QSAR modeling: um novo pacote computacional open source para gerar e validar modelos QSAR

Martins, João Paulo Ataide; Ferreira, Márcia M. C.

doi:10.1590/s0100-40422013000400013

Cited by 64 publications

(26 citation statements)

References 11 publications

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“…27 The final reduction of variables was carried out in this program. 27 The final reduction of variables was carried out in this program.…”

Section: Qsar Studymentioning

confidence: 99%

“…Matrices of descriptors were subjected to the method of selection of variables called ordered predictors selection (OPS), 28 an iterative algorithm for building QSAR models. 27,33,34 The obtained models were refined using Pirouette 4 (www.infometrix.com) by checking the possibility of removal of some of the descriptors to obtain an optimized, simpler, statistically significant, interpretative model. In this study, the three vectors were used simultaneously.…”

Section: Qsar Studymentioning

confidence: 99%

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A structure–activity relationship study of the toxicity of ionic liquids using an adapted Ferreira–Kiralj hydrophobicity parameter

Melo

2015

Phys. Chem. Chem. Phys.

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The Ferreira-Kiralj hydrophobicity parameter Wc is a number fraction of hydrophobic carbon atoms and can be regarded as a constitutional descriptor since its calculation depends only on the number of polar and nonpolar carbons in a compound. Hydrophobicity is important to the toxicity of ionic liquids (ILs), which are salts by nature. Herein, a descriptor for this property was calculated using a simple adaptation of the type of polar carbon atoms included (WcAdap) to explore the possibility of its use in quantitative structure-activity relationship (QSAR) studies of ILs. The resulting model was tested using a database of ILs with toxicity against the Leukemia rat cell line IPC-81. Two other models were constructed using Crippen log P and Mannhold log P descriptors, which are both available in the free program PaDEL. The use of WcAdap led to a better and more indicative model. Thus, WcAdap may be a suitable molecular descriptor for the hydrophobicity of ILs in QSAR studies.

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“…27 The final reduction of variables was carried out in this program. 27 The final reduction of variables was carried out in this program.…”

Section: Qsar Studymentioning

confidence: 99%

Section: Qsar Studymentioning

confidence: 99%

A structure–activity relationship study of the toxicity of ionic liquids using an adapted Ferreira–Kiralj hydrophobicity parameter

Melo

2015

Phys. Chem. Chem. Phys.

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“…This matrix is used in a multivariate regression, for example, an MLR, principal components regression (PCR), or PLS regression, with the biological activity as the dependent variable, to construct the QSAR model. The columns in the matrix are tab‐separated and are ready to be used in a multivariate analysis program, such as QSAR modeling, QSARINS, or R, for model building and validation.…”

Section: Methodsmentioning

confidence: 99%

Web‐4D‐QSAR: A web‐based application to generate 4D‐QSAR descriptors

Martins

Oliveira²,

Queiroz³

2018

J Comput Chem

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A web-based application is developed to generate 4D-QSAR descriptors using the LQTA-QSAR methodology, based on molecular dynamics (MD) trajectories and topology information retrieved from the GROMACS package. The LQTAGrid module calculates the intermolecular interaction energies at each grid point, considering probes and all aligned conformations resulting from MD simulations. These interaction energies are the independent variables or descriptors employed in a QSAR analysis. A friendly front end web interface, built using the Django framework and Python programming language, integrates all steps of the LQTA-QSAR methodology in a way that is transparent to the user, and in the backend, GROMACS and LQTAGrid are executed to generate 4D-QSAR descriptors to be used later in the process of QSAR model building. © 2018 Wiley Periodicals, Inc.

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“…This resulted into 4114 variables for Lenard-Jones independent Lenard-Jones variables and 11,321 C potential variables were obtained. The 11,321 C potentials were subjected to ordered predictor selection (OPS) algorithm [27] which reduced the data to columns of 40 variables. In the end, the data were preprocessed using autoscaling technique to generate a QSAR model.…”

Section: Methodsmentioning

confidence: 99%

Benzo[e]pyrimido[5,4-b][1,4]diazepin-6(11H)-one derivatives as Aurora A kinase inhibitors: LQTA-QSAR analysis and detailed systematic validation of the developed model

et al. 2015

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Aurora kinases are sub-divided into Aurora A, Aurora B, and Aurora C kinases that are considered as prospective targets for a new class of anticancer drugs. In this work, a 4-D-QSAR model using an LQTA-QSAR approach with previously reported 31 derivatives of benzo[e]pyrimido[5,4 -b][1,4]diazepin -6(11H)-one as potent Aurora kinase A inhibitors has been created. Instead of single conformation, the conformational ensemble profile generated for each ligand by using trajectories and topology information retrieved from molecular dynamics simulations from GROMACS package were aligned and used for the calculation of intermolecular interaction energies at each grid point. The descriptors generated on the basis of these Coulomb and Lennard-Jones potentials as independent variables were used to perform a PLS analysis using biological activity as dependent variable. A good predictive model was generated with nine field descriptors and five latent variables. The model showed [Formula: see text]; [Formula: see text] and [Formula: see text]. This model was further validated systematically by using different validation parameters. This 4D-QSAR model gave valuable information to recognize features essential to adapt and develop novel potential Aurora kinase inhibitors.

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QSAR modeling: um novo pacote computacional open source para gerar e validar modelos QSAR

Cited by 64 publications

References 11 publications

A structure–activity relationship study of the toxicity of ionic liquids using an adapted Ferreira–Kiralj hydrophobicity parameter

A structure–activity relationship study of the toxicity of ionic liquids using an adapted Ferreira–Kiralj hydrophobicity parameter

Web‐4D‐QSAR: A web‐based application to generate 4D‐QSAR descriptors

Benzo[e]pyrimido[5,4-b][1,4]diazepin-6(11H)-one derivatives as Aurora A kinase inhibitors: LQTA-QSAR analysis and detailed systematic validation of the developed model

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