2009
DOI: 10.1016/j.ejmech.2008.12.028
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Design and in silico screening of combinatorial library of antimalarial analogs of triclosan inhibiting Plasmodium falciparum enoyl-acyl carrier protein reductase

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Cited by 31 publications
(35 citation statements)
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“…1 and observed activities pK i pre /pK i exp , which yielded values close to 1, confirmed the predictive power of the QSAR model. Although the training and validation sets displayed somewhat limited variation in the R-groups space due to restricted availability of experimental data, prediction of inhibitory potencies by the trained targetspecific scoring function, which slightly exceed the activity ranges of the training set, is still possible, as QSAR models using ligand-receptor binding affinity estimate (LUDI score) of docked analogs are less sensitive to size of the training set [33][34][35][36].…”
Section: Qsar Model and Target-specific Scoring Functionmentioning
confidence: 99%
See 1 more Smart Citation
“…1 and observed activities pK i pre /pK i exp , which yielded values close to 1, confirmed the predictive power of the QSAR model. Although the training and validation sets displayed somewhat limited variation in the R-groups space due to restricted availability of experimental data, prediction of inhibitory potencies by the trained targetspecific scoring function, which slightly exceed the activity ranges of the training set, is still possible, as QSAR models using ligand-receptor binding affinity estimate (LUDI score) of docked analogs are less sensitive to size of the training set [33][34][35][36].…”
Section: Qsar Model and Target-specific Scoring Functionmentioning
confidence: 99%
“…1). A virtual library of more than 9,200 analogs containing natural and especially unusual amino acids was designed, structure-based focused and in silico screened by computer-assisted combinatorial techniques [33][34][35][36] aiming at finding more potent and specific antiviral compounds. The three-dimensional structure of the DEN2 NS2B-NS3pro complex was employed to develop a QSAR model, parameterize a target-specific scoring function specific for the NS3pro target and select analogues which display the highest predicted binding to the NS3pro.…”
Section: Admementioning
confidence: 99%
“…In this work, we have virtually explored in an extensive manner the chemical space around VAN1 by designing and in silico screening a virtual library of 2 0 ,3 0 -bicyclic thymidine analogues using computer-assisted combinatorial techniques [24][25][26][27][28]. Our goal was to select more potent TMPK mt inhibitors endowed with favorable ADME-related properties, and to prioritize them for future synthesis.…”
Section: Introductionmentioning
confidence: 99%
“…The virtual combinatorial chemistry technique, originating from efforts to efficiently synthesize libraries of diverse compounds, helps to shed light on the issue and thus provides a powerful approach to generate an in silico molecular structure library of SCCPs (Cho et al, 1998;Zhou, 2008). In fact, this method has developed rapidly and could generate thousands or even millions of chemical structures within a short time through correctly defined chemical reactions based on combinatorial theory and computational simulation (Frecer et al, 2009;Lokwani et al, 2015).…”
Section: Introductionmentioning
confidence: 99%