Search results for "Quantitative structure"
showing 10 items of 192 documents
LEGO-based generalized set of two linear algebraic 3D bio-macro-molecular descriptors: Theory and validation by QSARs
2019
Abstract Novel 3D protein descriptors based on bilinear, quadratic and linear algebraic maps in R n are proposed. The latter employs the kth 2-tuple (dis) similarity matrix to codify information related to covalent and non-covalent interactions in these biopolymers. The calculation of the inter-amino acid distances is generalized by using several dis-similarity coefficients, where normalization procedures based on the simple stochastic and mutual probability schemes are applied. A new local-fragment approach based on amino acid-types and amino acid-groups is proposed to characterize regions of interest in proteins. Topological and geometric macromolecular cutoffs are defined using local and…
Search of Chemical Scaffolds for Novel Antituberculosis Agents
2005
3 A method to identify chemical scaffolds potentially active against Mycobacterium tuberculosis is presented. The molecular features of a set of structurally heterogeneous antituberculosis drugs were coded by means of structural invariants. Three tech- niques were used to obtain equations able to model the antituberculosis activity: linear discriminant analysis, multilinear re- gression, and shrinkage estimation-ridge regression. The model obtained was statistically validated through leave-n-out test, and an external set and was applied to a database for the search of new active agents. The selected compounds were assayed in vitro, and among those identified as active stand reserpine, N,N,N…
Estimation of ADME Properties in Drug Discovery: Predicting Caco-2 Cell Permeability Using Atom-Based Stochastic and Non-stochastic Linear Indices
2007
The in vitro determination of the permeability through cultured Caco-2 cells is the most often-used in vitro model for drug absorption. In this report, we use the largest data set of measured P(Caco-2), consisting of 157 structurally diverse compounds. Linear discriminant analysis (LDA) was used to obtain quantitative models that discriminate higher absorption compounds from those with moderate-poorer absorption. The best LDA model has an accuracy of 90.58% and 84.21% for training and test set. The percentage of good correlation, in the virtual screening of 241 drugs with the reported values of the percentage of human intestinal absorption (HIA), was greater than 81%. In addition, multiple …
Preparation and Promotion of Fruit Growth in Kiwifruit of Fluorinated N-Phenyl-N‘-1,2,3-thiadiazol-5-yl Ureas
2004
Seventeen phenyl-fluorinated analogues of thidiazuron [N-phenyl-N'-(1,2,3-thiadiazol-5-yl)urea, TDZ] have been prepared and characterized. The effects of each fluorinated urea on growth and quality of kiwifruits (Actinidia deliciosa) were evaluated by comparison with untreated (control) and TDZ-treated fruits. The results obtained showed a clear dependence of the growth-promoting activity of these fluorinated ureas on the pattern and degree of fluorine substitution in the phenyl ring. The most effective for promoting fruit growth was N-(2,3,5,6-tetrafluorophenyl)-N'-(1',2',3'-thiadiazol-5'-yl)urea at 25 ppm (at harvest, treated fruits were 58% heavier than untreated ones) followed by N-(3,5…
Atom, atom-type and total molecular linear indices as a promising approach for bioorganic and medicinal chemistry: theoretical and experimental asses…
2004
Abstract Helminth infections are a medical problem in the world nowadays. In this paper a novel atom-level chemical descriptor has been applied to estimate the anthelmintic activity. Total and local linear indices and linear discriminant analysis were used to obtain a quantitative model that discriminates between anthelmintic and non-anthelmintic drug-like compounds. The discriminant model has an accuracy of 90.11% in the training set, with a high Matthews’ correlation coefficient (MCC = 0.80). To assess the robustness and predictive power of the obtained model, internal (leave-n-out) and external validation process was performed. The QSAR model correctly classified 88.55% of compounds in t…
QSAR Modeling ANTI-HIV-1 Activities by Optimization of Correlation Weights of Local Graph Invariants
2004
Results of using descriptors calculated with the correlation weights (CWs) of local graph invariants for modeling of anti-HIV-1 potencies of two groups of reverse transcriptase (RT) inhibitors are reported. Presence of different chemical elements in molecular structure of the inhibitors and the presence of Morgan extended connectivity values of zeroth-, first- and second order have been examined as local graph invariants in the labeled hydrogen-filled graphs. By Monte Carlo method optimization procedure, values of the CWs which produce as large values as possible of correlation coefficient between the numerical data on the anti-HIV-1 potencies and values of the descriptors on the training s…
QuBiLs-MAS method in early drug discovery and rational drug identification of antifungal agents
2015
The QuBiLs-MAS approach is used for the in silico modelling of the antifungal activity of organic molecules. To this effect, non-stochastic (NS) and simple-stochastic (SS) atom-based quadratic indices are used to codify chemical information for a comprehensive dataset of 2478 compounds having a great structural variability, with 1087 of them being antifungal agents, covering the broadest antifungal mechanisms of action known so far. The NS and SS index-based antifungal activity classification models obtained using linear discriminant analysis (LDA) yield correct classification percentages of 90.73% and 92.47%, respectively, for the training set. Additionally, these models are able to correc…
Application of molecular topology to the prediction of antifungal activity for a set of dication-substituted carbazoles, furans and benzimidazoles
2003
In this paper, the endpoint is the application of molecular topology to the search of QSAR relations into a group of dicationsubstituted carbazoles, furans and benzimidazoles, all showing antifungal activity against C. albicans. Mathematical and statistical methods such as linear regression and discriminant analysis, are used to goal. The obtained results clearly show a high efficiency of the formalism on the prediction and classification of antifungal activity. 83% of the compounds showing MIC , 10 mg/ml (active group) are correctly classified, whilst 100% overall accuracy is achieved for those compounds showing MIC . 100 mg/ml (inactive group). q 2003 Elsevier Science B.V. All rights rese…
Comparative study to predict toxic modes of action of phenols from molecular structures.
2013
Quantitative structure-activity relationship models for the prediction of mode of toxic action (MOA) of 221 phenols to the ciliated protozoan Tetrahymena pyriformis using atom-based quadratic indices are reported. The phenols represent a variety of MOAs including polar narcotics, weak acid respiratory uncouplers, pro-electrophiles and soft electrophiles. Linear discriminant analysis (LDA), and four machine learning techniques (ML), namely k-nearest neighbours (k-NN), support vector machine (SVM), classification trees (CTs) and artificial neural networks (ANNs), have been used to develop several models with higher accuracies and predictive capabilities for distinguishing between four MOAs. M…
Design of new DNA-interactive agents by molecular docking and QSPR approach
2010
The design of new series of pyrrolo-pyrimidine derivatives, further annelated with a third heterocycle of different size, which also present several chain shape moieties of variable length and with different physico-chemical character, is reported. In this contribution we showed that the combination of docking-based and QSPR-based methods could lead to good models for ligand-DNA interaction prediction. By means of these computational approaches on 360 proposed inhibitors, we were able to select the most promising candidates as DNA-interactive drugs potentially endowed with antitumor activity.