Theorems on Molecular Shape-Similarity Descriptors:  External T-Plasters and Interior T-Aggregates

Mezey, Paul G.

doi:10.1021/ci9600263

Cited by 14 publications

(5 citation statements)

References 50 publications

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“…The recently proven Holographic Electron Density Theorem [74] states that within any boundary-less molecular electron density cloud in a non-degenerate ground electronic state, any nonzero volume piece of the electron density cloud contains the complete information about the entire molecule. According to the classic and less powerful Hohenberg-Kohn Theorem, the entire electron density determines the energy of the molecule, whereas according to the Holographic Electron Density Theorem the entire electron density is not needed and any small nonzero volume piece of the electron density is already sufficient to determine the energy (and other properties) of the molecule.…”

Section: Electron Density Theorems and Molecular Similaritymentioning

confidence: 99%

Approaches to Measure Chemical Similarity – a Review

2003

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Although the concept of similarity is a convenient for humans, a formal definition of similarity between chemical compounds is needed to enable automatic decision‐making. The objective of similarity measures in toxicology and drug design is to allow assessment of chemical activities. The ideal similarity measure should be relevant to the activity of interest. The relevance could be established by exploiting the knowledge about fundamental chemical and biological processes responsible for the activity. Unfortunately, this knowledge is rarely available and therefore different approximations have been developed based on similarity between structures or descriptor values. Various methods are reviewed, ranging from two‐dimensional, three‐dimensional and field approaches to recent methods based on “Atoms in Molecules” theory. All these methods attempt to describe chemical compounds by a set of numerical values and define some means for comparison between them. The review provides analysis of potential pitfalls of this methodology – loss of information in the representations of molecular structures – the relevance of a particular representation and chosen similarity measure to the activity. A brief review of known methods for descriptor selection is also provided. The popular “neighborhood behavior” principle is criticized, since proximity with respect to descriptors does not necessarily mean proximity with respect to activity. Structural similarity should also be used with care, as it does not always imply similar activity, as shown by examples. We remind that similarity measures and classification techniques based on distances rely on certain data distribution assumptions. If these assumptions are not satisfied for a given dataset, the results could be misleading. A discussion on similarity in descriptor space in the context of applicability domain assessment of QSAR models is also provided. Finally, it is shown that descriptor based similarity analysis is prone to errors if the relationship between the activity and the descriptors has not been previously established. A justification for the usage of a particular similarity measure should be provided for every specific activity by expert knowledge or derived by data modeling techniques.

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Section: Electron Density Theorems and Molecular Similaritymentioning

confidence: 99%

Approaches to Measure Chemical Similarity – a Review

2003

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“…Since the 1960s, the rapid development of quantum chemical methods based on quantum mechanics (QM) has made it possible to calculate the electronic structure and associated properties of molecules, even for large systems with chemical accuracy . Many attempts , have been made to develop descriptors or models for the characterization of the molecular similarity based on the results of quantum chemical calculations, referring to the fact that the wave function and electron density contain all of the information related to energy about a molecule in question. Quantum chemical descriptors can be divided into two major categories, which describe either the overall molecule including HOMO and LUMO energies, dipole moments, total energy, heat of formation, and ionization potential or the fragments/substituents of a molecule like the net atomic charge .…”

Section: Introductionmentioning

confidence: 99%

Characterizing Chemical Similarity with Vibrational Spectroscopy: New Insights into the Substituent Effects in Monosubstituted Benzenes

2017

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A novel approach is presented to assess chemical similarity based the local vibrational mode analysis developed by Konkoli and Cremer. The local mode frequency shifts are introduced as similarity descriptors that are sensitive to any electronic structure change. In this work, 59 different monosubstituted benzenes are compared. For a subset of 43 compounds, for which experimental data was available, the ortho-/para- and meta-directing effect in electrophilic aromatic substitution reactions could be correctly reproduced, proving the robustness of the new similarity index. For the remaining 16 compounds, the directing effect was predicted. The new approach is broadly applicable to all compounds for which either experimental or calculated vibrational frequency information is available.

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“…4 show that 3D Hahn performs slowest and has lowest value of intra-class variance ratio among other 3D moments, although it requires less memory than Zernike moments and its classification accuracy is higher than 3D complex moments. The slow performance of 3D Hahn is attributed to its polynomial computation which is time consuming, despite using the recursive relationship shown in ( 36)- (41). Since the classification accuracy is the primary interest of this study, it should also be validated statistically.…”

Section: Resultsmentioning

confidence: 99%

“…In the QShAR domain itself, various molecular shape representation techniques have been proposed [38], [41]. Meanwhile, in pattern recognition problem, there are many shape representations or description techniques have been explored to extract the features from the object.…”

Section: A Existing 3d Moments Techniquesmentioning

confidence: 99%

Using 3D Hahn Moments as A Computational Representation of ATS Drugs Molecular Structure

Pratama

Muda

Choo

et al. 2020

Advances in Intelligent Systems and Computing

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The campaign against drug abuse is fought by all countries, most notably on ATS drugs. The technical limitations of the current test kits to detect new brand of ATS drugs present a challenge to law enforcement authorities and forensic laboratories. Meanwhile, new molecular imaging devices which allowed mankind to characterize the physical 3D molecular structure have been recently introduced, and it can be used to remedy the limitations of existing drug test kits. Thus, a new type of 3D molecular structure representation technique should be developed to cater the 3D molecular structure acquired physically using these molecular imaging devices. One of the applications of image processing methods to represent a 3D image is 3D moments, and this study formulates a new 3D moments technique, namely 3D Hahn moments, to represent the 3D molecular structure of ATS drugs. The performance of the proposed technique was analysed using drug chemical structures obtained from UNODC for the ATS drugs, while non-ATS drugs are obtained randomly from ChemSpider database. The evaluation shows the technique is qualified to be further explored in the future works to be fully compatible with ATS drug identification domain.

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Theorems on Molecular Shape-Similarity Descriptors: External T-Plasters and Interior T-Aggregates

Cited by 14 publications

References 50 publications

Approaches to Measure Chemical Similarity – a Review

Approaches to Measure Chemical Similarity – a Review

Characterizing Chemical Similarity with Vibrational Spectroscopy: New Insights into the Substituent Effects in Monosubstituted Benzenes

Using 3D Hahn Moments as A Computational Representation of ATS Drugs Molecular Structure

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