Binding Affinity of Triphenyl Acrylonitriles to Estrogen Receptors: Quantitative Structure-Activity Relationships

Bolboacă, Sorana D.; Marta, Monica Mihaela; Jäntschi, Lorentz

doi:10.2478/v10153-010-0005-2

Cited by 2 publications

(2 citation statements)

References 20 publications

(23 reference statements)

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“…The values of information criteria were used to compare the MLR models obtained by using different approaches on the same dataset of compounds. The lowest values of information criteria and the highest FIT function obtained for MDF QSAR/QSPR models compared to previously reported models showed the performances of the MDF approach [28,29,30]. The MDF methodology opens a new low-cost pathway in understanding the link between the chemical structure of compounds and their property/activity, the investigation of already known compounds as well as in the discovery of new compounds.…”

Section: Resultsmentioning

confidence: 78%

“…The structural information is collected by various molecular descriptors (2D descriptors [17][18][19][20][21][22]). The following methods were introduced in order to include structural 3D information in QSARs/QSPRs: CoMFAcomparative molecular field analysis and its variants CoMSIA (MSIA -molecular similarity indices Analysis) [23]; ▪ WHIM -weighted holistic invariant molecular (and its variant MS-WHIM -molecular surface WHIM) [24];▪ MTDminimal topological distance (and its variant MSD, S -steric) [25]; ▪ FPIF -fragmental property index family [26]; ▪ MDF -molecular descriptors family [27]; ▪ MDFV -molecular descriptors family on vertices [28][29][30]; ▪ TOPS-MODEtopological sub-structural molecular design [31][32][33][34][35], ▪ other approaches [36][37][38][39]. The selection of descriptors [40] is as important in QSAR/QSPR analysis as the statistical method (regression method [41,42], factor analysis [43], discriminant analysis [44], principal component analysis [45], cluster analysis [46] applied using genetic algorithms (GAs) [47] and/or neural network [48]) applied to identify the structure-activity/property relationship.…”

Section: Introductionmentioning

confidence: 99%

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Molecular Design and QSARs/QSPRs with Molecular Descriptors Family

Bolboacă¹,

Jäntschi²,

Diudea

2013

CAD

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The aim of the present paper is to present the methodology of the molecular descriptors family (MDF) as an integrative tool in molecular modeling and its abilities as a multivariate QSAR/QSPR modeling tool. An algorithm for extracting useful information from the topological and geometrical representation of chemical compounds was developed and integrated to calculate MDF members. The MDF methodology was implemented and the software is available online (http://l.academicdirect.org/Chemistry/SARs/MDF_SARs/). This integrative tool was developed in order to maximize performance, functionality, efficiency and portability. The MDF methodology is able to provide reliable and valid multiple linear regression models. Furthermore, in many cases, the MDF models were better than the published results in the literature in terms of correlation coefficients (statistically significant Steiger's Z test at a significance level of 5%) and/or in terms of values of information criteria and Kubinyi function. The MDF methodology developed and implemented as a platform for investigating and characterizing quantitative relationships between the chemical structure and the activity/property of active compounds was used on more than 50 study cases. In almost all cases, the methodology allowed obtaining of QSAR/QSPR models improved in explanatory power of structure-activity and structure-property relationships. The algorithms applied in the computation of geometric and topological descriptors (useful in modeling physicochemical or biological properties of molecules) and those used in searching for reliable and valid multiple linear regression models certain enrich the pool of low-cost low-time drug design tools.

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Section: Resultsmentioning

confidence: 78%

Section: Introductionmentioning

confidence: 99%

Molecular Design and QSARs/QSPRs with Molecular Descriptors Family

Bolboacă¹,

Jäntschi²,

Diudea

2013

CAD

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Sugars and Sweeteners: Structure, Properties and In Silico Modeling

Janežič

Jäntschi

Bolboacă

2020

CMC

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Several studies report the effects of excessive use of sugars and sweeteners in the diet. These include obesity, cardiac diseases, diabetes, and even lymphomas, leukemias, cancers of the bladder and brain, chronic fatigue syndrome, Parkinson's disease, Alzheimer's disease, multiple sclerosis, autism, and systemic lupus. On the other hand, each sugar and sweetener has a distinct metabolic assimilation process, and its chemical structure plays an important role in this process. Several scientific papers present the biological effects of the sugars and sweeteners in relation to their chemical structure. One important issue dealing with the sugars is the degree of similarity in their structures, focusing mostly on optical isomerism. Finding and developing new sugars and sweeteners with desired properties is an emerging research area, in which in silico approaches play an important role.

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Binding Affinity of Triphenyl Acrylonitriles to Estrogen Receptors: Quantitative Structure-Activity Relationships

Cited by 2 publications

References 20 publications

Molecular Design and QSARs/QSPRs with Molecular Descriptors Family

Molecular Design and QSARs/QSPRs with Molecular Descriptors Family

Sugars and Sweeteners: Structure, Properties and In Silico Modeling

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