Computational studies of the structures and properties of potential antimalarial compounds based on the 1,2,4-trioxane ring structure. I. Artemisinin-like molecules

Bérnardinelli, Gerald; Jefford, Charles W.; Maric, Dj. M.; Thomson, Colin; Weber, Jacques

doi:10.1002/qua.560520710

Cited by 29 publications

(34 citation statements)

References 13 publications

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“…The prediction of Absorption, Distribution, Metabolism and Excretion (ADME) proprieties for artemisinin and its derivatives of the test set (compounds [22][23][24][25][26][27][28][29] classified by PLS and PCR models as more potent are shown in Tables 7 and 8. In Table 7, one can observe the absorption values (HIA, PCaCO2 and PMDCK) predicted for the compounds.…”

Section: Pharmacokinetic and Toxicological Resultsmentioning

confidence: 99%

“…Since the compound 27 showed the value of penetration of the blood brain barrier (C Brain /C Blood ) closest to of artemisinin (C Brain /C Blood = 1.304) having the smallest variation between test compounds studied (C Brain /C Blood [compound 27] − C Brain /C Blood [artemisinin]), showing value equal to 0.6064. Table 9 shows the results of the toxicological properties of mutagenicity (Ames Test) and carcinogenicity (Mouse and rat) for artemisinin and its derivatives of the test set (22)(23)(24)(25)(26)(27)(28)(29) classified by PLS and PCR models as more potent with anticancer activity against human hepatocellular carcinoma HepG2. One of the important reasons for the discovery of new drugs is the evaluation of the toxicity of drug candidates.…”

Section: Pharmacokinetic and Toxicological Resultsmentioning

confidence: 99%

“…The models reveal that compounds with high biological potency against human hepatocellular carcinoma HepG2 have a combination of higher values of IC5 and GAP energy and lower values of ALOGPS_logs and Mor29m for the PLS and PCR models. The eight compounds of the test set (22)(23)(24)(25)(26)(27)(28)(29) were molded from the most stable structure of artemisinin, compound 1 of Figure 1, and constructed using GaussView 5.0 program, carrying the complete optimization of the geometry of each compound with the basis set of separated valence B3LYP/6-31G** using the DFT method as implemented in Gaussian 03 program. After obtain the most stable geometry of each compound was determined only selected descriptors in PCA and used in the construction of the QSAR models, namely ALOGPS_logs, Mor29m, IC5 and GAP energy, shown in Table 5.…”

Section: Partial Least Squares (Pls) and Principal Component Regressimentioning

confidence: 99%

“…This type of strategy, unlike molecular modification, does not have high time demands and is low in financial investment. Among the various techniques we can highlight planning with the help of computer, which is a resource that increases considerably the possibilities of scientific research in discovery of new drugs [20][21][22][23].…”

Section: Introductionmentioning

confidence: 99%

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A QSAR, Pharmacokinetic and Toxicological Study of New Artemisinin Compounds with Anticancer Activity

et al. 2014

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Abstract:The Density Functional Theory (DFT) method and the 6-31G** basis set were employed to calculate the molecular properties of artemisinin and 20 derivatives with different degrees of cytotoxicity against the human hepatocellular carcinoma HepG2 line. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were employed to select the most important descriptors related to anticancer activity. The significant molecular descriptors related to the compounds with anticancer activity were the ALOGPS_log, Mor29m, IC5 and GAP energy. The Pearson correlation between OPEN ACCESSMolecules 2014, 19 10671 activity and most important descriptors were used for the regression partial least squares (PLS) and principal component regression (PCR) models built. The regression PLS and PCR were very close, with variation between PLS and PCR of R 2 = ±0.0106, R 2 ajust = ±0.0125, s = ±0.0234, F (4,11) = ±12.7802, Q 2 = ±0.0088, SEV = ±0.0132, PRESS = ±0.4808 and S PRESS = ±0.0057. These models were used to predict the anticancer activity of eight new artemisinin compounds (test set) with unknown activity, and for these new compounds were predicted pharmacokinetic properties: human intestinal absorption (HIA), cellular permeability (P CaCO2 ), cell permeability Maden Darby Canine Kidney (P MDCK ), skin permeability (P Skin ), plasma protein binding (PPB) and penetration of the blood-brain barrier (C Brain/Blood ), and toxicological: mutagenicity and carcinogenicity. The test set showed for two new artemisinin compounds satisfactory results for anticancer activity and pharmacokinetic and toxicological properties. Consequently, further studies need be done to evaluate the different proposals as well as their actions, toxicity, and potential use for treatment of cancers.

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Section: Pharmacokinetic and Toxicological Resultsmentioning

confidence: 99%

Section: Pharmacokinetic and Toxicological Resultsmentioning

confidence: 99%

Section: Partial Least Squares (Pls) and Principal Component Regressimentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A QSAR, Pharmacokinetic and Toxicological Study of New Artemisinin Compounds with Anticancer Activity

et al. 2014

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“…Therefore, obtaining molecular properties will depend on the method and basis set to reproduce experimental data with greater accuracy. In this case, the MEP of aspirin in different basis set was used to evaluate the key features of aspirin from qualitative comparisons in the region of the acetyl group, which according to Bernardinelli et al [88] the geometric form of the electrostatic potential is similar for all active compounds. However, new derivatives of aspirin must have some structural similarity in terms of their electrostatic potentials that allow one to be recognized by the other, with similar biological activities [87] [89] [90].…”

Section: Case Study On Aspirinmentioning

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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Quantitative structure–activity relationship (QSAR) of artemisinin: the development of predictive in vivo antimalarial activity models

Srivastava

Singh

Naik

2009

Journal of Chemometrics

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A quantitative structure-activity relationship (QSAR) analysis has been performed on a data set of 194 artemisinin analogs for antimalarial activity. Several types of descriptors including topological, spatial, thermodynamics, information content, lead likeness, and E-state indices have been used to derive a quantitative relationship between antimalarial activity and structural properties. A systematic approach of zero tests, missing value test, simple correlation test, multicollinearity test, and genetic algorithm method of variable selection was used to generate the model. Statistically significant model (r 2 ¼ 0.845, q 2 cv ¼ 0.799, F-test ¼ 53.40) was obtained with the descriptors like molecular connectivity indexes, E-state index, length-to-breadth ratio of compounds, MLog P, HOMO, electron density, Balabans topological index, and strain energy of the molecules. The robustness of the QSAR models was characterized by the values of the internal leave one out cross-validated regression coefficient (q 2 cv ) for the training set and determination coefficient in prediction, q 2 test for the test set. The value of q 2 test ¼ 0.876 for the test set; revealed good external predictability of the QSAR model. Also, for an external data set (validation set) of four artemisinin analogs, the QSAR model was able to predict the antimalarial activity very well in comparison to experimental values. The model was also tested successfully for external validation criteria. The QSAR model developed in this study should aid further design of novel potent artemisinin derivatives.

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Computational studies of the structures and properties of potential antimalarial compounds based on the 1,2,4-trioxane ring structure. I. Artemisinin-like molecules

Cited by 29 publications

References 13 publications

A QSAR, Pharmacokinetic and Toxicological Study of New Artemisinin Compounds with Anticancer Activity

A QSAR, Pharmacokinetic and Toxicological Study of New Artemisinin Compounds with Anticancer Activity

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

Quantitative structure–activity relationship (QSAR) of artemisinin: the development of predictive in vivo antimalarial activity models

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