Chiral Sugars Drive Enantioenrichment in Prebiotic Amino Acid Synthesis

Chiral pentose sugars mediate the enantioselective synthesis of amino acid precursors, with the magnitude of the chiral induction dictated by a subtle cooperativity between sugar hydroxyl groups. Ribose and lyxose give opposite chiral preferences, and theoretical calculations reveal the pseudoenantiomeric nature of transition state structures from the two sugars. Prebiotically plausible mixtures of natural d-sugars lead to enantioenrichment of natural l-amino acid precursors. Temporal monitoring and kinetic modeling of the reaction reveal an unusual dynamic kinetic resolution that shifts toward an enantioselective pathway over time, providing an amplification mechanism for the transfer of chiral information. This work adds to growing evidence for synergy in the etiology of the single chirality of the two most important classes of biological molecules, the sugars that make up DNA and RNA and the amino acids that form proteins

Aromaticity and Antiaromaticity in Transition-Metal Systems

Aromaticity is an important concept in chemistry primarily for organic compounds, but it has been extended to compounds containing transition-metal atoms. Recent findings of aromaticity and antiaromaticity in all-metal clusters have stimulated further research in describing the chemical bonding, structures and stability in transition-metal clusters and compounds on the basis of aromaticity and antiaromaticity, which are reviewed here. The presence of d-orbitals endows much more diverse chemistry, structure and chemical bonding to transition-metal clusters and compounds. One interesting feature is the existence of a new type of aromaticity-d-aromaticity, in addition to s-and p-aromaticity which are the only possible types for main-group compounds. Another striking characteristic in the chemical bonding of transition-metal systems is the multifold nature of aromaticity, antiaromaticity or even conflicting aromaticity. Separate sets of counting rules have been proposed for cyclic transition-metal systems to account for the three types of s-, p-and d-aromaticity/antiaromaticity. The diverse transition-metal clusters and compounds reviewed here indicate that multiple aromaticity and antiaromaticity may be much more common in chemistry than one would anticipate. It is hoped that the current review will stimulate interest in further understanding the structure and bonding, on the basis of aromaticity and antiaromaticity, of other known or unknown transition-metal systems, such as the active sites of enzymes or other biomolecules which contain transition-metal atoms and clusters

Quantum-centric Supercomputing for Materials Science: A Perspective on Challenges and Future Directions

Computational models are an essential tool for the design, characterization, and discovery of novel materials. Hard computational tasks in materials science stretch the limits of existing high-performance supercomputing centers, consuming much of their simulation, analysis, and data resources. Quantum computing, on the other hand, is an emerging technology with the potential to accelerate many of the computational tasks needed for materials science. In order to do that, the quantum technology must interact with conventional high-performance computing in several ways: approximate results validation, identification of hard problems, and synergies in quantum-centric supercomputing. In this paper, we provide a perspective on how quantum-centric supercomputing can help address critical computational problems in materials science, the challenges to face in order to solve representative use cases, and new suggested directions.Comment: 60 pages, 14 figures; comments welcom

Analysis of Chemical Bonding in Clusters by Means of The Adaptive Natural Density Partitioning

Models of chemical bonding are essential for contemporary chemistry. Even the explosive development of the computational resources including, both hardware and software, cannot eliminate necessity of compact, intuitive, and efficient methods of representing chemically relevant information. The Lewis model of chemical bonding, which was proposed eleven years before the formulation of quantum theory and preserves its pivotal role in chemical education and research for more than ninety years, is a vivid example of such a tool. As chemistry shifts to the nanoscale, it is becoming obvious that a certain shift of the paradigms of chemical bonding is inescapable. For example, none of the currently available models of chemical bonding can correctly predict structures and properties of sub-nano and nanoclusters. Clusters of main-group elements and transition metals are of major interest for nanotechnology with potential applications including catalysis, hydrogen storage, molecular conductors, drug development, nanodevices, etc. Thus, the goals of this dissertation were three-fold. Firstly, the dissertation introduces a novel approach to the description of chemical bonding and the algorithm of the software performing analysis of chemical bonding, which is called Adaptive Natural Density Partitioning. Secondly, the dissertation presents a series of studies of main-group element and transition-metal clusters in molecular beams, including obtaining their photoelectron spectra, establishing their structures, analyzing chemical bonding, and developing generalized model of chemical bonding. Thirdly, the dissertation clarifies and develops certain methodological aspects of the quantum chemical computations dealing with clusters. This includes appraisal of the performance of several computational methods based on the Density Functional Theory and the development of global optimization software based on the Particle Swarm Optimization algorithm

Uncertainty of Prebiotic Scenarios: The Case of the Non-Enzymatic Reverse Tricarboxylic Acid Cycle

We consider the hypothesis of the primordial nature of the non-enzymatic reverse tricarboxylic acid (rTCA) cycle and describe a modeling approach to quantify the uncertainty of this hypothesis due to the combinatorial aspect of the constituent chemical transformations. Our results suggest that a) rTCA cycle belongs to a degenerate optimum of auto-catalytic cycles, and b) the set of targets for investigations of the origin of the common metabolic core should be significantly extended

Radiolysis Generates a Complex Organosynthetic Chemical Network

Origins of life chemistry has progressed from seeking out the production of specific molecules to seeking out conditions in which macromolecular precursors may interact with one another in ways that lead to biological organization. Reported precursor synthesis networks generally lack biological organizational attributes. Radical species are highly reactive, but do their chemical reaction networks resemble living systems? Here we report the results of radiolysis reaction experiments that connect abundant geochemical reservoirs to the production of carboxylic acids, amino acids, and ribonucleotide precursors and study the topological properties of the resulting network. The network exhibits attributes associated with biological systems: it is hierarchically organized, there are families of closed loop cycles, and the species and cycle histograms exhibit heterogeneous (heavy-tailed) distributions. The core cycles of the network are made possible by the high reactivity of radical species such as H and OH. Radiolysis is implicated as a unique prerequisite for driving abiotic organosynthetic self-organization. </p

A Recommender System for Inverse Design of Polycarbonates and Polyesters

The convergence of artificial intelligence and machine learning with material science holds significant promise to rapidly accelerate development timelines of new high-performance polymeric materials. Within this context, we report an inverse design strategy for polycarbonate and polyester discovery based on a recommendation system that proposes polymerization experiments that are likely to produce materials with targeted properties. Following recommendations of the system driven by the historical ring-opening polymerization results, we carried out experiments targeting specific ranges of monomer conversion and dispersity of the polymers obtained from cyclic lactones and carbonates. The results of the experiments were in close agreement with the recommendation targets with few false negatives or positives obtained for each class.<br /

Pathways to Soot Oxidation: Reaction of OH with Phenanthrene Radicals

Energetics and kinetics of the oxidation of possible soot surface sites by hydroxyl radicals were investigated theoretically. Energetics were calculated by employing density functional theory. Three candidate reactions were selected as suitable prototypes of soot oxidation by OH. The first two, OH + benzene and OH + benzene–phenol complex, did not produce pathways that lead to substantial CO expulsion. The third reaction, OH attack on the phenanthrene radical, had multiple pathways leading to CO elimination. The kinetics of the latter reaction system were determined by solving the master equations with the MultiWell suite of codes. The barrierless reaction rates of this system were computed using the VariFlex program. The computations were carried out over the ranges 1500–2500 K and 0.01–10 atm. At higher temperatures, above 2000 K, the oxidation of phenanthrene radicals by OH followed a chemically activated path. At temperatures lower than 2000 K, chemical activation was not sufficient to drive the reaction to products; reaction progress was impeded by intermediate adducts rapidly de-energizing before reaching products. In such cases, the reaction system was modeled by treating the accumulating adducts as distinct chemical species and computing their kinetics via thermal decomposition. The overall rate coefficient of phenanthrene radical oxidation by OH forming CO was found to be insensitive to pressure and temperature and is approximately 1 × 10¹⁴ cm³ mol^–1 s^–1. The oxidation of phenanthrene radicals by OH is shown to be controlled by two main processes: H atom migration/elimination and oxyradical decomposition. H atom migration and elimination made possible relatively rapid rearrangement of the aromatic edge to form oxyradicals with favorable decomposition rates. The reaction then continues down the fastest oxyradical pathways, eliminating CO

Complex Chemical Reaction Networks from Heuristics-Aided Quantum Chemistry

While structures and reactivities of many small molecules can be computed efficiently and accurately using quantum chemical methods, heuristic approaches remain essential for modeling complex structures and large-scale chemical systems. Here, we present a heuristics-aided quantum chemical methodology applicable to complex chemical reaction networks such as those arising in cell metabolism and prebiotic chemistry. Chemical heuristics offer an expedient way of traversing high-dimensional reactive potential energy surfaces and are combined here with quantum chemical structure optimizations, which yield the structures and energies of the reaction intermediates and products. Application of heuristics-aided quantum chemical methodology to the formose reaction reproduces the experimentally observed reaction products, major reaction pathways, and autocatalytic cycles