Sorana D. Bolboaca

Comparison of Quantitative Structure-Activity Relationship Model Performances on Carboquinone Derivatives

Quantitative structure-activity relationship (qSAR) models are used to understand how the structure and activity of chemical compounds relate. In the present study, 37 carboquinone derivatives were evaluated and two different qSAR models were developed using members of the Molecular Descriptors Family (MDF) and the Molecular Descriptors Family on Vertices (MDFV). The usual parameters of regression models and the following estimators were defined and calculated in order to analyze the validity and to compare the models: Akaike?s information criteria (three parameters), Schwarz (or Bayesian) information criterion, Amemiya prediction criterion, Hannan-Quinn criterion, Kubinyi function, Steigers Z test, and Akaikes weights. The MDF and MDFV models proved to have the same estimation ability of the goodness-of-fit according to Steigers Z test. The MDFV model proved to be the best model for the considered carboquinone derivatives according to the defined information and prediction criteria, Kubinyi function, and Akaikes weights.

A Structural Informatics Study on Collagen

The study integrates knowledge resulting from structure–activity relationships analysis of amino acids with respect to the characterization of α1 and α2 type I collagen chains. Specifically, 15 amino acids and 14 properties were investigated and their structure–activity relationship models were obtained. The models were integrated into a web application and were used to predict the properties of a set of six amino acids. The similarities in α1 and α2 type I collagen chains has been investigated starting from the observed and predicted properties of amino acids by using two‐step cluster analysis.

Thermal Energy Efficiency Analysis for Residential Buildings

The paper presents an interactive software application, for the calculus of the heat flux demand in residential houses, based on international trends, standards and specifications in the fields of thermal energy in buildings. These types of calculations are considerable useful in the context of the large and constant interest on the subjects of energy conservation, reduction of polluting emissions and use on large scale of renewable energies. In order to reach the objective of the research, the heat flux demand was parameterized to identify each influence on the thermal energy consumption and costs. The development of the mathematical model had the aim to allow the minimization of the heat losses into the environment and to choose the correct thermal power for the residential houses heating devices. By the use of PHP language, the mathematical model has been transposed into a client-server application. The interactive software system has been validated through a case study and the obtained results were consistent and relevant. Based on the results it was possible to extract key conclusions about the parameters that contribute to the heat losses.

E-learning and e-evaluation: A case study

The aim of this paper is to present and analyze an e-learning and e-evaluation project, a framework for training, learning and evaluation. The project was initiated in 2001 in order to develop an educational environment able to bring together virtual experimental applications useful in undergraduate student education. Several e-evaluation systems were also created four years later. The paper describes the design of the e-learning and e-evaluation systems, and presents its applicability.

Molecular design and QSARs/QSPRs with molecular descriptors family.

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 Steigers 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.

A Structural Modelling Study on Marine Sediments Toxicity

Quantitative structure-activity relationship models were obtained by applying the Molecular Descriptor Family approach to eight ordnance compounds with different toxicity on five marine species (arbacia punctulata, dinophilus gyrociliatus, sciaenops ocellatus, opossum shrimp, and ulva fasciata). The selection of the best among molecular descriptors generated and calculated from the ordnance compounds structures lead to accurate monovariate models. The resulting models obtained for six endpoints proved to be accurate in estimation (the squared correlation coefficient varied from 0.8186 to 0.9997) and prediction (the correlation coefficient obtained in leave-one-out analysis varied from 0.7263 to 0.9984).

Linking Assessment to e-Learning in Microbiology and Toxicology for Undergraduate Students

An e-assessment formative multiple-choice questions experience using an auto-calibrated system is presented. The testing system is briefly described, and the testing and grading methodology used to certify abilities and knowledge in microbiology and toxicology achieved by undergraduate students are presented. The development methodology applied to multiple-choice questions bank has been introduced. The students were actively implied in creation of the multiple-choice questions bank. The paper highlighted the relationship between learning and assessment. The results had been shown the efficiency and effectiveness of the proposed assessment system for both students and teacher.

Toxicity caused by para-substituted phenols on Tetrahymena pyriformis: The structure-activity relationships

The toxicity of thirty para-substituted phenols on Tetrahymena pyriformis was modelled using an original methodology that uses the complex structural information of the compounds. Two models were built. The methodology allows atomic properties to be assigned to toxicity based on the selection of pairs of descriptors from the entire family, which is called Molecular Descriptors Family (MDF). One model has two independent structural descriptors and the other has four. The model with four descriptors proved to have high estimated and predictive abilities (over 97% of toxicity could be explained by structural information). The partial charge distribution by bonds (molecular topology) and space (molecular geometry) interaction proved to be related with the toxicity of para-substituted phenols on Tetrahymena pyriformis . The predictive ability of the model was tested by using the following methods: the cross-validation leave-one-out and the training versus test experiments . The comparisons among the models were performed using the correlated correlations method. The embedding of the complex information from the structure using MDF methodology can lead to further investigations of the mechanism of chemicals toxicity on Tetrahymena pyriformis .

Sugars and Sweeteners: Structure, Properties and in silico Modeling

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, Parkinsons disease, Alzheimers 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.

Computer-assisted instruction in evidence-based medicine: A pilot study

The paper presents a computer-based curriculum designed for evidence-based medicine (EBM) training of Romanian undergraduate students. A series of materials and cases were developed and integrated into a virtual training environment in order to provide the students with the opportunity to learn about and to assess their evidence-based medicine knowledge and skills. The interactive Web-based approach was efficient and effective in the EBM training of undergraduate students, thus suggesting that it could be the appropriate method for teaching evidence-based medicine.