Synthesis of quinoxaline derivatives from substituted acetanilides through intramolecular quaternization reactions

Castro, Sonia de; Chicharro, Roberto; Arán, Vicente J.

doi:10.1039/b109725c

Cited by 29 publications

(13 citation statements)

References 36 publications

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“…In order to test the potential of TOMOCOMD-CARDD method and LDA for detecting novel antiprotozoal leads, we predicted the biological activity of all the chemicals contained in our 'in-house' collections of indazole, indole, cinnoline and quinoxaline derivatives, which have been recently obtained by our chemical synthesis team [67,[77][78][79][80][81][82][83][84]. On the basis of computer-aided predictions we selected potential trichomonacidal compounds (virtual hits).…”

Section: Ligand-based Virtual In Silico Screening and Lead Trichomonamentioning

confidence: 99%

A Computer-Based Approach to the Rational Discovery of New Trichomonacidal Drugs by Atom-Type Linear Indices

Marrero-Ponce¹,

Machado-Tugores²,

Pereira³

et al. 2005

CDDT

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Computational approaches are developed to design or rationally select, from structural databases, new lead trichomonacidal compounds. First, a data set of 111 compounds was split (design) into training and predicting series using hierarchical and partitional cluster analyses. Later, two discriminant functions were derived with the use of non-stochastic and stochastic atom-type linear indices. The obtained LDA (linear discrimination analysis)-based QSAR (quantitative structure-activity relationship) models, using non-stochastic and stochastic descriptors were able to classify correctly 95.56% (90.48%) and 91.11% (85.71%) of the compounds in training (test) sets, respectively. The result of predictions on the 10% full-out cross-validation test also evidenced the quality (robustness, stability and predictive power) of the obtained models. These models were orthogonalized using the Randic orthogonalization procedure. Afterwards, a simulation experiment of virtual screening was conducted to test the possibilities of the classification models developed here in detecting antitrichomonal chemicals of diverse chemical structures. In this sense, the 100.00% and 77.77% of the screened compounds were detected by the LDA-based QSAR models (Eq. 13 and Eq. 14, correspondingly) as trichomonacidal. Finally, new lead trichomonacidals were discovered by prediction of their antirichomonal activity with obtained models. The most of tested chemicals exhibit the predicted antitrichomonal effect in the performed ligand-based virtual screening, yielding an accuracy of the 90.48% (19/21). These results support a role for TOMOCOMD-CARDD descriptors in the biosilico discovery of new compounds.

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Section: Ligand-based Virtual In Silico Screening and Lead Trichomonamentioning

confidence: 99%

A Computer-Based Approach to the Rational Discovery of New Trichomonacidal Drugs by Atom-Type Linear Indices

Marrero-Ponce¹,

Machado-Tugores²,

Pereira³

et al. 2005

CDDT

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“…One of the most important features of any QSAR model is its ability to predict the desired property for new compounds, from databases of chemicals [18]. Computational in silico screening of large databases considering the use of such models, has emerged as an interesting alternative to highthroughput screening (HTS) and as an important drugdiscovery tool [87,88] In order to test the potential of the TOMOCOMD-CARDD method and LDA, for detecting novel antiprotozoan compounds, we predicted the biological activity of all the chemicals contained in our 'in-house' collection of quinoxaline derivatives that were provided by one of our synthesis research teams from IQM, CSIC, Spain [89]. The structures of these compounds are depicted in Fig.…”

Section: Identification Of Reported Chemicals Through a Simulated Ligmentioning

confidence: 99%

Bond-based linear indices in QSAR: computational discovery of novel anti-trichomonal compounds

Marrero-Ponce

Meneses‐Marcel

Rivera-Borroto

et al. 2008

J Comput Aided Mol Des

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Trichomonas vaginalis (Tv) is the causative agent of the most common, non-viral, sexually transmitted disease in women and men worldwide. Since 1959, metronidazole (MTZ) has been the drug of choice in the systemic treatment of trichomoniasis. However, resistance to MTZ in some patients and the great cost associated with the development of new trichomonacidals make necessary the development of computational methods that shorten the drug discovery pipeline. Toward this end, bond-based linear indices, new TOMOCOMD-CARDD molecular descriptors, and linear discriminant analysis were used to discover novel trichomonacidal chemicals. The obtained models, using non-stochastic and stochastic indices, are able to classify correctly 89.01% (87.50%) and 82.42% (84.38%) of the chemicals in the training (test) sets, respectively. These results validate the models for their use in the ligand-based virtual screening. In addition, they show large Matthews' correlation coefficients (C) of 0.78 (0.71) and 0.65 (0.65) for the training (test) sets, correspondingly. The result of predictions on the 10% full-out cross-validation test also evidences the robustness of the obtained models. Later, both models are applied to the virtual screening of 12 compounds already proved against Tv. As a result, they correctly classify 10 out of 12 (83.33%) and 9 out of 12 (75.00%) of the chemicals, respectively; which is the most important criterion for validating the models. Besides, these classification functions are applied to a library of seven chemicals in order to find novel antitrichomonal agents. These compounds are synthesized and tested for in vitro activity against Tv. As a result, experimental observations approached to theoretical predictions, since it was obtained a correct classification of 85.71% (6 out of 7) of the chemicals. Moreover, out of the seven compounds that are screened, synthesized and biologically assayed, six compounds (VA7-34, VA7-35, VA7-37, VA7-38, VA7-68, VA7-70) show pronounced cytocidal activity at the concentration of 100 mug/ml at 24 h (48 h) within the range of 98.66%-100% (99.40%-100%), while only two molecules (chemicals VA7-37 and VA7-38) show high cytocidal activity at the concentration of 10 mug/ml at 24 h (48 h): 98.38% (94.23%) and 97.59% (98.10%), correspondingly. The LDA-assisted QSAR models presented here could significantly reduce the number of synthesized and tested compounds and could increase the chance of finding new chemical entities with anti-trichomonal activity.

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“…The microwave assisted synthesis has been recently reported to be remarkably successful approach which gave quinoxalinone-hydrazones [2] in higher yield at less reaction time compared to conventional heating method [3]. Recent updates showed that the chemistry of quinoxaline has attracted considerable attention [4] due to its diverse chemical reactivities [5][6][7], application in material science [8,9] and wide spectrum of biological activities [10,11]. Quinoxaline motif is known to represent a class of medicinally important compounds which are effective as antibacterial [1,4], antifungal [2,10], anticancer [11], analgesic [12], antimalarial [13], antitumor [14], antiamoebic [15], antiepileptic [16], anticonvulsant [17], antitubercular [18], antiproliferative [19], anti-HCV [20], anti-inflammatory [21] agents among others.…”

Section: Introductionmentioning

confidence: 99%

Present status of quinoxaline motifs: Excellent pathfinders in therapeutic medicine

Ajani

2014

European Journal of Medicinal Chemistry

100

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Synthesis of quinoxaline derivatives from substituted acetanilides through intramolecular quaternization reactions

Cited by 29 publications

References 36 publications

A Computer-Based Approach to the Rational Discovery of New Trichomonacidal Drugs by Atom-Type Linear Indices

A Computer-Based Approach to the Rational Discovery of New Trichomonacidal Drugs by Atom-Type Linear Indices

Bond-based linear indices in QSAR: computational discovery of novel anti-trichomonal compounds

Present status of quinoxaline motifs: Excellent pathfinders in therapeutic medicine

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