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Special Issue "The Fuzziness in Molecular, Supramolecular, and Systems Chemistry"

A special issue of Molecules (ISSN 1420-3049). This special issue belongs to the section "Physical Chemistry".

Deadline for manuscript submissions: closed (30 June 2019).

Special Issue Editor

Dr. Pier Luigi Luigi Gentili
E-Mail Website
Guest Editor
Department of Chemistry, Biology, and Biotechnology; University of Perugia, 06123 Perugia, Italy.
Tel. (+39) 075-585-5573
Interests: the fuzziness of the molecular world; chemical artificial intelligence; complex systems; systems chemistry; natural computing; neuromorphic engineering; computing by molecules; fuzzy logic; binary logic; oscillating reactions; hydrodynamics; chaos
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Special Issue Information

Dear Colleagues,

Fuzzy Logic is a good model for the human ability to compute with words. It is based on the theory of Fuzzy set. A Fuzzy set is different from a classical set because it breaks the Law of the Excluded Middle. In fact, an item may belong to a Fuzzy set and its complement at the same time and with the same or different degree of membership. The degree of membership of an item to a Fuzzy set can be any real number included between 0 and 1. This property allows dealing with all those statements of which truths are a matter of degree. Fuzzy logic is playing a relevant role in the field of Artificial Intelligence because it enables making decisions in complex situations, where there are many intertwined variables involved. Traditionally, Fuzzy logic is implemented through software on a computer or, even better, through analog electronic circuits. Recently, the idea of using molecules and chemical reactions for processing Fuzzy logic is blooming. In fact, the molecular word is fuzzy in its essence. The overlapping of quantum states, on the one hand, and the conformational heterogeneity of large molecules, on the other, enable context-specific functions to emerge in response to changing environmental conditions. Moreover, analog input–output relationships, involving not only electrical but also other physical and chemical variables can be exploited to build Fuzzy Logic Systems. The development of “Fuzzy Chemical Systems” is tracing a new path in the field of Artificial Intelligence. Such new path shows that Artificial Intelligent Systems can be implemented not only through software and electronic circuits but also through solutions of properly chosen chemical compounds. The design of Chemical Artificial Intelligent Systems and Chemical Robots promises to have a significant impact on science, medicine, economy, security, and well-being. Therefore, it is my great pleasure to announce a Special Issue of Molecules entitled “The Fuzziness in Molecular, Supramolecular, and Systems Chemistry.” All researchers who experience the Fuzziness of the molecular world or use Fuzzy logic to understand Chemical Complex Systems are warmly invited to contribute to this Special Issue by submitting research papers or reviews. This Special Issue has the ambition of gathering the brilliant ideas of the principal investigators in this field and promoting the generation of a research network for further scientific collaborations. 

Dr. Pier Luigi Gentili
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Molecules is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • The Fuzziness in Molecular Computing
  • The Fuzziness of Proteins
  • The Fuzziness of DNA/RNA and their Hybridization Reactions
  • Supramolecular Fuzziness
  • The Fuzziness in Systems Chemistry
  • The Fuzziness of Cellular Processes
  • The Fuzziness in Chemical Artificial Intelligent Systems
  • The Fuzziness in Chemical Robots
  • The Fuzziness of the Quantum World
  • The Fuzziness of Quantum Computation
  • Fuzzy Logic Systems and Complex Systems
  • Fuzzy Logic and Analytical Chemistry
  • Fuzzy Cognitive Maps in Chemistry

Published Papers (6 papers)

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Open AccessArticle
“Transitivity”: A Code for Computing Kinetic and Related Parameters in Chemical Transformations and Transport Phenomena
Molecules 2019, 24(19), 3478; https://doi.org/10.3390/molecules24193478 - 25 Sep 2019
Cited by 1
Abstract
The Transitivity function, defined in terms of the reciprocal of the apparent activation energy, measures the propensity for a reaction to proceed and can provide a tool for implementing phenomenological kinetic models. Applications to systems which deviate from the Arrhenius law at low [...] Read more.
The Transitivity function, defined in terms of the reciprocal of the apparent activation energy, measures the propensity for a reaction to proceed and can provide a tool for implementing phenomenological kinetic models. Applications to systems which deviate from the Arrhenius law at low temperature encouraged the development of a user-friendly graphical interface for estimating the kinetic and thermodynamic parameters of physical and chemical processes. Here, we document the Transitivity code, written in Python, a free open-source code compatible with Windows, Linux and macOS platforms. Procedures are made available to evaluate the phenomenology of the temperature dependence of rate constants for processes from the Arrhenius and Transitivity plots. Reaction rate constants can be calculated by the traditional Transition-State Theory using a set of one-dimensional tunneling corrections (Bell (1935), Bell (1958), Skodje and Truhlar and, in particular, the deformed ( d -TST) approach). To account for the solvent effect on reaction rate constant, implementation is given of the Kramers and of Collins–Kimball formulations. An input file generator is provided to run various molecular dynamics approaches in CPMD code. Examples are worked out and made available for testing. The novelty of this code is its general scope and particular exploit of d -formulations to cope with non-Arrhenius behavior at low temperatures, a topic which is the focus of recent intense investigations. We expect that this code serves as a quick and practical tool for data documentation from electronic structure calculations: It presents a very intuitive graphical interface which we believe to provide an excellent working tool for researchers and as courseware to teach statistical thermodynamics, thermochemistry, kinetics, and related areas. Full article
(This article belongs to the Special Issue The Fuzziness in Molecular, Supramolecular, and Systems Chemistry)
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Open AccessArticle
Hardware Realization of the Pattern Recognition with an Artificial Neuromorphic Device Exhibiting a Short-Term Memory
Molecules 2019, 24(15), 2738; https://doi.org/10.3390/molecules24152738 - 28 Jul 2019
Abstract
Materials exhibiting memory or those capable of implementing certain learning schemes are the basic building blocks used in hardware realizations of the neuromorphic computing. One of the common goals within this paradigm assumes the integration of hardware and software solutions, leading to a [...] Read more.
Materials exhibiting memory or those capable of implementing certain learning schemes are the basic building blocks used in hardware realizations of the neuromorphic computing. One of the common goals within this paradigm assumes the integration of hardware and software solutions, leading to a substantial efficiency enhancement in complex classification tasks. At the same time, the use of unconventional approaches towards signal processing based on information carriers other than electrical carriers seems to be an interesting trend in the design of modern electronics. In this context, the implementation of light-sensitive elements appears particularly attractive. In this work, we combine the abovementioned ideas by using a simple optoelectronic device exhibiting a short-term memory for a rudimentary classification performed on a handwritten digits set extracted from the Modified National Institute of Standards and Technology Database (MNIST)(being one of the standards used for benchmarking of such systems). The input data was encoded into light pulses corresponding to black (ON-state) and white (OFF-state) pixels constituting a digit and used in this form to irradiate a polycrystalline cadmium sulfide electrode. An appropriate selection of time intervals between pulses allows utilization of a complex kinetics of charge trapping/detrapping events, yielding a short-term synaptic-like plasticity which in turn leads to the improvement of data separability. To the best of our knowledge, this contribution presents the simplest hardware realization of a classification system capable of performing neural network tasks without any sophisticated data processing. Full article
(This article belongs to the Special Issue The Fuzziness in Molecular, Supramolecular, and Systems Chemistry)
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Open AccessArticle
Sequence-Specific DNA Binding by Noncovalent Peptide–Azocyclodextrin Dimer Complex as a Suitable Model for Conformational Fuzziness
Molecules 2019, 24(13), 2508; https://doi.org/10.3390/molecules24132508 - 09 Jul 2019
Abstract
Transcription factors are proteins lying at the endpoint of signaling pathways that control the complex process of DNA transcription. Typically, they are structurally disordered in the inactive state, but in response to an external stimulus, like a suitable ligand, they change their conformation, [...] Read more.
Transcription factors are proteins lying at the endpoint of signaling pathways that control the complex process of DNA transcription. Typically, they are structurally disordered in the inactive state, but in response to an external stimulus, like a suitable ligand, they change their conformation, thereby activating DNA transcription in a spatiotemporal fashion. The observed disorder or fuzziness is functionally beneficial because it can add adaptability, versatility, and reversibility to the interaction. In this context, mimetics of the basic region of the GCN4 transcription factor (Tf) and their interaction with dsDNA sequences would be suitable models to explore the concept of conformational fuzziness experimentally. Herein, we present the first example of a system that mimics the DNA sequence-specific recognition by the GCN4 Tf through the formation of a non- covalent tetra-component complex: peptide–azoβ-CyD(dimer)–peptide–DNA. The non-covalent complex is constructed on the one hand by a 30 amino acid peptide corresponding to the basic region of GCN4 and functionalized with an adamantane moiety, and on the other hand an allosteric receptor, the azoCyDdimer, that has an azobenzene linker connecting two β-cyclodextrin units. The azoCyDdimer responds to light stimulus, existing as two photo-states: the first thermodynamically stable with an E:Z isomer ratio of 95:5 and the second obtained after irradiation with ultraviolet light, resulting in a photostationary state with a 60:40 E:Z ratio. Through electrophoretic shift assays and circular dichroism spectroscopy, we demonstrate that the E isomer is responsible for dimerization and recognition. The formation of the non-covalent tetra component complex occurs in the presence of the GCN4 cognate dsDNA sequence (′5-..ATGA cg TCAT..-3′) but not with (′5-..ATGA c TCAT..-3′) that differs in only one spacing nucleotide. Thus, we demonstrated that the tetra-component complex is formed in a specific manner that depends on the geometry of the ligand, the peptide length, and the ds DNA sequence. We hypothesized that the mechanism of interaction is sequential, and it can be described by the polymorphism model of static fuzziness. We argue that chemically modified peptides of the GCN4 Tf are suitable minimalist experimental models to investigate conformational fuzziness in protein–DNA interactions. Full article
(This article belongs to the Special Issue The Fuzziness in Molecular, Supramolecular, and Systems Chemistry)
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Open AccessPerspective
Supramolecular Fuzziness of Intracellular Liquid Droplets: Liquid–Liquid Phase Transitions, Membrane-Less Organelles, and Intrinsic Disorder
Molecules 2019, 24(18), 3265; https://doi.org/10.3390/molecules24183265 - 07 Sep 2019
Abstract
Cells are inhomogeneously crowded, possessing a wide range of intracellular liquid droplets abundantly present in the cytoplasm of eukaryotic and bacterial cells, in the mitochondrial matrix and nucleoplasm of eukaryotes, and in the chloroplast’s stroma of plant cells. These proteinaceous membrane-less organelles (PMLOs) [...] Read more.
Cells are inhomogeneously crowded, possessing a wide range of intracellular liquid droplets abundantly present in the cytoplasm of eukaryotic and bacterial cells, in the mitochondrial matrix and nucleoplasm of eukaryotes, and in the chloroplast’s stroma of plant cells. These proteinaceous membrane-less organelles (PMLOs) not only represent a natural method of intracellular compartmentalization, which is crucial for successful execution of various biological functions, but also serve as important means for the processing of local information and rapid response to the fluctuations in environmental conditions. Since PMLOs, being complex macromolecular assemblages, possess many characteristic features of liquids, they represent highly dynamic (or fuzzy) protein–protein and/or protein–nucleic acid complexes. The biogenesis of PMLOs is controlled by specific intrinsically disordered proteins (IDPs) and hybrid proteins with ordered domains and intrinsically disordered protein regions (IDPRs), which, due to their highly dynamic structures and ability to facilitate multivalent interactions, serve as indispensable drivers of the biological liquid–liquid phase transitions (LLPTs) giving rise to PMLOs. In this article, the importance of the disorder-based supramolecular fuzziness for LLPTs and PMLO biogenesis is discussed. Full article
(This article belongs to the Special Issue The Fuzziness in Molecular, Supramolecular, and Systems Chemistry)
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Open AccessFeature PaperPerspective
Towards a Stochastic Paradigm: From Fuzzy Ensembles to Cellular Functions
Molecules 2018, 23(11), 3008; https://doi.org/10.3390/molecules23113008 - 17 Nov 2018
Cited by 3
Abstract
The deterministic sequence → structure → function relationship is not applicable to describe how proteins dynamically adapt to different cellular conditions. A stochastic model is required to capture functional promiscuity, redundant sequence motifs, dynamic interactions, or conformational heterogeneity, which facilitate the decision-making in [...] Read more.
The deterministic sequence → structure → function relationship is not applicable to describe how proteins dynamically adapt to different cellular conditions. A stochastic model is required to capture functional promiscuity, redundant sequence motifs, dynamic interactions, or conformational heterogeneity, which facilitate the decision-making in regulatory processes, ranging from enzymes to membraneless cellular compartments. The fuzzy set theory offers a quantitative framework to address these problems. The fuzzy formalism allows the simultaneous involvement of proteins in multiple activities, the degree of which is given by the corresponding memberships. Adaptation is described via a fuzzy inference system, which relates heterogeneous conformational ensembles to different biological activities. Sequence redundancies (e.g., tandem motifs) can also be treated by fuzzy sets to characterize structural transitions affecting the heterogeneous interaction patterns (e.g., pathological fibrillization of stress granules). The proposed framework can provide quantitative protein models, under stochastic cellular conditions. Full article
(This article belongs to the Special Issue The Fuzziness in Molecular, Supramolecular, and Systems Chemistry)
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Open AccessFeature PaperPerspective
The Fuzziness of the Molecular World and Its Perspectives
Molecules 2018, 23(8), 2074; https://doi.org/10.3390/molecules23082074 - 19 Aug 2018
Cited by 4
Abstract
Scientists want to comprehend and control complex systems. Their success depends on the ability to face also the challenges of the corresponding computational complexity. A promising research line is artificial intelligence (AI). In AI, fuzzy logic plays a significant role because it is [...] Read more.
Scientists want to comprehend and control complex systems. Their success depends on the ability to face also the challenges of the corresponding computational complexity. A promising research line is artificial intelligence (AI). In AI, fuzzy logic plays a significant role because it is a suitable model of the human capability to compute with words, which is relevant when we make decisions in complex situations. The concept of fuzzy set pervades the natural information systems (NISs), such as living cells, the immune and the nervous systems. This paper describes the fuzziness of the NISs, in particular of the human nervous system. Moreover, it traces three pathways to process fuzzy logic by molecules and their assemblies. The fuzziness of the molecular world is useful for the development of the chemical artificial intelligence (CAI). CAI will help to face the challenges that regard both the natural and the computational complexity. Full article
(This article belongs to the Special Issue The Fuzziness in Molecular, Supramolecular, and Systems Chemistry)
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