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

3. Supramolecular Systems Chemistry

Breik, Keenan, et al. Programming Substrate-Independent Kinetic Barriers with Thermodynamic Binding Networks. arXiv:1810.12889. UT Austin and UC Davis researchers including David Doty press on with a frontier synthesis of chemical catalysis and energetic systems.

Engineering molecular systems that exhibit complex behavior requires the design of kinetic barriers. While programming such energy barriers seems to require knowledge of the specific substrate, we develop a novel substrate-independent approach. We extend the recently-developed model known as thermodynamic binding networks to programmable kinetic barriers that arise solely from the driving forces of bond formation and configurational entropy of separate complexes. Our model is robust such that several variations lead to equivalent energy barriers. Our results yield robust amplifiers using DNA strand displacement, a popular technology for engineering synthetic reaction pathways. (Abstract excerpt)

Brijder, Robert. Computing with Chemical Reaction Networks. Natural Computing. Online January, 2019. A Theoretical Computer Science Group, Hasselt University, Belgium researcher, in collaboration with David Doty (search RB and DD) and others, provides a tutorial survey of novel, growing realizations that chemical phenomena can be appreciated, and indeed availed, as another form of programmic operations.

Chemical reaction networks (CRNs) model the behavior of chemical reactions in well-mixed solutions and they can be designed to perform computations. In this tutorial we give an overview of various computational models for CRNs. Moreover, we discuss a method to implement arbitrary (abstract) CRNs in a test tube using DNA. Finally, we discuss relationships between CRNs and other models of computation.

Brijder, Robert, et al. Democratic, Existential, and Consensus-based Output Conventions in Stable Computation by Chemical Reaction Networks. Natural Computing. 17/1, 2018. In a technical paper RB Hasselt University, Belgium, David Doty UC Davis and David Soloveichik UT Austin metaphorically allude to an electoral polarity of aye and nay options as a good way to explain and represent chemical interactions.

We show that some natural output conventions for error-free computation in chemical reaction networks (CRN) lead to a common level of computational expressivity. Our main results are that the standard consensus-based output convention have equivalent computational power to (1) existence-based and (2) democracy-based output conventions. The CRNs using the former output convention have only “yes” voters, with the interpretation that the CRN’s output is yes if any voters are present and no otherwise. The CRNs using the latter output convention define output by majority vote among “yes” and “no” voters. These results support the thesis that the computational expressivity of error-free CRNs is intrinsic, not sensitive to arbitrary definitional choices. (Abstract) (universal democracy)

David Soloveichik Research Interests: Natural computing: models of computing inspired by nature. Computation is not a man-made phenomenon. From our brains to the regulatory networks of bacteria, nature provides fascinating examples of information processing, which is quite different from electronic computers. : Formal models of distributed computing help us to discover the potential and limits of chemical information processing. We study models inspired by self-assembly and chemical reaction networks.

Cao, Yudong, et al. Quantum Chemistry in the Age of Quantum Computing. arXiv:1812.09976. This is a 194 page, 404 citation paper by a 14 member team based at Alan Aspuru-Gizik’s University of Toronto lab with other credits at Harvard, MIT, University of Waterloo, Intel, Macquarie University and the Czech Republic Academy of Sciences. It is a worldwise, humankinder example of current integrations of micro quantum and macro classical realms into a seamless organic milieu. See also Quantum Computational Chemistry by this extended group at 1808.10402.

Practical challenges in simulating quantum systems on classical computers have been widely recognized in the quantum physics and chemistry communities over the past years. By manipulating quantum states of matter and taking advantage of their unique features such as superposition and entanglement, novel quantum computers can deliver accurate results for many important problems such as the electronic structure of molecules. This article is an overview of the algorithms and results that are relevant for quantum chemistry. (Abstract)

One of the most promising applications of quantum computing is solving classically intractable chemistry problems. This may enable the design of new materials, medicines, catalysts, or high temperature superconductors. As a result, quantum computational chemistry is rapidly emerging as an interdisciplinary knowledge of both quantum information and computational chemistry. (1808.10402 excerpt)

Cejkova, Jitka and Julyan Cartwright. Chembrionics and Systems Chemistry. ChemSystemsChem. 4/3, 2022. For this new Chemistry Europe journal, University of Chemistry and Technology, Prague, and University of Granada polychemists describe this novel approach which reveals another way that living beingness can be seem to spontaneously arise wherever it can (search JC, Cardoso).

Chemobrionics is a core topic of systems chemistry, as it plays a central role in understanding complex self-assembling systems and is related to work done on the origin of life as well as the design of complex materials. The ChemSystemsChem Special Collection on Chemobrionics showcases some of the most exciting work done in this field today. (Abstract)

Chepelev, Leonid and Michel Dumontier. Semantic Web Integration of Cheminformatics Resources with the SADI Framework. Journal of Cheminformatics. 3/16, 2011. As an example of the merging and cross-integration of systems biology and systems chemistry, Carleton University, Ottawa, information biologists describe a prototype “Semantic Automated Discovery and Integration” ontology to help fine-tune, up-grade, and reach a common viable online software “language.” Google Dumontier’s publication listing for more instances. And also check the above journal, PLoS Computational Biology, all the “–Omic’s” journals sprouting online, and so on. For another example see Chepelev, et al, “Self-Organizing Ontology of Biochemically Relevant Small Molecules” in BMC Bioinformatics (13/3, 2012).

The introduction and subsequent widespread availability of computers in the latter half of the 20th century has had an enormous impact on chemistry and related sciences. A wide range of problems which could only be addressed by tedious manual or semi-automated computation a few decades prior suddenly became readily accessible with computers. The explosion of the diversity of the various software packages addressing every aspect of chemistry that followed can only be compared, in relative terms, to the Cambrian explosion in species diversity. Myriads of file formats, programming languages, platforms, operating systems, programming paradigms, distribution models, and access methods have been employed in hundreds of largely-independent projects, each vying for widespread adoption and often offering a unique set of functionalities and features to target a specific subdomain or application of chemistry. (1)

Clark, Edward, et al. Semantic Closure Demonstrated by the Evolution of a Universal Constructor Architecture in an Artificial Chemistry. Journal of the Royal Society Interface. 14/20161033, 2017. As the Abstract alludes, University of York computer scientists Clark, Simon Hickinbotham, and Susan Stepney present a technical synthesis of computational methods applied to genetic phenomena. As these systems proceed they take on a guise of a chemical process which then results in a generative issue.

We present a novel stringmol-based artificial chemistry system modelled on the universal constructor architecture (UCA) first explored by von Neumann. In a UCA, machines interact with an abstract description of themselves to replicate by copying the abstract description and constructing the machines that the abstract description encodes. DNA-based replication follows this architecture, with DNA being the abstract description, the polymerase being the copier, and the ribosome being the principal machine in expressing what is encoded on the DNA. This architecture is semantically closed as the machine that defines what the abstract description means is itself encoded on that abstract description. We present a series of experiments with the stringmol UCA that show the evolution of the meaning of genomic material, allowing the concept of semantic closure and transitions between semantically closed states to be elucidated in the light of concrete examples. We present results where, for the first time in an in silico system, simultaneous evolution of the genomic material, copier and constructor of a UCA, giving rise to viable offspring. (Abstract)

Cragg, Peter. Supramolecular Chemistry. Dordrecht: Springer, 2010. A University of Brighton, School of Pharmacy and Biomolecular Sciences, chemist surveys this frontier field from an overall Introduction, Life as a Supramolecular Phenomenon, Artificial Cells, Enzyme Mimics, and Synthetic Bionanotechnology Medicine going forward.

Crespo-Otero, Rachel and Mario Barbatti. Recent Advances and Perspectives on Nonadiabatic Mixed Quantum-Classical Dynamics. Chemical Society Reviews. Online May, 2018. Queen Mary University of London and Aix Marseille University physical chemists review such current abilities to theoretically integrate these previously separate micro and macro domains as each contributes to a bio-physical and bio-chemical cosmic evolutionary genesis which can reach this late phenomenal retrospect. See also Ab Initio Quantum Molecular Dynamics by Basile Curchod and Todd Martinez in this same journal (118/7, 2018).

Queen Mary University of London and Aix Marseille University physical chemists review such current abilities to theoretically integrate these previously separate micro and macro domains as each contributes to a bio-physical and bio-chemical cosmic evolutionary genesis which can reach this late phenomenal retrospect. See also Ab Initio Quantum Molecular Dynamics by Basile Curchod and Todd Martinez in this same journal (118/7, 2018).

Dodziuk, Helena. Introduction to Supramolecular Chemistry. Dordrecht: Kluwer Academic, 2002. From Institute of Physical Chemistry, Polish Academy of Sciences, a survey in part of “the role of self-organization and self-association in the living nature.”

Doty, David and Shaopeng Zhu. Computational Complexity of Atomic Chemical Reaction Networks. arXiv:1702.05704. UC Davis computer scientists report a natural affinity between chemical phenomena, algorithmic processes, which are then further exemplified by genomic structures and dynamics. It is quite technical so we post three quotes. This active approach has an annual conference on “DNA Computing and Molecular Programming,” search Rondelez for DNA 2016. See also journals such as Natural Computing, Distributed Computing, Soft Computing, Acta Informatica, and Algorithms for Molecular Biology. An earlier paper of note is DNA as a Universal Substrate for Chemical Kinetics by David Soloveichik, Georg Seelig, and Erik Winfree (PNAS 107/5393, 2010). See also an update with the above title in Natural Computing (online June 2018).

Informally, a chemical reaction network is "atomic" if each reaction may be interpreted as the rearrangement of indivisible units of matter. We investigate the computational complexity of deciding whether a given network is atomic according to each of these definitions. Our first definition, primitive atomic, which requires each reaction to preserve the total number of atoms, is to shown to be equivalent to mass conservation. Since it is known that it can be decided in polynomial time whether a given chemical reaction network is mass-conserving, the equivalence gives an efficient algorithm to decide primitive atomicity. Another definition, subset atomic, further requires that all atoms are species. We show that deciding whether a given network is subset atomic is in NP, and the problem "is a network subset atomic with respect to a given atom set" is strongly NP-Complete. (Abstract excerpts)

A chemical reaction network is a set of reactions intended to model molecular species that interact, possibly combining or splitting in the process. The model is syntactically equivalent to Petri nets: molecules correspond to “tokens”, species correspond to “places”, reactions correspond to “transitions”, and configurations correspond to “marking.” (1) For 150 years, the model has been a popular language for describing natural chemicals that react in a well-mixed solution. Several recent wet-lab experiments demonstrate the systematic engineering of custom-designed chemical reactions, and it is known that in theory any set of reactions can be implemented by synthetic DNA complexes. Thus chemical reaction networks are now equally appropriate as a programming language that can be compiled into real chemicals. With advances in synthetic biology heralding a new era of sophisticated biomolecular engineering, chemical reaction networks will gain prominence as a natural high-level language for designing molecular control circuitry. (1-2)

Computational complexity theory is a branch of theoretical computer science that focuses on classifying computational problems according to their inherent difficulty. A computational problem is a task that is in principle amenable to being solved by a computer, which is equivalent to stating that the problem may be solved by mechanical application of mathematical steps, such as an algorithm. In computational complexity theory, NP is a complexity class used to describe certain types of decision problems. Informally, NP is the set of all decision problems for which the instances where the answer is "yes" have efficiently verifiable proofs. (Wikipedia edits)

Ghosh, Abhik and Paul Kiparsky. Grammar of the Elements. American Scientist. November-December, 2019. Once in a while, a truly unique contribution comes to light. Here an Arctic University of Norway chemist and a Stanford University linguist, each veteran scholars, make a good case that Dmitri Menddeleev’s periodic table drew inspiration for its form and phrases from Sanskrit. It seems that both he and Otto von Bohtlingk, who wrote a German edition about this ancient Indian script, lived in St. Petersburg in the 1870s and knew each other. Akin to Antoine Lavoisier who used linguistic metaphors, its tabular frame and generative grammar, traced to the 4th century BCE philologist Panini, served as an initial guide for sorting and arraying the 70 or so atomic elements at the time. See also Mendeleev’s Predictions: Success and Failure by Philip Stewart in Foundations of Chemistry (21/1, 2019), Challenges for the Periodic Systems of Elements by Guillermo Restrepo in Chemistry: A European Journal (November 2019), and Mendeleev and earlier The Periodic Table by Subhash Kak at arXiv:0411080. At its 150th anniversary, this deep affinity reveals an innate connection between chemical matter and linguistic forms, so as to infer a textual uniVerse which we peoples seem meant to learn, read and write.

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