A study on antimalarial artemisinin derivatives using MEP maps and multivariate QSAR

Cardoso, Fábio José Bonfim; Figueiredo, Antonio Florêncio de; Lobato, Maycon da Silva; Miranda, Ricardo Morais de; Almeida, Ruth C. O. De; Pinheiro, José

doi:10.1007/s00894-007-0249-9

Cited by 26 publications

(16 citation statements)

References 30 publications

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“…A comparison of the reported QSAR models on the artemisinin analogues [53][54][55][56][57] and the GRNN model developed in this work is given in ▶ table 4. Although, the calculated descriptors were not similar in the reported works, this comparison reveals the ability of GRNN to predict the activity of artemisinin analogues.…”

Section: Resultsmentioning

confidence: 99%

QSAR Study of Artemisinin Analogues as Antimalarial Drugs by Neural Network and Replacement Method

Abbasitabar

Zare-Shahabadi

2017

Drug Res (Stuttg)

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Quantitative structure-activity relationship (QSAR) models were derived for 179 analogues of artemisinin, a potent antimalarial agent. Molecular descriptors derived solely from molecular structure were used to represent molecular structure. Utilizing replacement method, a subset of 11 descriptors was selected. General regression neural network (GRNN) was used to construct the nonlinear QSAR models in all stages of study. The relative standard error percent in antimalarial activity predictions for the training set by the application of cross-validation (RMSE-CV) was 0.43, and for test set (RMSE) was 0.51. GRNN analysis yielded predicted activities in the excellent agreement with the experimentally obtained values (R2training = 0.967 and R2test = 0.918). The mean absolute error for the test set was computed as 0.4115.

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Section: Resultsmentioning

confidence: 99%

QSAR Study of Artemisinin Analogues as Antimalarial Drugs by Neural Network and Replacement Method

Abbasitabar

Zare-Shahabadi

2017

Drug Res (Stuttg)

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“…Applications of MEP to investigate the key features of compounds that are necessary for their biological activities and thus proposing new derivatives as well as the construction of chemometric models as indicative of the most promising among the new derivatives for syntheses and biological assays were reported by us in literature [37][38][39][40][41][42][43]. Pinheiro…”

Section: Mep and Chemometrics Techniques As Tools For The Design Of Bmentioning

confidence: 99%

Molecular Electrostatic Potential and Chemometric Techniques as Tools to Design Bioactive Compounds

Santos¹,

Oliveira²,

Figueiredo³

et al. 2020

Cheminformatics and Its Applications

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In this chapter, firstly, we briefly review aspects of the approximation of quantum chemistry, molecular electrostatic potential (MEP), and chemometrics techniques, which are accredited as important tools in the development of chemical science and are frequently used in the study and design of bioactive compounds. Ultimately, we use MEP and pattern recognition (PR) techniques as tools to design nitrofuran compounds with biological activity against Trypanosoma cruzi (T. cruzi). PR models (PCA, HCA, KNN, SDA, and SIMCA) were constructed and demonstrated that 23 nitrofurans can be classified into two classes or groups: more active and less active according to their degrees of activity against T. cruzi. Properties such as charge on the N atom of the nitro group (QN1); the difference between the highest occupied molecular orbital (HOMO) energy and the lowest unoccupied molecular orbital (LUMO) energy (GAP energy); molecular representation of structure based on electron diffraction code of signal 5, unweighted (Mor05u); and Moriguchi water-octanol partition coefficient (MlogP) are responsible for the classification into more active and less active studied nitrofurans. It is interesting to notice that these properties represent three distinct classes of interactions between the nitrofurans and the biological receptor: electronic (QN1 and GAP energy), steric (Mor05u), and hydrophobic (MlogP). The results of the application of PR models on the validation set evidenced two nitrofuran compounds (compounds 25 and 30) as more promising for synthesis and biological assays, which in the future can be used to validate our PR models.

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“…From a set of 10 proposed artemisinin derivatives (artemisinin derivatives with unknown antimalarial activity against Plasmodium falciparum), a novel compound was produced with superior antimalarial activity compared with the compounds previously described in the literature [20]. Cardoso et al (2008) studied artemisinin and some of its derivatives with activity against D-6 strains of Plasmodium falciparum using the HF/3-21G method. To verify the reliability of the geometry obtained, Cardoso et al compared the structural parameters of the artemisinin trioxane ring with theoretical and experimental values from the literature.…”

Section: (B) Map Of Molecular Electrostatic Potential (Mep) ((C) Andmentioning

confidence: 99%

“…To verify the reliability of the geometry obtained, Cardoso et al compared the structural parameters of the artemisinin trioxane ring with theoretical and experimental values from the literature. MEP was used in an attempt to identify key features of the compounds that are necessary for their activities, and they use those to propose new artemisinin derivatives [21]. There is however, the need for discovery of new antimalarial drugs using techniques of quantum chemistry which has been extensively used in the pharmaceutical industry, where predicting the probable activity of a drug from molecular orbital calculations is much less expensive than manufacturing it in order to perform expensive tests [22].…”

Section: (B) Map Of Molecular Electrostatic Potential (Mep) ((C) Andmentioning

confidence: 99%

Application of Hartree-Fock Method for Modeling of Bioactive Molecules Using SAR and QSPR

Santos¹,

Lobato²,

Braga³

et al. 2014

CMB

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The central importance of quantum chemistry is to obtain solutions of the Schrödinger equation for the accurate determination of the properties of atomic and molecular systems that occurred from the calculation of wave functions accurate for many diatomic and polyatomic molecules, using Self Consistent Field method (SCF). The application of quantum chemical methods in the study and planning of bioactive compounds has become a common practice nowadays. From the point of view of planning it is important to note, when it comes to the use of molecular modeling, a collective term that refers to methods and theoretical modeling and computational techniques to mimic the behavior of molecules, not intend to reach a bioactive molecule simply through the use of computer programs. The choice of method for energy minimization depends on factors related to the size of the molecule, parameters of availability, stored data and computational resources. Molecular models generated by the computer are the result of mathematical equations that estimate the positions and properties of the electrons and nuclei, the calculations exploit experimentally, the characteristics of a structure, providing a new perspective on the molecule. In this work we show that studies of

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A study on antimalarial artemisinin derivatives using MEP maps and multivariate QSAR

Cited by 26 publications

References 30 publications

QSAR Study of Artemisinin Analogues as Antimalarial Drugs by Neural Network and Replacement Method

QSAR Study of Artemisinin Analogues as Antimalarial Drugs by Neural Network and Replacement Method

Molecular Electrostatic Potential and Chemometric Techniques as Tools to Design Bioactive Compounds

Application of Hartree-Fock Method for Modeling of Bioactive Molecules Using SAR and QSPR

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