Modelling Toxicity using Molecular Quantum Similarity Measures

Abstract

In this work, a general procedure for the application of Molecular Quantum Similarity Measures (MQSM) into the Quantitative Structure-Toxicity Relationships (QSTR) field is presented. The methodology is presented from its theoretical background, beginning with the formulation of MQSM and the role of density functions. Other topics, like molecular modelling, electronic density fitting, similarity scaling and molecular superposition are also analysed. The theoretical part is complemented with three different application examples dealing with acute aquatic toxicity related to different fish species. The molecular sets are constituted by different kinds of benzene derivatives. Acceptable correlations are obtained for the aquatic toxicity using quantum similarity derived descriptors, allowing a fairly confident classification of the studied compounds according to their toxicity level.

Understanding the Polar Character Trend in a Series of Diels-Alder Reactions Using Molecular Quantum Similarity and Chemical Reactivity Descriptors

“…Overlap integral is involving the AB between the electronic density of the molecules A and B, and AA and BB are selfsimilarity of the molecules A and B, respectively [65]; using this framework the quantum similarity indexes are defined. In the QS framework the axiomatic properties of the Euclidean distance can be mentioned and defined according to M. Deza and E. Deza [66] as follows: let H be a set.…”

Assessing the State of an Organism and Toxicity of Substances Using Biochemical Indicators

“…Понимание молекулярных механизмов токсичности боль-шинства веществ пока не достигнуто, хотя наря-ду с экспериментальными исследованиями для анализа химических и биологических объектов и явлений и определения потенциально токси-ческого влияния различных соединений на ор-ганизм разработан и используется ряд теорети-ческих подходов. Например, анализ распределе-ний и тестовых данных Yuan, Yin, 2009], топологические индексы , количественные связи между структурой и активностью (Quantitative Structure-Activity Relations (QSAR)) [Tantra et al, 2015], гистограммы , измерения молекулярного квантового подобия [Gironés, Carbó-Dorca, 2006] и другие методы [Nigsch et al, 2009;Valerio, 2009]. Так или иначе, оценка влияния токсикан-тов различной природы на состояние организма и оценка степени их токсичности является важ-ной и нетривиальной проблемой.…”

Scale Alpha and Beta of Quantitative Convergence and Chemical Reactivity Analysis in Dual Cholinesterase/Monoamine Oxidase Inhibitors for the Alzheimer Disease Treatment Using Density Functional Theory (DFT)

“…First, one can hope that theoretical descriptors based on quantum similarity (QS) [17][18][19][20][21][22][23][24] and the Density Functional Theory (DFT) [25] can be used to get insights into the factors determining exact nature of the biological activity and selectivity of cholinesterase/monoamine oxidase inhibition and its interactions or at least trends, as to what factors affect the structural properties of these inhibitors molecules.…”

“…The similarity index concept was originally proposed from the perspective of quantum chemistry by Carbó and coworkers [17][18][19][20][21][22][23][24]. Similarity concepts is an omnipresent concept that permeates almost every chemistry field and other scientific fields such as physics, biology, and biochemistry among others.…”

“…From the similarity or dissimilarity concept it is possible to obtain vital information of molecular designers, who are molecular designers within the drugdevelopment context, and the molecular similarity formalism has been proved to be one of the most significant computational tools that can be used to supply novel design ideas in order to get new drugs. The present work is concerned with such methodology that is based on similarity indexes computed from molecular fields using Carbó approach [17][18][19][20][21][22][23][24].…”