III. Ecosmos: A Revolutionary Fertile, Habitable, Solar-Bioplanet, Incubator Lifescape

3. Supramolecular Systems Chemistry

Sadowski, Peter, et al. Synergies Between Quantum Mechanics and Machine Learning in Reaction Prediction. Journal of Chemical Information and Modeling. 56/2135, 2016. UC Irvine and ExxonMobil Research computational chemists including Pierre Baldi achieve a novel synthesis of these physical and neural methods, which are reported herein, and in Mind Over Matter. As a result, an efficient, quantum learning approach serves to parse the “grammar” of chemical reactions by these natural language processes. See also in this journal Deep Neural Nets as a Method for Quantitative Structure-Activity Relationships by Junshui Ma, et al (55/263, 2015).

Machine learning (ML) and quantum mechanical (QM) methods can be used in two-way synergy to build chemical reaction expert systems. The proposed ML approach identifies electron sources and sinks among reactants and then ranks all source–sink pairs. This addresses a bottleneck of QM calculations by providing a prioritized list of mechanistic reaction steps. QM modeling can then be used to compute the transition states and activation energies of the top-ranked reactions, providing additional or improved examples of ranked source–sink pairs. Retraining the ML model closes the loop, producing more accurate predictions from a larger training set. The approach is demonstrated in detail using a small set of organic radical reactions. (Abstract)

Saitou, Naruya, Naruya. Introduction to Evolutionary Genomics. International: Springer, 2018. A National Institute of Genetics, Mishima, Japan population geneticist provides after 2013 a second edition which further joins our homo sapiens genetic endowment with a deep ancestry in life’s emergent development. Three main sections are Basic Processes of Genome Evolution, Evolving Genomes, and Methods for Evolutionary Genomics.

Topics and Features: Introduces the basics of molecular biology, covering protein structure and diversity, as well as DNA replication, transcription, and translation; Examines the phylogenetic relationships of DNA sequences, and the processes of mutation, neutral evolution, and natural selection; Presents a brief evolutionary history of life, surveying the key features of the genomes of prokaryotes, eukaryotes, viruses and phages, vertebrates, and humans; Reviews the various biological “omic” databases, and discusses the analysis of homologous nucleotide and amino acid sequences; Provides an overview of the experimental sequencing of genomes and transcriptomes, and the construction of phylogenetic trees.

Salles, Airton, et al. A Self-Organizing Chemical Assembly Line. Journal of the American Chemical Society. 135/51, 2013. University of Cambridge complexity chemists in coauthor Jonathan Nitschke’s group describe how principles of biological self-organization can similarly be applied to “inorganic” material dynamic reactivities. View Nitschke’s website to learn about members, projects such as Complex Topologies, and more publications.

Chemical syntheses generally involve a series of discrete transformations whereby a simple set of starting materials are progressively rendered more complex. In contrast, living systems accomplish their syntheses within complex chemical mixtures, wherein the self-organization of biomolecules allows them to form “assembly lines” that transform simple starting materials into more complex products. Here we demonstrate the functioning of an abiological chemical system whose simple parts self-organize into a complex system capable of directing the multistep transformation of the small molecules furan, dioxygen, and nitromethane into a more complex and information-rich product. The novel use of a self-assembling container molecule to catalytically transform a high-energy intermediate is central to the system’s functioning. (Abstract)

Sayama, Hiroki. Swarm Chemistry. Artificial Life. 15/1, 2009. In a special issue on Artificial Chemistry, a SUNY Binghamton bioengineer finds these generic complex systems principles to be similarly suitable across chemical domains.

We propose swarm chemistry, a new artificial chemistry framework that uses artificial swarm populations as chemical reactants. Reaction in swarm chemistry is not determined by predefined reaction rules as commonly assumed in typical artificial chemistry studies, but is spontaneously achieved by the emergence of a new spatiotemporal pattern of collective behavior through the kinetic interaction between multiple chemical species.

Sayama, Hiroki. Swarm Chemistry Evolving. Fellermann, Harold, et al, eds. Artificial Life XII: Proceedings of the Twelfth International Conference. Cambridge: MIT Press, 2010. The SUNY Binghampton bioengineer updates his laboratory project (Google keywords for info) to reconceive active chemical phenomena in terms of complex adaptive systems.

Moreover, to demonstrate that macro-level ecological/evolutionary dynamics of self-organizing swarm patterns can arise out of micro-level processes embedded in particle interactions, we further introduced minimal mechanisms for variation and competition of recipes when they are transmitted between particles. With these additional mechanisms, the Swarm Chemistry world has become capable of producing fully autonomous ecological and evolutionary behaviors of self-organized “super-organisms” made of a number of swarming particles.

Scholes, Gregory. Quantum-like states on complex synchronized networks. arXiv:2405.07950. A Princeton chemist whom by way of his lab group (scholes.princeton.edu) is a pioneer researcher for an beneficial integration of macro/micro, classical and quantum chemical reactivities. This entry is a latest review, search arXiv for more work such as Foundations of Quantum Information for Physical Chemistry at 2311.12238.

Recent work suggests that interesting quantum-like probability laws, including interference effects, can be manifest in classical systems. Here we propose a model for quantum-like (QL) states and bits. We propose a way that complex systems can host robust states to process information in a QL fashion. It is shown that QL states are networks based on k-regular random graphs which can encode information for QL like processing. Although the emergent cases are classical, they have properties analogous to quantum states. The possibility of a QL advantage for computer operations and new kinds of function in the brain are discussed as open questions.

The Scholes Group studies how complex molecular systems in chemistry and biology interact with light. We are interested to learn the mechanisms for photo-initiated processes like solar energy conversion. We are also working out how quantum-mechanical phenomena influence function. We study a broad range of projects which include questions in quantum information science, photobiomodulation medicine, quantum electrodynamics, photosynthesis, solar energy conversion, and photo-activated catalysis in synthetic chemistry.

Schwerdtfeger, Peter, et al. The Periodic Table and the Physics that Drives It. Nature Reviews Chemistry. 4/7, 2020. Massey University, New Zealand and University of Helsinki (Pekka Pyykko) theorists consider how the formation of chemical elements can necessarily be traced in an analogic way to deep physical forces such as relativistic electronic-structure theory, nuclear-structure theory and the astrophysical origins.

The periodic table can be seen as parallel to the Standard Model in particle physics, in which elementary particles can be ordered according to their intrinsic properties. The underlying theory to describe the interactions between particles comes from quantum field theory and its inherent symmetries. In the periodic table, the elements are placed into a certain period and group based on electronic configurations that originate from principles for the electrons surrounding a positively charged nucleus. In this Perspective, we critically analyse the periodic table of elements and the current status of theoretical predictions and origins for the heaviest elements, which combine both quantum chemistry and physics. (Abstract excerpt)

Segler, Marwin, et al. Planning Chemical Synthesis with Deep Neural Networks and Symbolic AI. Nature. 555/604, 2018. Institute of Organic Chemistry and Center for Multiscale Theory and Computation, Westfälische Wilhelms-Universität, and International Centre for Quantum and Molecular Structures, Shanghai University researchers seek novel chemical creations by way of applying natural materiality principles by their affinity with cerebral cognition and brain-based artificial intelligence methods.

To plan the design of small organic molecules, chemists use retrosynthesis, a problem-solving technique in which target molecules are recursively transformed into increasingly simpler precursors. Computer-aided retrosynthesis at present is slow and of unsatisfactory quality. Here we use Monte Carlo tree search and symbolic artificial intelligence (AI) to discover retrosynthetic routes. We combined Monte Carlo tree search with an expansion to a policy network guide, and a filter to pre-select the most promising steps. These deep neural networks were trained on essentially all reactions ever published in organic chemistry. Our system solves for many molecules, thirty times faster than the traditional computer-aided search method. (Abstract edits)

Showalter, Kenneth and Irving Epstein. From Chemical Systems to Systems Chemistry: Patterns in Space and Time. Chaos. 25/9, 2015. For a 25th Anniversary issue focus Perspectives on Nonlinear Science, West Virginia University and Brandeis University scientists review the passage, akin to other domains as biology and genetics, from many separate pieces to their integral dynamics. By this adjustment, novel properties such as collective behavior, networks, and emergence can be perceived. By so doing, a “chimera” of orderly synchronization and unsynchronized disorder is seen to occur. Again, the 2015 recognition of nature’s universality proceeds apace.

Chemical systems display a remarkable range of nonlinear phenomena in time and space. These include temporal oscillations, multistability and chaos as well as stationary (Turing) spatial patterns, and a variety of traveling and standing waves. During the past twenty-five years, experimental and theoretical chemists have learned much about the properties and mechanisms associated with these strange and beautiful patterns, and they have begun to link their understanding with discoveries in biology, physics, engineering, and other fields. There remain many challenges for those who seek to weave together chemical reactions, transport phenomena, and external forces in new and exciting ways. (Abstract excerpts)

Stankiewicz, Johanna and Lars Henning Eckardt. Chemobiogenesis 2005 and Systems Chemistry Workshop. Angewandte Chemie. 45/342, 2006. Extraordinary insights into an innately dynamic materiality which leads to biological precursors are arising in central Europe as evidenced by this conference report. Leading researchers such as Peter Schuster, Eors Szathmary, Antonia Lazcano, Reza Ghadiri, and Steen Rasmussen were in attendance. A “prebiotic robustness” via the spontaneous coevolution of peptides and chemical energetics is seen to cause the emergence of homochirality (molecules of similar handedness) and nucleotides. Self-organizing catalytic networks will spawn non-Brownian self-reproducing vesicles. Such protocells can then be seen as a supersystem phase of a complex nonlinear chemistry. Chembiogenesis 2007 is to be held in Dubrovnik, Croatia in May.

Steinbock, Oliver, et al. The Fertile Physics of Chemical Gardens. Physics Today. March, 2016. As the lead image of this section conveys, a colorful summary of the project described in From Chemical Gardens to Chemobrionics by Laura Barge, et al, noted above. Here Steinbock, a Florida State University chemist, Julyan Cartwright, Spanish National Research Council systems theorist, and Laura Barge, a Jet Propulsion Laboratory astrobiologist, illustrate how intricate structural forms will emerge, via natural self-organizing propensities, from “inorganic” chemicals such as metal salt crystals in a sodium silicate solutions. A primordial analog might be the way life arose from similar hydrothermal vents. Are we altogether lately realizing that cosmic materiality is intrinsically fertile and pregnant, as Christian de Duve would say, with life and people?

The diverse chemical inventory that can lead to the formation of self-organized chemical garden structures clearly suggests universal principles that are more rooted in physics than in chemistry. We must understand the relevant physics not only to control the growth of chemical gardens but also to harness the many possible applications of self-assembling inorganic tubes that can incorporate diverse materials. (46) The self-organization of chemical garden formation is a nonequilibrium situation fueled by steep concentration gradients that in most other scenarios would quickly dissipate. That fundamental characteristic is shared with living systems that have mastered the art of controlling and utilizing such far-from-equilibrium conditions for materials synthesis and other engineering feats. (49)

Stulz, Eugen and Guido Clever. DNA in Supramolecular Chemistry and Nanotechnology. New York: Wiley, 2015. University of Southampton, UK, and Georg-August University, Germany chemists present a technical book-length edition of this novel nucleotide-based systems chemistry.

This book covers the emerging topic of DNA nanotechnology and DNA supramolecular chemistry in its broader sense. By taking DNA out of its biological role, this biomolecule has become a very versatile building block in materials chemistry, supramolecular chemistry and bio-nanotechnology. Many novel structures have been realized in the past decade, which are now being used to create molecular machines, drug delivery systems, diagnosis platforms or potential electronic devices. The book combines many aspects of DNA nanotechnology, including formation of functional structures based on covalent and non-covalent systems, DNA origami, DNA based switches, DNA machines, and alternative structures and templates. This broad coverage is very appealing since it combines both the synthesis of modified DNA as well as designer concepts to successfully plan and make DNA nanostructures.

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