Abstract:A previous analysis performed in our laboratory about the polynomial dependency of the atomic quantum self-similarity measures on the atomic number, together with recent publications on quantitative structure-properties relationships (QSPR), based on the number of molecular atoms, published by various authors, have driven us to show here that a simplified form of the fundamental quantum QSPR (QQSPR) equation, permits to theoretically demonstrate the important, but obvious, role of the number of atoms in a mole… Show more
“…The classical and quantum QSPR consequences of this fact, have been broadly discussed in a previous paper (Carbó-Dorca & Gallegos, 2009a), as the culmination of a wide set of studies on the modern structure of QQSPR fundamental equation and its connection with classical QSPR (Carbó-Dorca et al, 2009;Carbó-Dorca & Gallegos, 2009b;Carbó-Dorca, 2013a).…”
Section: Quantum Selfsimilaritymentioning
confidence: 98%
“…So far, this theoretical scheme corresponds to an actual alternative representation of the basic quantum QSPR abstract structure, which has been presented into the literature, since the first applicable descriptions of quantum similarity (Carbó-Dorca et al, 2009;Carbó-Dorca & Gallegos, 2009a;Carbó-Dorca, 2013a;Bultinck et al, 2005;Carbó et al, 1996;Carbó & Calabuig, 1990;1992a;1992b;Carbó-Dorca & Gallegos, 2009b;Carbó-Dorca, 2013b).…”
Section: Definition Of the Qqspr Operator And Its Action Over Dfmentioning
confidence: 99%
“…Also, once defined such an operator, for instance via an approximate computational procedure, one can calculate the corresponding expectation value α, attached to every QP DF vertex, by using the integral expression, the following references describe the evolution of theoretical and practical use of this technique with time (Bultinck, Gironés, & Carbó-Dorca, 2005;Carbó, Besalú, Amat, & Fradera, 1996;Carbó & Calabuig, 1990;1992a;1992b;Carbó-Dorca & Gallegos, 2009b;Carbó-Dorca, 2013b …”
Section: Introduction Quantum Similarity and Quantum Object Setsmentioning
confidence: 99%
“…Quantum similarity is theoretically and computationally based on such a quantum mechanical expectation value framework (Carbó & Calabuig, 1992a;Carbó-Dorca & Gallegos, 2009b;Carbó-Dorca, 2013b). This quantum similarity background important fact might be therefore also stated by means of the above integral (1).…”
Section: Introduction Quantum Similarity and Quantum Object Setsmentioning
The nature and origin of a fundamental quantum QSPR (QQSPR) equation are discussed. In principle, as any molecular structure can be associated to quantum mechanical density functions (DF), a molecular set can be reconstructed as a quantum multimolecular polyhedron (QMP), whose vertices are formed by each molecular DF.According to QQSPR theory, complicated kinds of molecular properties, like biological activity or toxicity, of molecular sets can be calculated via the quantum expectation value of an approximate Hermitian operator, which can be evaluated with the geometrical information contained in the attached QMP via quantum similarity matrices.Practical ways of solving the QQSPR problem from the point of view of QMP geometrical structure are provided.Such a development results into a powerful algorithm, which can be implemented within molecular design as an alternative to the current classical QSPR procedures.
“…The classical and quantum QSPR consequences of this fact, have been broadly discussed in a previous paper (Carbó-Dorca & Gallegos, 2009a), as the culmination of a wide set of studies on the modern structure of QQSPR fundamental equation and its connection with classical QSPR (Carbó-Dorca et al, 2009;Carbó-Dorca & Gallegos, 2009b;Carbó-Dorca, 2013a).…”
Section: Quantum Selfsimilaritymentioning
confidence: 98%
“…So far, this theoretical scheme corresponds to an actual alternative representation of the basic quantum QSPR abstract structure, which has been presented into the literature, since the first applicable descriptions of quantum similarity (Carbó-Dorca et al, 2009;Carbó-Dorca & Gallegos, 2009a;Carbó-Dorca, 2013a;Bultinck et al, 2005;Carbó et al, 1996;Carbó & Calabuig, 1990;1992a;1992b;Carbó-Dorca & Gallegos, 2009b;Carbó-Dorca, 2013b).…”
Section: Definition Of the Qqspr Operator And Its Action Over Dfmentioning
confidence: 99%
“…Also, once defined such an operator, for instance via an approximate computational procedure, one can calculate the corresponding expectation value α, attached to every QP DF vertex, by using the integral expression, the following references describe the evolution of theoretical and practical use of this technique with time (Bultinck, Gironés, & Carbó-Dorca, 2005;Carbó, Besalú, Amat, & Fradera, 1996;Carbó & Calabuig, 1990;1992a;1992b;Carbó-Dorca & Gallegos, 2009b;Carbó-Dorca, 2013b …”
Section: Introduction Quantum Similarity and Quantum Object Setsmentioning
confidence: 99%
“…Quantum similarity is theoretically and computationally based on such a quantum mechanical expectation value framework (Carbó & Calabuig, 1992a;Carbó-Dorca & Gallegos, 2009b;Carbó-Dorca, 2013b). This quantum similarity background important fact might be therefore also stated by means of the above integral (1).…”
Section: Introduction Quantum Similarity and Quantum Object Setsmentioning
The nature and origin of a fundamental quantum QSPR (QQSPR) equation are discussed. In principle, as any molecular structure can be associated to quantum mechanical density functions (DF), a molecular set can be reconstructed as a quantum multimolecular polyhedron (QMP), whose vertices are formed by each molecular DF.According to QQSPR theory, complicated kinds of molecular properties, like biological activity or toxicity, of molecular sets can be calculated via the quantum expectation value of an approximate Hermitian operator, which can be evaluated with the geometrical information contained in the attached QMP via quantum similarity matrices.Practical ways of solving the QQSPR problem from the point of view of QMP geometrical structure are provided.Such a development results into a powerful algorithm, which can be implemented within molecular design as an alternative to the current classical QSPR procedures.
“…In recent publications, it has been developed the theoretical background, leading into the establishment of a quantum quantitative structure–properties relations (QSPR) equation defined in molecular spaces, resulting from the quantum similarity framework development evolving in time. Recently, a basic concept for this endeavor appears grounded on the description of molecular quantum polyhedra .…”
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 perchlorobenzene within the set of chlorobenzenes and a typical quantum QSAR study on the popular Cramer steroid set.
Computation of density gradient quantum similarity integrals is analyzed, while comparing such integrals with overlap density quantum similarity measures. Gradient quantum similarity corresponds to another kind of numerical similarity assessment between a pair of molecular frames, which contrarily to the usual up to date quantum similarity definitions are not measures, that is: strictly positive definite integrals. As the density gradient quantum similarity integrals are defined as scalar products of three real functions, they appear to possess a richer structure than the corresponding positive definite density overlap quantum similarity measures, while preserving the overall similarity trends, when the molecular frames are relatively moved in three-dimensional space. Similarity indices are also studied when simple cases are analyzed in order to perform more comparisons with density overlap quantum similarity. Multiple gradient quantum similarity integrals are also defined. General GTO formulae are given. Numerical results within the atomic shell approximation (ASA) framework are presented as simple examples showing the new performances of the gradient density quantum similarity. Fortran 90 programs illustrating the proposed theoretical development can be downloaded from appropriate websites.
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