2012
DOI: 10.1021/ci300039a
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Four-Dimensional Structure–Activity Relationship Model to Predict HIV-1 Integrase Strand Transfer Inhibition using LQTA-QSAR Methodology

Abstract: Despite highly active antiretroviral therapy (HAART) implementation, there is a continuous need to search for new anti-HIV agents. HIV-1 integrase (HIV-1 IN) is a recently validated biological target for AIDS therapy. In this work, a four-dimensional quantitative structure-activity relationship (4D-QSAR) study using the new methodology named LQTA-QSAR approach with a training set of 85 HIV-1 IN strand transfer inhibitors (INSTI), containing the β-diketo acid (DKA) substructure, was carried out. The GROMACS mol… Show more

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Cited by 26 publications
(18 citation statements)
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“…The nD-QSAR approaches are good enough to interpret the descriptors into activity prediction models [24,32,[36][37][38].…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…The nD-QSAR approaches are good enough to interpret the descriptors into activity prediction models [24,32,[36][37][38].…”
Section: Resultsmentioning
confidence: 99%
“…In order to have a superior predictive potential of the model, a modified R 2 (R 2 m ) was determined [31]. Further, the model was externally validated by predicting the activity of external set or test set of compounds and evaluated by means of coefficient of determination (R 2 pred ), standard error of external prediction (SEP), and the average relative error (ARE pred ) [32]. Additionally, different external validation techniques were implemented.…”
Section: Methodsmentioning
confidence: 99%
“…In addition, Y-randomization is also a good indicator of coincidence rates. De Melo and Ferreira [36] showed that their model (Y-randomization: r 2 intercept = 0.109; q 2 intercept = À0.398) was not built by chance through the Y-randomization test. Applicability domain analysis could further assess the prediction reliability of QSAR models using an extrapolation method [42,43].…”
Section: Function Of Inmentioning
confidence: 99%
“…Current IN studies focus on 2D-QSAR and 3D-QSAR, although 4D-QSAR is becoming increasingly popular. De Melo and Ferreira [36] used a 4D-QSAR model to predict IN strand transfer inhibition using Laborató rio de Quimiometria Teó rica e Aplicada (LQTA)-QSAR, which has a module (LQTAgrid) that calculates intermolecular interaction energies at each grid point considering probes and all aligned conformations resulting from MD simulations. Further validation showed that this 4D-QSAR model performed well in both internal (q 2 = 0.832, r 2 = 0.905) and external prediction (r 2 pred ¼ 0:839).…”
Section: Function Of Inmentioning
confidence: 99%
“…As a natural consequence, a simple SCP check 15 was introduced in 2010 to be a tool for rapid SCP detection and elimination, and then extended to a more advanced SCP check 16 in 2012. SCP check has been already applied by some researchers, [20][21][22][23][24] whilst for other QSAR/QSPR groups it served to make them more aware of the danger of SCP. [25][26][27][28] In this work, the previous SCP check 16 is substantially extended to Integral SCP (ISCP) check.…”
Section: Introductionmentioning
confidence: 99%