Continuous Molecular Fields and the Concept of Molecular Co-Fields in Structure–Activity Studies

Baskin, Igor I.; Zhokhova, N. I.

doi:10.4155/fmc-2018-0360

Cited by 3 publications

(2 citation statements)

References 42 publications

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“…Therefore, every molecular vector can be considered as the condensation of another Euclidian-Banach space of arbitrary dimensions. This point of view has never been discussed in the theory of classical QSPR at any level, as far as the author is aware; see for example a modern assorted sample of references [68][69][70][71][72][73][74][75][76][77][78].…”

Section: The Qspr Framework As a Condensed Set Of Euclidian Vector Sp...mentioning

confidence: 99%

Quantum similarity and QSPR in Euclidean-, and Minkowskian–Banach spaces

Carbó‐Dorca

2023

J Math Chem

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This paper describes first how Euclidian- and Minkowskian–Banach spaces are related via the definition of a metric or signature vector. Also, it is discussed later on how these spaces can be generated using homothecies of the unit sphere or shell. Such possibility allows for proposing a process aiming at the dimension condensation in such spaces. The condensation of dimensions permits the account of the incompleteness of classical QSPR procedures, independently of whether the algorithm used is statistical bound or AI-neural network related. Next, a quantum QSPR framework within Minkowskian vector spaces is discussed. Then, a well-defined set of general isometric vectors is proposed, and connected to the set of molecular density functions generating the quantum similarity metric matrix. A convenient quantum QSPR algorithm emerges from this Minkowskian mathematical structure and isometry.

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Section: The Qspr Framework As a Condensed Set Of Euclidian Vector Sp...mentioning

confidence: 99%

Quantum similarity and QSPR in Euclidean-, and Minkowskian–Banach spaces

Carbó‐Dorca

2023

J Math Chem

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“…The development of visualisation prompted the re-optimization of the representation of molecular on accessing the databases. This feature creates new opportunities to utilise spatial information for molecular studies, such as quantitative structure -activity relationship and similarity analysis (Baskin & Zhokhova, 2019). Several accessible small molecule collections are available and provide start-up for the studies.…”

Section: What Is the Role Of Molecular Visualisation In Databases?mentioning

confidence: 99%

Database and Molecular Visualisation for Learning Media of Teaching Computational Chemistry/Pharmacy in Undergraduate Level

Syarif,

Supriatini

2023

AIJP

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Teaching chemistry in the information technology era has made it easy to understand topics related to the structure and properties of a molecule. One of the courses that intensively utilises information technology as a learning media is computational chemistry. This study measured student-learning outcomes during computational courses using molecular visualization software and databases. The instruments of this research are the results/answers of final exams and the assignments of the students in the semesters of 2018/2019 and 2019/2020 in the chemistry and pharmacy departments. A hundred students enrolled in these courses per year. The study was conducted for two years. The score results of six assignments for practical and four essay questions tests were analyzed. Students were asked to visualize molecules using the requested application in practical test. The assessment shows that project scores with the topic of using databases and visualization, a 'good' score profile of the results the two years. The student has ‘good’ score on small molecule database and visualization. The students mastered the Avogadro application more than VMD. Students generally understand to get data (computer files) from the database and then the visual constructions requested by the questions.

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QSPR in molecular spaces: ordering data, {de- & re-} constructing molecular similarity matrices, building their isometric vectors defining statistical-like momenta of molecular polyhedra, and analyzing the structure of a quantum QSPR operator

Carbó-Dorca

2023

J Math Chem

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A general review of quantum molecular similarity structure and applications is presented. The backbone of the discussion corresponds to the general problem of the data structure associated with the mathematical representation of a molecular set. How to standardize, and how to compare it to any other problem. This computational track describes the exact isometric vectors of the similarity matrix in a Minkowskian space. The further aim is to construct a set of origin-shifted vectors forming the vertices of a molecular polyhedron. From here, one can calculate a set of statistical-like momenta, providing a set of scalars that describe in a compact form the attached molecular set. Finally, the definition of a quantum QSPR operator permits building up a system of equations that can be further employed to determine the unknown properties of molecules in the original set. This last achievement leads to a quantum QSPR algorithm comparable with the classical QSPR counterpart but described in molecular space, not parameter space.

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Continuous Molecular Fields and the Concept of Molecular Co-Fields in Structure–Activity Studies

Cited by 3 publications

References 42 publications

Quantum similarity and QSPR in Euclidean-, and Minkowskian–Banach spaces

Quantum similarity and QSPR in Euclidean-, and Minkowskian–Banach spaces

Database and Molecular Visualisation for Learning Media of Teaching Computational Chemistry/Pharmacy in Undergraduate Level

QSPR in molecular spaces: ordering data, {de- & re-} constructing molecular similarity matrices, building their isometric vectors defining statistical-like momenta of molecular polyhedra, and analyzing the structure of a quantum QSPR operator

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