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Results for “Genetic Code”

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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At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Factors influencing the rate of non-enzymatic activation of carboxylic and amino acids by ATP

The nonenzymatic formation of adenylate anhydrides of carboxylic and amino acids is discussed as a necessary step in the origin of the genetic code and protein biosynthesis. Results of studies are presented which have shown the rate of activation to depend on the pKa of the carboxyl group, the pH of the medium, temperature, the divalent metal ion catalyst, salt concentration, and the nature of the amino acid. In particular, it was found that of the various amino acids investigated, phenylalanine had the greatest affinity for the adenine derivatives adenosine and ATP. Results thus indicate that selective affinities between amino acids and nucleotides were important during prebiotic chemical evolution, and may have played a major role in the origin of protein synthesis and genetic coding.

Mullins, D. W., Jr.↗
NASA NTRS1966

Molecules and Evolution

Biochemical basis of evolution - evolution and DNA, genetic code, microbiology and heredity, mutations, and evolution and hemoglobins

GENETIC CODE↗
NASA NTRS1999

Modeling the Volcanic Source at Long Valley, CA, Using a Genetic Algorithm Technique

In this project, we attempted to model the deformation pattern due to the magmatic source at Long Valley caldera using a real-value coded genetic algorithm (GA) inversion similar to that found in Michalewicz, 1992. The project has been both successful and rewarding. The genetic algorithm, coded in the C programming language, performs stable inversions over repeated trials, with varying initial and boundary conditions. The original model used a GA in which the geophysical information was coded into the fitness function through the computation of surface displacements for a Mogi point source in an elastic half-space. The program was designed to invert for a spherical magmatic source - its depth, horizontal location and volume - using the known surface deformations. It also included the capability of inverting for multiple sources.

Tiampo, Kristy F.↗
NASA NTRS2022

A Closer Look at Non-Random Patterns Within Chemistry Space for a Smaller, Earlier Amino Acid Alphabet

Recent findings, in vitro and in silico, are strengthening the idea of a simpler, earlier stage of genetically encoded proteins which used amino acids produced by prebiotic chemistry. These findings motivate a re-examination of prior work which has identified unusual properties of the set of twenty amino acids found within the full genetic code, while leaving it unclear whether similar patterns also characterize the subset of prebiotically plausible amino acids. We have suggested previously that this ambiguity may result from the low number of amino acids recognized by the definition of prebiotic plausibility used for the analysis. Here, we test this hypothesis using significantly updated data for organic material detected within meteorites, which contain several coded and non-coded amino acids absent from prior studies. In addition to confirming the well-established idea that “late” arriving amino acids expanded the chemistry space encoded by genetic material, we find that a prebiotically plausible subset of coded amino acids generally emulates the patterns found in the full set of 20, namely an exceptionally broad and even distribution of volumes and an exceptionally even distribution of hydrophobicities (quantified as logP) over a narrow range. However, the strength of this pattern varies depending on both the size and composition the library used to create a background (null model) for a random alphabet, and the precise definition of exactly which amino acids were present in a simpler, earlier code. Findings support the idea that a small sample size of amino acids caused previous ambiguous results, and further improvements in meteorite analysis, and/or prebiotic simulations will further clarify the nature and extent of unusual properties. We discuss the case of sulfur-containing amino acids as a specific and clear example and conclude by reviewing the potential impact of better understanding the chemical “logic” of a smaller forerunner to the standard amino acid alphabet.

Amino acids↗
NASA NTRS2001

Searching for Organics, Fossils, and Biology on Mars

One of the goals of Astrobiology is to understand life on a fundamental level. All life on Earth is constructed from the same basic biochemical building blocks consisting of 20 amino acids with left handed symmetry, five nucleotides, a few sugars of right handed symmetry and some lipids. Using the metaphor of computers this is equivalent to saying that all life shares the same hardware. Beyond hardware similarity, it is now known that all life has fundamentally the same software. The genetic code of life is common to all organisms. Some have argued that the "hammer of evolution is heavy" and life anywhere is likely to be composed of identical biochemical and genetic patterns. However, in a system as complex as biochemistry it is likely that there are numerous local optima and the details of the optimum found by evolutionary selection on another world would likely depend on the initial conditions and random developments in the early biological history on that world. To address these fundamental questions in Astrobiology we need a second example of life: a second genesis.

McKay, Christopher P.↗
DOE OSTI2024

Pre-hypertrophic chondrogenic enhancer landscape of limb and axial skeleton development

Chondrocyte differentiation controls skeleton development and stature. Here we provide a comprehensive map of chondrocyte-specific enhancers and show that they provide a mechanistic framework through which non-coding genetic variants can influence skeletal development and human stature. Working with fetal chondrocytes isolated from mice bearing a Col2a1 fluorescent regulatory sensor, we identify 780 genes and 2'704 putative enhancers specifically active in chondrocytes using a combination of RNA-seq, ATAC-seq and H3K27ac ChIP-seq. Most of these enhancers (74%) show pan-chondrogenic activity, with smaller populations being restricted to limb (18%) or trunk (8%) chondrocytes only. Notably, genetic variations overlapping these enhancers better explain height differences than those overlapping non-chondrogenic enhancers. Finally, targeted deletions of identified enhancers at the Fgfr3, Col2a1, Hhip and, Nkx3-2 loci confirm their role in regulating cognate genes. This enhancer map provides a framework for understanding how genes and non-coding variations influence bone development and diseases.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2012

System and method for embedding emotion in logic systems

A system, method, and computer readable-media for creating a stable synthetic neural system. The method includes training an intellectual choice-driven synthetic neural system (SNS), training an emotional rule-driven SNS by generating emotions from rules, incorporating the rule-driven SNS into the choice-driven SNS through an evolvable interface, and balancing the emotional SNS and the intellectual SNS to achieve stability in a nontrivial autonomous environment with a Stability Algorithm for Neural Entities (SANE). Generating emotions from rules can include coding the rules into the rule-driven SNS in a self-consistent way. Training the emotional rule-driven SNS can occur during a training stage in parallel with training the choice-driven SNS. The training stage can include a self assessment loop which measures performance characteristics of the rule-driven SNS against core genetic code. The method uses a stability threshold to measure stability of the incorporated rule-driven SNS and choice-driven SNS using SANE.

Curtis, Steven A.↗
DOE OSTI2024

A One‐Pot Biocatalytic Cascade to Access Diverse l ‐Phenylalanine Derivatives from Aldehydes or Carboxylic Acids

Abstract Nonstandard amino acids (nsAAs) that are l ‐phenylalanine derivatives with aryl ring functionalization have long been harnessed in natural product synthesis, therapeutic peptide synthesis, and diverse applications of genetic code expansion. Yet, to date, these chiral molecules have often been the products of poorly enantioselective and environmentally harsh organic synthesis routes. Here, we reveal the broad specificity of multiple natural pyridoxal 5′‐phosphate (PLP)‐dependent enzymes, specifically an l ‐threonine transaldolase, a phenylserine dehydratase, and an aminotransferase, toward substrates that contain aryl side chains with diverse substitutions. We exploit this tolerance to construct a one‐pot biocatalytic cascade that achieves high‐yield synthesis of 18 diverse l ‐phenylalanine derivatives from aldehydes under mild aqueous reaction conditions. We demonstrate the addition of a carboxylic acid reductase module to this cascade to enable the biosynthesis of l ‐phenylalanine derivatives from carboxylic acids that may be less expensive or less reactive than the corresponding aldehydes. Finally, we investigate the scalability of the cascade by developing a lysate‐based route for preparative‐scale synthesis of 4‐formyl‐ l ‐phenylalanine, a nsAA with a bio‐orthogonal handle that is not readily market‐accessible. Overall, this work offers an efficient, versatile, and scalable route with the potential to lower manufacturing costs and democratize synthesis for many valuable nsAAs.

Anderson, Shelby R. [Department of Chemical and Bi↗
DOE OSTI2024

NCAP: Noncanonical Amino Acid Parameterization Software for CHARMM Potentials

Noncanonical Amino Acids (NCAAs) provide numerous avenues for introduction of novel functionality to peptides and proteins. NCAAs can be incorporated through solid phase synthesis or genetic code expansion in conjugation with heterologous expression of the encoded protein modification. Due to the difficulty of synthesis, wide chemical space and lack of empirically resolved structures modeling the effects of NCAA mutation is critical for rational protein design. To evaluate the structural and functional perturbations NCAAs introduce we utilize molecular potentials that describe the forces in protein structure. Most potentials such as CHARMM are designed to model canonical residues but can be parameterized in include novel NCAAs. Here, in this work, we introduce NCAP a software package to generate CHARMM compatible parameters from quantum chemical calculation. Unlike currently available tools NCAP is designed to recognize NCAA structure and automatically bridge the gap between DFT calculations and potential parameters. For our software we discuss workflow, validation against canonical parameter sets and comparison to published NCAA-protein structures.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Rapid discovery and evolution of nanosensors containing fluorogenic amino acids

Binding-activated optical sensors are powerful tools for imaging, diagnostics, and biomolecular sensing. However, biosensor discovery is slow and requires tedious steps in rational design, screening, and characterization. Here we report on a platform that streamlines biosensor discovery and unlocks directed nanosensor evolution through genetically encodable fluorogenic amino acids (FgAAs). Building on the classical knowledge-based semisynthetic approach, we engineer ~15 kDa nanosensors that recognize specific proteins, peptides, and small molecules with up to 100-fold fluorescence increases and subsecond kinetics, allowing real-time and wash-free target sensing and live-cell bioimaging. An optimized genetic code expansion chemistry with FgAAs further enables rapid (~3 h) ribosomal nanosensor discovery via the cell-free translation of hundreds of candidates in parallel and directed nanosensor evolution with improved variant-specific sensitivities (up to ~250-fold) for SARS-CoV-2 antigens. Altogether, this platform could accelerate the discovery of fluorogenic nanosensors and pave the way to modify proteins with other non-standard functionalities for diverse applications.

Biosensors↗
DOE OSTI2025

Enhancing chemical bioproduction with rational control of bacterial post-translational modifications

Efficient conversion of inexpensive feedstocks to valuable chemicals by microbes is critical for a robust bioeconomy, but the ability to rationally design bacteria is hampered by insufficient knowledge of how post translational modifications (PTMs) control bacterial protein function and thus bioproduction phenotypes. Our study will focus on the lysine acetylation, a ubiquitous bacterial PTM that can affect the function of enzymes in central metabolism that are often critical for bioproduction processes, disrupt transcriptional regulation, and reduce translation. However, most lysine acetylation data is observational, which means that we do not know when, how, and what specific acetylated residues affect protein function and bacterial physiology. For our model host, we will use a Pseudomonas putida strain that we previously engineered to convert lignocellulosic feedstocks into chemicals such as itaconic acid (ITA). With this strain, we use a dynamic two-stage bioproduction process in which ITA is produced during a non-growth associated production phase. Production is highest during growth stages when lysine acetylation is low in other organisms (early stationary phase) and stalls in conditions where acetylation is highest (late stationary phase). The switch from high to stalled ITA production is also correlated with an unexpected increase in acetate levels – the precursor to non-enzymatic lysine acetylation. As such, we predict that lysine acetylation plays a substantial role in regulating the metabolic pathways required for ITA production. We will develop a generalizable approach that combines high-throughput genetic screens and cutting-edge genome engineering with state-of-the-art proteomics, metabolomics, and genetic code expansion methods to identify and modulate lysine acetylation patterns in bacteria. Ultimately, these strategies aim to manipulate protein expression and acetylation patterns to enhance bioproduction phenotypes (e.g., sustained ITA production in late stationary phase).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2026

Multimodal Approaches for Leveraging Domain Knowledge with State-of-the-Art Machine Learning to Engineer Biocatalysts

This grant aimed to accelerate the development of specialized enzymes—biological catalysts essential for sustainable manufacturing and medicine—by integrating traditional laboratory evolution with cutting-edge artificial intelligence. To achieve this, we developed a suite of high-throughput sequencing tools and a centralized database to bridge the gap between a protein’s genetic "code" and its physical function. By training machine learning models on large datasets, we also demonstrated the ability to move beyond slow, trial-and-error testing to a "generative" approach, where AI can independently design new, versatile enzymes like tryptophan synthases. Ultimately, these findings demonstrate that combining laboratory data with computer-guided design enables the engineering of highly efficient biological tools with unprecedented speed and precision.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1971

Comparisons of the polypeptide chains of globins.

Discussion of the amino acid differences and minimum base differences per codon due to mutations which took place during divergent evolution of vertebrates from a common ancestral gene. The ?random mutation model' of evolution is examined by comparing a carp alpha Hb chain and six mammalian alpha Hb chains in terms of the genetic code. The occurrence of recognizable three-base changes is analyzed and a summary of the distribution of changes in the hemoglobin and myoglobin chains is given for 148 sites.

Jukes, T. H.↗
NASA NTRS1974

Conservation of Shannon's redundancy for proteins

Concepts of information theory are applied to examine various proteins in terms of their redundancy in natural originators such as animals and plants. The Monte Carlo method is used to derive information parameters for random protein sequences. Real protein sequence parameters are compared with the standard parameters of protein sequences having a specific length. The tendency of a chain to contain some amino acids more frequently than others and the tendency of a chain to contain certain amino acid pairs more frequently than other pairs are used as randomness measures of individual protein sequences. Non-periodic proteins are generally found to have random Shannon redundancies except in cases of constraints due to short chain length and genetic codes. Redundant characteristics of highly periodic proteins are discussed. A degree of periodicity parameter is derived.

Gatlin, L. L.↗
NASA NTRS1974

Coacervate droplets, proteinoid microspheres, and the genetic apparatus

Differences between typical coacervate droplets and typical proteinoid microspheres are examined. It is pointed out that coacervate droplets are produced from polymers obtained from contemporary organisms. The microspheres considered are aggregates of proteinoid formed from monomeric amino acids under geologically relevant conditions. Aspects regarding the primordial sequence are discussed along with the origin of the genetic apparatus and the genetic code.

Fox, S. W.↗
NASA NTRS1975

Beta structures of alternating polypeptides and their possible prebiotic significance

A survey of the commonest amino acids formed in prebiotic conditions suggests that the earliest form of genetic coding may have specified polypeptides with a strong tendency to form stable beta-sheet structures. Poly(Val-Lys), like other polypeptides in which hydrophobic and hydrophilic residues alternate, tends to form beta structures. It is shown that bilayers with a hydrophobic interior and a hydrophilic exterior may be present in aqueous solution.

Brack, A.↗