Evaluation of Quantum Chemical Methods and Basis Sets Applied in the Molecular Modeling of Artemisinin

Abstract

In this paper, we evaluate semiempirical methods (AM1, PM3, and ZINDO), HF and DFT (B3LYP) in different basis sets to determine which method best describes the sign and magnitude of the geometrical parameters of artemisinin in the region of the endoperoxide ring compared to crystallographic data. We also classify these methods using statistical analysis. The results of PCA were based on three main components, explaining 98.0539% of the total variance, for the geometrical parameters C3O13, O1O2C3, O13C12C12a, and O2C3O13C12. The DFT method (B3LYP) corresponded well with the experimental data in the hierarchical cluster analysis (HCA). The experimental and theoretical angles were analyzed by simple linear regression, and statistical parameters (correlation coefficients, significance, and predictability) were evaluated to determine the accuracy of the calculations. The statistical analysis exhibited a good correlation and high predictive power for the DFT (B3LYP) method in the 6-31G** basis set.

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

“…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.…”

“…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.…”

“…However, the minimum base 6-31G has several deficiencies; thus, a polarization function was included to improve upon this base (i.e., p orbitals represented by *). Thus, 6-31G* refers to basis set 6-31G with a polarization function for heavy atoms (i.e., atoms other than hydrogen), and 6-31G** refers to the inclusion of a polarization function for hydrogen and helium atoms [29][30][31][32][33][34][35].…”

“…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.…”

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

“…So it becomes necessary adding diffuse functions to basis function associated to configuration of the neutral metal atom in order to obtain a better description of the metal complex. The great importance of diffuse functions is due to the fact that they better describe the farthest molecular orbital of the nuclei [54].…”