The development of 3D-QSAR study and recursive partitioning of heterocyclic quinone derivatives with antifungal activity

Choi, Sang Hyoun; Shin, Jae Hong; Ryu, Chung Kyu; Nam, Ky Youb; No, Kyoung Tai; Choo, Hea Young Park

doi:10.1016/j.bmc.2005.10.010

Cited by 21 publications

(10 citation statements)

References 16 publications

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“…The minimal and maximal graphs are used to discuss various contexts on molecular shape (54,56). The importance of the Kappa‐3 descriptor is also studied by other researchers in QSAR analysis of heterocyclic quinone derivatives as antifungal agents (57). Figure 7 shows this parity plot relating the predicted activity with the experimental values for S. typhi and Table 9 lists the data.…”

Section: Resultsmentioning

confidence: 99%

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Impact of Topological and Electronic Descriptors in the QSAR of Pyrazine Containing Thiazolines and Thiazolidinones as Antitubercular and Antibacterial Agents

Sivakumar

Babu

Doble³

2008

Chem Biol Drug Des

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Quantitative structure activity relationships (QSAR) were developed relating the 14th and 21st day antituberculosis activity against H(37)Rv strain of Mycobacterium tuberculi and antibacterial activity against Staphylococcus aureus ATCC3750, Bacillus subtilis 6633, Escherichia coli ATCC3750, and Salmonella typhi NCTC786 of 55 pyrazine containing thiazolines and thiazolidinones, with the molecular descriptors. The developed models were able to fit the data well (r(2) = 0.69-0.87) and had reasonable predictive capability (q(2) > 0.62). The data were also divided into a training set and a test set, the former was used to develop the QSAR and the latter was used to evaluate the predictive capability of these developed models. In all the cases, the models were able to predict the test data set reasonably well. Predominantly, pyrazine ring is well-known for its antimycobacterial activity and hence these equation could be used to design newer analogues with higher activity. These compounds also possess both antitubercular and antibacterial activity. Descriptors pertaining to electronic, topology, and hydrophobicity of the molecules appear in the model equations.

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Section: Resultsmentioning

confidence: 99%

“…Kappa-3 Topological Kier's shape index heterocyclic quinone derivatives as antifungal agents (57). Figure 7 shows this parity plot relating the predicted activity with the experimental values for S. typhi and Table 9 lists the data.…”

Section: Qsar Of Pyrazine Containing Thiazolines and Thiazolidinonesmentioning

confidence: 99%

Impact of Topological and Electronic Descriptors in the QSAR of Pyrazine Containing Thiazolines and Thiazolidinones as Antitubercular and Antibacterial Agents

Sivakumar

Babu

Doble³

2008

Chem Biol Drug Des

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“…Recursive partitioning (RP) is a simple, yet powerful statistical technique that seeks to decode the elusive relationships in complex datasets involving thresholds, interactions, and nonlinearities. These factors impede an analysis that is based on assumptions of linearity such as multiple linear regression, principal component analysis, or partial least squares.…”

Section: Methodsmentioning

confidence: 99%

Targeting Dormant Tuberculosis Bacilli: Results for Molecules with a Novel Pyrimidone Scaffold

et al. 2014

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Our inability to completely control TB has been due in part to the presence of dormant mycobacteria. This also renders drug regimens ineffective and is the prime cause of the appearance of drug-resistant strains. In continuation of our efforts to develop novel antitubercular agents that especially target dormant mycobacteria, a set of 55 new compounds belonging to the pyrimidone class were designed on the basis of CoMFA and CoMSIA studies, and these were synthesized and subsequently tested against both the dormant and virulent BCG strain of M. tuberculosis. Some novel compounds have been identified which selectively inhibit the dormant tuberculosis bacilli with significantly low IC50 values. This study reports the second molecule after TMC-207, having the ability to inhibit tuberculosis bacilli exclusively in its dormant phase. The synthesis was accomplished by a modified multicomponent Biginelli reaction. A classification model was generated using the binary QSAR approach--recursive partitioning (RP) to identify structural characteristics related to the activity. Physicochemical, structural, topological, connectivity indices, and E-state key descriptors were used for generation of the decision tree. The decision tree could provide insights into structure-activity relationships that will guide the design of more potent inhibitors.

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“…One of the potent antifungal agents with novel mode of action is UHDBT 1 (5-n-indecyl-6-hydroxy-4,7-dioxobenzothiazole). A series of UHDBT 1 analogues with 1,4-quinone moiety such as 4,7-benzimidazolediones and 4,7-dioxobenzothiazoles showed potent antifungal activity against pathogenic fungi [3]. Native Kenyan plants containing muzigadial, warburganal, polygodial, ugandensidial, muzigadiolide, and Azadirachtin have also been found to be effective against Fusarium oxysporum, Alternaria passiflorae, and Aspergillus niger [4].…”

Section: Introductionmentioning

confidence: 99%

“…Two novel structural descriptors namely, lone-pair electrons index (LEI) and molecular volume index (MVI) were tested on 24 heterocyclic nitrogen containing compounds against miracidium, 19 benzyl alcohols against Aspergillus niger and 50 substituted phenols against tetrahymena pyriformis [5]. MIC values of 1,4-quinone derivatives on Aspergillus niger exhibited a strong correlation with steric and electrostatic factors of the 3D structure of the molecules [3]. The relative contributions of steric and electrostatic were 65.1% and 34.9%, respectively.…”

Section: Introductionmentioning

confidence: 99%

Experimental and modelling studies on antifungal compounds

Doble

Kumar

2006

Open Chemistry

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Antifungal activity of organic compounds (aromatic, salicylic derivatives, cinnamyl derivatives etc) on Fusarium Rosium (14 compounds) and Aspergillus niger (17 compounds) was studied and QSAR models were developed relating molecular descriptors with the observed activity. Back propagation Neural Network models and single and multiple regression models were tested for predicting the observed activity. The data fit as well as the predictive capability of the neural network models were satisfactory (R 2 = 0.84, q 2 = 0.73 for Fusarium Rosium and R 2 = 0.75, q 2 = 0.62 for Aspergillus niger ). The descriptors used in the network for the former were X4 (connectivity) and Jhetv (topological); and TIC1 (information) and SPI (topological) for the latter fungus. Antifungal activities of these organic compounds were generally lower against the latter than with the former fungus.

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The development of 3D-QSAR study and recursive partitioning of heterocyclic quinone derivatives with antifungal activity

Cited by 21 publications

References 16 publications

Impact of Topological and Electronic Descriptors in the QSAR of Pyrazine Containing Thiazolines and Thiazolidinones as Antitubercular and Antibacterial Agents

Impact of Topological and Electronic Descriptors in the QSAR of Pyrazine Containing Thiazolines and Thiazolidinones as Antitubercular and Antibacterial Agents

Targeting Dormant Tuberculosis Bacilli: Results for Molecules with a Novel Pyrimidone Scaffold

Experimental and modelling studies on antifungal compounds

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