Search NASA⌕ Search

SEARCH · Search NASA

Results for “DNA computation”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Final Report

This final progress report describes the development of the CANDO Software package at ThirdLaw Technologies LLC (TLT) towards a software platform that will be used by its subsidiary company ThirdLaw Molecular LLC (TLM) for the development of therapeutic Spiroligomer™ molecules. ThirdLaw Molecular LLC is 95% owned by ThirdLaw Technologies LLC. TLM is developing a new therapeutics platform based on Spiroligomer™ molecules and is currently funded by the Department of Defense, Defense Threat Reduction Agency (DOD/DTRA W15QKN209C004). Spiroligomer™ molecules are complex, highly-preorganized macromolecules with programmable three-dimensional shapes. Spiroligomer™ molecules are currently synthesized by TLM in the form of large (>880,000 member) DNA-encoded libraries and screened against dangerous bacteria and viruses as part of the DOD/DTRA project. The CANDO software package is being developed to enable the computational design of Spiroligomer™ molecules for the development of therapeutic and diagnostic molecules. Towards this end, over the period of the grant we implemented software algorithms and a user interface within CANDO to enable the computational design of Spiroligomer™ molecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1991

Nucleic acid and protein synthesis during lateral root initiation in Marsilea quadrifolia (Marsileaceae)

The pattern of DNA, RNA, and protein synthesis during lateral root initiation in Marsilea quadrifolia L. was monitored by autoradiography of incorporated of 3H-thymidine, 3H-uridine, and 3H-leucine, respectively. DNA synthesis was associated with the enlargement of the lateral root initial prior to its division. Consistent with histological studies, derivatives of the lateral root initial as well as the cells of the adjacent inner cortex and pericycle of the parent root also continued to synthesize DNA. RNA and protein synthetic activities were found to be higher in the lateral root initials than in the endodermal initials of the same longitudinal layer. The data suggest a role for nucleic acid and protein synthesis during cytodifferentiation of a potential endodermal cell into a lateral root initial.

Non-NASA Center↗
NASA NTRS2015

Prototype Biology-Based Radiation Risk Module Project

Biological effects of space radiation and risk mitigation are strategic knowledge gaps for the Evolvable Mars Campaign. The current epidemiology-based NASA Space Cancer Risk (NSCR) model contains large uncertainties (HAT #6.5a) due to lack of information on the radiobiology of galactic cosmic rays (GCR) and lack of human data. The use of experimental models that most accurately replicate the response of human tissues is critical for precision in risk projections. Our proposed study will compare DNA damage, histological, and cell kinetic parameters after irradiation in normal 2D human cells versus 3D tissue models, and it will use a multi-scale computational model (CHASTE) to investigate various biological processes that may contribute to carcinogenesis, including radiation-induced cellular signaling pathways. This cross-disciplinary work, with biological validation of an evolvable mathematical computational model, will help reduce uncertainties within NSCR and aid risk mitigation for radiation-induced carcinogenesis.

Terrier, Douglas↗
DOE OSTI2015

Ultraviolet radiation therapy and UVR dose models

Ultraviolet radiation (UVR) has been an effective treatment for a number of chronic skin disorders, and its ability to alleviate these conditions has been well documented. Although nonionizing, exposure to ultraviolet (UV) radiation is still damaging to deoxyribonucleic acid integrity, and has a number of unpleasant side effects ranging from erythema (sunburn) to carcinogenesis. As the conditions treated with this therapy tend to be chronic, exposures are repeated and can be high, increasing the lifetime probability of an adverse event or mutagenic effect. Despite the potential detrimental effects, quantitative ultraviolet dosimetry for phototherapy is an underdeveloped area and better dosimetry would allow clinicians to maximize biological effect whilst minimizing the repercussions of overexposure. This review gives a history and insight into the current state of UVR phototherapy, including an overview of biological effects of UVR, a discussion of UVR production, illness treated by this modality, cabin design and the clinical implementation of phototherapy, as well as clinical dose estimation techniques. Several dose models for ultraviolet phototherapy are also examined, and the need for an accurate computational dose estimation method in ultraviolet phototherapy is discussed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

ADEPT: a domain independent sequence alignment strategy for gpu architectures

Bioinformatic workflows frequently make use of automated genome assembly and protein clustering tools. At the core of most of these tools, a significant portion of execution time is spent in determining optimal local alignment between two sequences. This task is performed with the Smith-Waterman algorithm, which is a dynamic programming based method. With the advent of modern sequencing technologies and increasing size of both genome and protein databases, a need for faster Smith-Waterman implementations has emerged. Multiple SIMD strategies for the Smith-Waterman algorithm are available for CPUs. However, with the move of HPC facilities towards accelerator based architectures, a need for an efficient GPU accelerated strategy has emerged. Existing GPU based strategies have either been optimized for a specific type of characters (Nucleotides or Amino Acids) or for only a handful of application use-cases. In this paper, we present ADEPT, a new sequence alignment strategy for GPU architectures that is domain independent, supporting alignment of sequences from both genomes and proteins. Our proposed strategy uses GPU specific optimizations that do not rely on the nature of sequence. We demonstrate the feasibility of this strategy by implementing the Smith-Waterman algorithm and comparing it to similar CPU strategies as well as the fastest known GPU methods for each domain. ADEPT’s driver enables it to scale across multiple GPUs and allows easy integration into software pipelines which utilize large scale computational systems. We have shown that the ADEPT based Smith-Waterman algorithm demonstrates a peak performance of 360 GCUPS and 497 GCUPs for protein based and DNA based datasets respectively on a single GPU node (8 GPUs) of the Cori Supercomputer. Overall ADEPT shows 10x faster performance in a node-to-node comparison against a corresponding SIMD CPU implementation. ADEPT demonstrates a performance that is either comparable or better than existing GPU strategies. We demonstrated the efficacy of ADEPT in supporting existing bionformatics software pipelines by integrating ADEPT in MetaHipMer a high-performance denovo metagenome assembler and PASTIS a high-performance protein similarity graph construction pipeline. Our results show 10% and 30% boost of performance in MetaHipMer and PASTIS respectively.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Cadmium(II) inhibition of human uracil-DNA glycosylase by catalytic water supplantation

Toxic metals are known to inhibit DNA repair but the underlying mechanisms of inhibition are still not fully understood. DNA repair enzymes such as human uracil-DNA glycosylase (hUNG) perform the initial step in the base excision repair (BER) pathway. In this work, we showed that cadmium [Cd(II)], a known human carcinogen, inhibited all activity of hUNG at 100 μM. Computational analyses based on 2 μs equilibrium, 1.6 μs steered molecular dynamics (SMD), and QM/MM MD determined that Cd(II) ions entered the enzyme active site and formed close contacts with both D145 and H148, effectively replacing the catalytic water normally found in this position. Geometry refinement by density functional theory (DFT) calculations showed that Cd(II) formed a tetrahedral structure with D145, P146, H148, and one water molecule. This work for the first time reports Cd(II) inhibition of hUNG which was due to replacement of the catalytic water by binding the active site D145 and H148 residues. Comparison of the proposed metal binding site to existing structural data showed that D145:H148 followed a general metal binding motif favored by Cd(II). The identified motif offered structural insights into metal inhibition of other DNA repair enzymes and glycosylases.

Science & Technology - Other Topics↗
DOE OSTI2018

Hybrid Lithographic and DNA-Directed Assembly of a Configurable Plasmonic Metamaterial That Exhibits Electromagnetically Induced Transparency

Metamaterials are architectures that interact with light in novel ways by virtue of symmetry manipulation, and have opened a window into studying unprecedented light-matter interactions. However, they are commonly fabricated via lithographic methods, are usually static structures, and are limited in how they can react to external stimuli. Here we show that by combining lithographic techniques with DNA-based self-assembly methods, we can construct responsive plasmonic metamaterials that exhibit the plasmonic analog of an effect known as electromagnetically induced transparency (EIT), which can dramatically change their spectra upon motion of their constituent parts. Correlative scanning electron microscopy measurements, scattering dark-field microscopy, and computational simulations are performed on single assemblies to determine the relationship between their structures and spectral responses to a variety of external stimuli. The strength of the EIT-like effect in these assemblies can be tuned by precisely controlling the positioning of the plasmonic nanoparticles in these structures. For example, changing the ionic environment or dehydrating the sample will change the conformation of the DNA linkers and therefore the distance between the nanoparticles. Dark-field spectra of individual assemblies show peak shifts of up to many tens of nanometers upon DNA perturbations. This dynamic metamaterial represents a stepping stone toward state-of-the-art plasmonic sensing platforms and next-generation dynamic metamaterials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Predictive models of the genetic bases underlying budding yeast fitness in multiple environments

Abstract The ability of organisms to adapt and survive depends on the effects of genes and the environment on fitness. However, the multigenic nature of fitness and genotype-by-environment interactions hinder our understanding of the genetic basis of fitness. Here, we established fitness prediction models for 35 environments using machine learning and existing fitness data and different genetic variant types for a Saccharomyces cerevisiae population. Models revealed that the predictive ability of genetic variants varied across environments, with copy number variants explaining the majority of fitness variation in most cases. Model interpretation showed that different variant types identified distinct gene sets associated with predictive variants. These gene sets were significantly enriched in experimentally validated genes affecting fitness in only a subset of environments, indicating that many genes influencing fitness remain unexplored. Notably, non-experimentally validated genes were more important than validated ones for fitness predictions. Gene contributions to predictions were both isolate- and environment-dependent, pointing to gene-by-gene and gene-by-environment interactions. Furthermore, models uncovered experimentally validated and novel candidate genetic interactions for a well-characterized stress, the fungicide benomyl. These findings highlight the feasibility of identifying the genetic basis of fitness by using different genetic variant types and offer novel targets for future functional analysis.

DNA copy number variations↗
NASA NTRS2009

Simulation of TGF-Beta Activation by Low-Dose HZE Radiation in a Cell Culture

High charge (Z) and energy (E) (HZE) nuclei comprised in the galactic cosmic rays are main contributors to space radiation risk. They induce many lesions in living matter such as non-specific oxidative damage and the double-strand breaks (DSBs), which are considered key precursors of early and late effects of radiation. There is increasing evidence that cells respond collectively rather than individually to radiation, suggesting the importance of cell signaling1. The transforming growth factor (TGF ) is a signaling peptide that is expressed in nearly all cell type and regulates a large array of cellular processes2. TGF have been shown to mediate cellular response to DNA damage3 and to induce apoptosis in non-irradiated cells cocultured with irradiated cells4. TFG molecules are secreted by cells in an inactive complex known as the latency-associated peptide (LAP). TGF is released from the LAP by a conformational change triggered by proteases, thrombospondin-1, integrins, acidic conditions and .OH radical5. TGF then binds to cells receptors and activates a cascade of events mediated by Smad proteins6, which might interfere with the repair of DNA. Meanwhile, increasingly sophisticated Brownian Dynamics (BD) algorithms have appeared recently in the literature7 and can be applied to study the interaction of molecules with receptors. These BD computer models have contributed to the elucidation of signal transduction, ligand accumulation and autocrine loops in the epidermal growth factor (EGF) and its receptor (EFGR) system8. To investigate the possible roles of TGF in an irradiated cell culture, our Monte-Carlo simulation codes of the radiation track structure9 will be used to calculate the activation of TFG triggered by .OH produced by low doses of HZE ions. The TGF molecules will then be followed by a BD algorithm in a medium representative of a cell culture to estimate the number of activated receptors.

Plante, Ianik↗
DOE OSTI2013

Selecting Summary Statistics in Approximate Bayesian Computation for Calibrating Stochastic Models

Approximate Bayesian computation (ABC) is an approach for using measurement data to calibrate stochastic computer models, which are common in biology applications. ABC is becoming the “go-to” option when the data and/or parameter dimension is large because it relies on user-chosen summary statistics rather than the full data and is therefore computationally feasible. One technical challenge with ABC is that the quality of the approximation to the posterior distribution of model parameters depends on the user-chosen summary statistics. In this paper, the user requirement to choose effective summary statistics in order to accurately estimate the posterior distribution of model parameters is investigated and illustrated by example, using a model and corresponding real data of mitochondrial DNA population dynamics. We show that for some choices of summary statistics, the posterior distribution of model parameters is closely approximated and for other choices of summary statistics, the posterior distribution is not closely approximated. A strategy to choose effective summary statistics is suggested in cases where the stochastic computer model can be run at many trial parameter settings, as in the example.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Novobiocin blocks nucleic acid binding to Polθ and inhibits stimulation of its ATPase activity

Polymerase theta (Polθ) acts in DNA replication and repair, and its inhibition is synthetic lethal in BRCA1 and BRCA2-deficient tumor cells. Novobiocin (NVB) is a first-in-class inhibitor of the Polθ ATPase activity, and it is currently being tested in clinical trials as an anti-cancer drug. Here, we investigated the molecular mechanism of NVB-mediated Polθ inhibition. Using hydrogen deuterium exchange-mass spectrometry (HX-MS), biophysical, biochemical, computational and cellular assays, we found NVB is a non-competitive inhibitor of ATP hydrolysis. NVB sugar group deletion resulted in decreased potency and reduced HX-MS interactions, supporting a specific NVB binding orientation. Collective results revealed that NVB binds to an allosteric site to block DNA binding, both in vitro and in cells. Comparisons of The Cancer Genome Atlas (TCGA) tumors and matched controls implied that POLQ upregulation in tumors stems from its role in replication stress responses to increased cell proliferation: this can now be tested in fifteen tumor types by NVB blocking ssDNA-stimulation of ATPase activity, required for Polθ function at replication forks and DNA damage sites. Structural and functional insights provided in this study suggest a path for developing NVB derivatives with improved potency for Polθ inhibition by targeting ssDNA binding with entropically constrained small molecules.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

The role of machine learning in scientific workflows

Machine learning (ML) is being applied in a number of everyday contexts from image recognition, to natural language processing, to autonomous vehicles, to product recommendation. In the science realm, ML is being used for medical diagnosis, new materials development, smart agriculture, DNA classification, and many others. In this article, we describe the opportunities of using ML in the area of scientific workflow management. Scientific workflows are key to today’s computational science, enabling the definition and execution of complex applications in heterogeneous and often distributed environments. We describe the challenges of composing and executing scientific workflows and identify opportunities for applying ML techniques to meet these challenges by enhancing the current workflow management system capabilities. We foresee that as the ML field progresses, the automation provided by workflow management systems will greatly increase and result in significant improvements in scientific productivity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

A fast Monte Carlo cell-by-cell simulation for radiobiological effects in targeted radionuclide therapy using pre-calculated single-particle track standard DNA damage data

Introduction: We developed a new method that drastically speeds up radiobiological Monte Carlo radiation-track-structure (MC-RTS) calculations on a cell-by-cell basis. Methods: The technique is based on random sampling and superposition of single-particle track (SPT) standard DNA damage (SDD) files from a “pre-calculated” data library, constructed using the RTS code TOPAS-nBio, with “time stamps” manually added to incorporate dose-rate effects. This time-stamped SDD file can then be input into MEDRAS, a mechanistic kinetic model that calculates various radiation-induced biological endpoints, such as DNA double-strand breaks (DSBs), misrepairs and chromosomal aberrations, and cell death. As a benchmark validation of the approach, we calculated the predicted energy-dependent DSB yield and the ratio of direct-to-total DNA damage, both of which agreed with published in vitro experimental data. We subsequently applied the method to perform a superfast cell-by-cell simulation of an experimental in vitro system consisting of neuroendocrine tumor cells uniformly incubated with 177 Lu. Results and discussion: The results for residual DSBs, both at 24 and 48 h post-irradiation, are in line with the published literature values. Our work serves as a proof-of-concept demonstration of the feasibility of a cost-effective “in silico clonogenic cell survival assay” for the computational design and development of radiopharmaceuticals and novel radiotherapy treatments more generally.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2024

Novel Z-DNA binding domains in giant viruses

Z-nucleic acid structures play vital roles in cellular processes and have implications in innate immunity due to their recognition by Zα domains containing proteins (Z-DNA/Z-RNA binding proteins, ZBPs). Although Zα domains have been identified in six proteins, including viral E3L, ORF112, and I73R, as well as, cellular ADAR1, ZBP1, and PKZ, their prevalence across living organisms remains largely unexplored. In this study, we introduce a computational approach to predict Zα domains, leading to the revelation of previously unidentified Zα domain-containing proteins in eukaryotic organisms, including non-metazoan species. Our findings encompass the discovery of new ZBPs in previously unexplored giant viruses, members of the Nucleocytoviricota phylum. Through experimental validation, we confirm the Zα functionality of select proteins, establishing their capability to induce the B-to-Z conversion. Additionally, we identify Zα-like domains within bacterial proteins. While these domains share certain features with Zα domains, they lack the ability to bind to Z-nucleic acids or facilitate the B-to-Z DNA conversion. Our findings significantly expand the ZBP family across a wide spectrum of organisms and raise intriguing questions about the evolutionary origins of Zα-containing proteins. Moreover, our study offers fresh perspectives on the functional significance of Zα domains in virus sensing and innate immunity and opens avenues for exploring hitherto undiscovered functions of ZBPs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Structure of an RNA G-quadruplex from the West Nile virus genome

Potential G-quadruplex sites have been identified in the genomes of DNA and RNA viruses and proposed as regulatory elements. The genus Orthoflavivirus contains arthropod-transmitted, positive-sense, single-stranded RNA viruses that cause significant human disease globally. Computational studies have identified multiple potential G-quadruplex sites that are conserved across members of this genus. Subsequent biophysical studies established that some G-quadruplexes predicted in Zika and tickborne encephalitis virus genomes can form and known quadruplex binders reduced viral yields from cells infected with these viruses. The susceptibility of RNA to degradation and the variability of loop regions have made structure determination challenging. Despite these difficulties, we report a high-resolution structure of the NS5-B quadruplex from the West Nile virus genome. Analysis reveals two stacked tetrads that are further stabilized by a stacked triad and transient noncanonical base pairing. This structure expands the landscape of solved RNA quadruplex structures and demonstrates the diversity and complexity of biological quadruplexes. We anticipate that the availability of this structure will assist in solving further viral RNA quadruplexes and provides a model for a conserved antiviral target in Orthoflavivirus genomes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Comparative Analysis of DNA LLM Classification Techniques Using Intra-Layer Feature Extraction with Autoencoder Stacks [Poster]

This project conducts a comparative analysis of DNA LLM classification techniques using Evo2, Grover, and UTRML, focusing on intra-layer feature extraction in Evo2. By extracting features from multiple layers of Evo2 and integrating them into an autoencoder stack with a binary classification head, we evaluate its effectiveness in classifying genomic sequences compared to smaller DNA language models. My findings demonstrate that Evo2 outperforms Grover and UTRML in classification accuracy on a dataset provided by department 08625, CAO2021, while UTRML offers competitive performance with lower computational costs. This study highlights the potential of advanced embedding techniques in enhancing genomic data analysis and informs future research in bioinformatics.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Spectro Analytical, Computational and In Vitro Biological Studies of Novel Substituted Quinolone Hydrazone and it’s Metal Complexes

Some novel transition metal [Cu (II), Ni (II) and Co (II)] complexes of nalidixic acid hydrazone have been prepared and characterized by employing spectro-analytical techniques viz: elemental analysis, {sup 1}H-NMR, Mass, UV–Vis, IR, TGA-DTA, SEM-EDX, ESR and Spectrophotometry studies. The HyperChem 7.5 software was used for geometry optimization of title compound in its molecular and ionic forms. Quantum mechanical parameters, contour maps of highest occupied molecular orbitals (HOMO) and lowest unoccupied molecular orbitals (LUMO) and corresponding binding energy values were computed using semi empirical single point PM3 method. The stoichiometric equilibrium studies of metal complexes carried out spectrophotometrically using Job’s continuous variation and mole ratio methods inferred formation of 1:2 (ML{sub 2}) metal complexes in respective systems. The title compound and its metal complexes screened for antibacterial and antifungal properties, exemplified improved activity in metal complexes. The studies of nuclease activity for the cleavage of CT- DNA and MTT assay for in vitro cytotoxic properties involving metal complexes exhibited high activity. In addition, the DNA binding properties of Cu (II), Ni (II) and Co (II) complexes investigated by electronic absorption and fluorescence measurements revealed their good binding ability and commended agreement of K{sub b} values obtained from both the techniques. Molecular docking studies were also performed to find the binding affinity of synthesized compounds with DNA (PDB ID: 1N37) and “Thymidine phosphorylase from E.coli” (PDB ID: 4EAF) protein targets.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
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↗