-quadruplex dynamics on inter-tetrad electronic couplings: a hybrid computational study

The G-quadruplex is a fascinating nucleic acid motif with implications in biology, medicine, and nanotechnologies. G-quadruplexes can form in the telomeres at the edges of chromosomes and in other guanine-rich regions of the genome. They can also be engineered for exploitation as biological materials for nanodevices. Their higher stiffness and higher charge transfer rates make them better candidates in nanodevices than duplex DNA. For the development of molecular nanowires, it is important to optimize electron transport along the wire axis. One powerful basis to do so is by manipulating the structure, based on known effects that structural changes have on electron transport. Here, for this work, we investigate such effects, by a combination of classical simulations of the structure and dynamics and quantum calculations of electronic couplings. We find that this structure–function relationship is complex. A single helix shape parameter alone does not embody such complexity, but rather a combination of distances and angles between stacked bases influences charge transfer efficiency. By analyzing linear combinations of shape descriptors for different topologies, we identify the structural features that most affect charge transfer efficiency. We discuss the transferability of the proposed model and the limiting effects of inherent flexibility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗