One Among Millions: The Chemical Space of Nucleic Acid-Like Molecules.

Biology encodes hereditary information in DNA and RNA, which are finely tuned to their biological functions and modes of biological production. The central role of nucleic acids in biological information flow makes them key targets of pharmaceutical research. Indeed, other nucleic acid-like polymers can play similar roles to natural nucleic acids both in vivo and in vitro; yet despite remarkable advances over the last few decades, much remains unknown regarding which structures are compatible with molecular information storage. Chemical space describes the structures and properties of molecules that could exist within a given molecular formula or other classification system. Using structure generation methods, we explore nucleic acid analogues within the formula ranges BC3-7H5-15O2-4 and BC3-6H5-15N1-2O0-4, where B is a recognition element (e.g., a nucleobase). Other restrictions included two obligatory points of attachment for inclusion into a linear polymer and substructures predicting chemical stability. These sets contain 86,007 (CHO) and 75,309 (CHNO) compositionally isomeric structures, representing 706,568 CHO and 454,422 CHNO stereoisomers, that diversely and densely occupy this space. These libraries point toward there being large spaces of unexplored chemistry relevant to pharmacology and biochemistry and efforts to understand the origins of life.

Comparative Evaluation of Electron Ionization Mass Spectral Prediction Methods.

During the past decade promising methods for computational prediction of electron ionization mass spectra have been developed. The most prominent ones are based on quantum chemistry (QCEIMS) and machine learning (CFM-EI, NEIMS). Here we provide a threefold comparison of these methods with respect to spectral prediction and compound identification. We found that there is no unambiguous way to determine the best of these three methods. Among other factors, we find that the choice of spectral distance functions play an important role regarding the performance for compound identification.

An open source computational workflow for the discovery of autocatalytic networks in abiotic reactions.

A central question in origins of life research is how non-entailed chemical processes, which simply dissipate chemical energy because they can do so due to immediate reaction kinetics and thermodynamics, enabled the origin of highly-entailed ones, in which concatenated kinetically and thermodynamically favorable processes enhanced some processes over others. Some degree of molecular complexity likely had to be supplied by environmental processes to produce entailed self-replicating processes. The origin of entailment, therefore, must connect to fundamental chemistry that builds molecular complexity. We present here an open-source chemoinformatic workflow to model abiological chemistry to discover such entailment. This pipeline automates generation of chemical reaction networks and their analysis to discover novel compounds and autocatalytic processes. We demonstrate this pipeline's capabilities against a well-studied model system by vetting it against experimental data. This workflow can enable rapid identification of products of complex chemistries and their underlying synthetic relationships to help identify autocatalysis, and potentially self-organization, in such systems. The algorithms used in this study are open-source and reconfigurable by other user-developed workflows.

Deciphering Biosignatures in Planetary Contexts.

Microbial life permeates Earth's critical zone and has likely inhabited nearly all our planet's surface and near subsurface since before the beginning of the sedimentary rock record. Given the vast time that Earth has been teeming with life, do astrobiologists truly understand what geological features untouched by biological processes would look like? In the search for extraterrestrial life in the Universe, it is critical to determine what constitutes a biosignature across multiple scales, and how this compares with "abiosignatures" formed by nonliving processes. Developing standards for abiotic and biotic characteristics would provide quantitative metrics for comparison across different data types and observational time frames. The evidence for life detection falls into three categories of biosignatures: (1) substances, such as elemental abundances, isotopes, molecules, allotropes, enantiomers, minerals, and their associated properties; (2) objects that are physical features such as mats, fossils including trace-fossils and microbialites (stromatolites), and concretions; and (3) patterns, such as physical three-dimensional or conceptual n-dimensional relationships of physical or chemical phenomena, including patterns of intermolecular abundances of organic homologues, and patterns of stable isotopic abundances between and within compounds. Five key challenges that warrant future exploration by the astrobiology community include the following: (1) examining phenomena at the "right" spatial scales because biosignatures may elude us if not examined with the appropriate instrumentation or modeling approach at that specific scale; (2) identifying the precise context across multiple spatial and temporal scales to understand how tangible biosignatures may or may not be preserved; (3) increasing capability to mine big data sets to reveal relationships, for example, how Earth's mineral diversity may have evolved in conjunction with life; (4) leveraging cyberinfrastructure for data management of biosignature types, characteristics, and classifications; and (5) using three-dimensional to n-D representations of biotic and abiotic models overlain on multiple overlapping spatial and temporal relationships to provide new insights.

Prebiotic chemistry: geochemical context and reaction screening.

The origin of life on Earth is widely believed to have required the reactions of organic compounds and their self- and/or environmental organization. What those compounds were remains open to debate, as do the environment in and process or processes by which they became organized. Prebiotic chemistry is the systematic organized study of these phenomena. It is difficult to study poorly defined phenomena, and research has focused on producing compounds and structures familiar to contemporary biochemistry, which may or may not have been crucial for the origin of life. Given our ignorance, it may be instructive to explore the extreme regions of known and future investigations of prebiotic chemistry, where reactions fail, that will relate them to or exclude them from plausible environments where they could occur. Come critical parameters which most deserve investigation are discussed.