Abstract:This article presents a discussion about the formalism, which might be associated to a general Quantum quantitative structure–properties relations operator, appearing in a Boltzmann‐like exponential form, which is based in turn on the definition of the concept of thermal voltage, applied to thermally scaled electronic density functions. Three practical numerical examples are presented, corresponding to the calculation of the polarization angle in assorted chiral molecules, the estimation of fish toxicity for p… Show more
“…From the QS matrix, one can use theoretical and computational procedures, recently described in Refs. [44,79,80], to obtain atomic element QS coordinates such that the PT structure can be graphically observed or described with an as large dimension discrete vector as needed. See Appendix 2 for mathematical details.…”
Section: Multidimensional Aspects Of the Periodic Tablementioning
confidence: 99%
“…The main mathematical and algorithmic developments can be easily found in the Refs. [44,63,64,[69][70][71][72][73][74][75][76][77][78][79][80], where the interested readers can obtain specific details and peruse the theoretical development. When a set of quantum objects, in the present case the whole set or a subset of atoms in the PT, are associated one-toone to a set of quantum mechanical density functions (DF), one can talk about a quantum polyhedron, where each vertex is represented by the corresponding DF.…”
Section: Statistical-like Moments Of a Quantum Polyhedronmentioning
confidence: 99%
“…As mentioned in point (l), some preliminary rough work has been already performed on the PT.Now, the next purpose of this article is to set up a prospect using the state of the art in QS. Such new possibilities have been published not very far in time up to date …”
Section: Introductionmentioning
confidence: 99%
“…Now, the next purpose of this article is to set up a prospect using the state of the art in QS. Such new possibilities have been published not very far in time up to date …”
“…From the QS matrix, one can use theoretical and computational procedures, recently described in Refs. [44,79,80], to obtain atomic element QS coordinates such that the PT structure can be graphically observed or described with an as large dimension discrete vector as needed. See Appendix 2 for mathematical details.…”
Section: Multidimensional Aspects Of the Periodic Tablementioning
confidence: 99%
“…The main mathematical and algorithmic developments can be easily found in the Refs. [44,63,64,[69][70][71][72][73][74][75][76][77][78][79][80], where the interested readers can obtain specific details and peruse the theoretical development. When a set of quantum objects, in the present case the whole set or a subset of atoms in the PT, are associated one-toone to a set of quantum mechanical density functions (DF), one can talk about a quantum polyhedron, where each vertex is represented by the corresponding DF.…”
Section: Statistical-like Moments Of a Quantum Polyhedronmentioning
confidence: 99%
“…As mentioned in point (l), some preliminary rough work has been already performed on the PT.Now, the next purpose of this article is to set up a prospect using the state of the art in QS. Such new possibilities have been published not very far in time up to date …”
Section: Introductionmentioning
confidence: 99%
“…Now, the next purpose of this article is to set up a prospect using the state of the art in QS. Such new possibilities have been published not very far in time up to date …”
“…History of mathematical chemistry contains contributions of many outstanding scientists, such as A.T. Balaban, M. Randić, I. Gutman, N.Trinajstić, S.C. Basak, R. Carbó-Dorca, as well as many others [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15]. Mathematical chemistry [1] is the area of research engaged in novel applications of mathematics to chemistry, biochemistry, and biology.…”
The algorithm of building up a model for the biological activity of peptides as a mathematical function of a sequence of amino acids is suggested. The general scheme is the following: The total set of available data is distributed into the active training set, passive training set, calibration set, and validation set. The training (both active and passive) and calibration sets are a system of generation of a model of biological activity where each amino acid obtains special correlation weight. The numerical data on the correlation weights calculated by the Monte Carlo method using the CORAL software (http://www. insil ico.eu/coral ). The target function aimed to give the best result for the calibration set (not for the training set). The final checkup of the model is carried out with data on the validation set (peptides, which are not visible during the creation of the model). Described computational experiments confirm the ability of the approach to be a tool for the design of predictive models for the biological activity of peptides (expressed by pIC50).
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