On polarization functions for Gaussian basis sets.

In this work, we introduce a technique to choose polarization functions directly from the primitive set of Gaussian exponent without the necessity to optimize or even reoptimized them. For this purpose, initially, we employed Gaussian basis sets generated by using the Polynomial Generator Coordinate Hartree-Fock (PGCHF) method, and later we extended our technique to the cc-pVQZ and pc-3 Gaussian basis sets in order to show how our technique works and how good it is. Using the new polarized basis sets, from our technique, total electronic energies, equilibrium geometries, and vibrational frequencies were calculated for a set of molecules containing atoms from H(Z = 1) to Ba(Z = 56). The technique presented here can be used with any Gaussian basis set flexible (large) enough and also can be used to choose Gaussian basis set exponents from one basis set to another as polarization functions.

Relativistic Prolapse-Free Gaussian Basis Sets of Quadruple-ζ Quality: (aug-)RPF-4Z. III. The f-Block Elements.

The f-block elements are addressed in this third part of a series of prolapse-free basis sets of quadruple-ζ quality (RPF-4Z). Relativistic adapted Gaussian basis sets (RAGBSs) are used as primitive sets of functions while correlating/polarization (C/P) functions are chosen by analyzing energy lowerings upon basis set increments in Dirac-Coulomb multireference configuration interaction calculations with single and double excitations of the valence spinors. These function exponents are obtained by applying the RAGBS parameters in a polynomial expression. Moreover, through the choice of C/P characteristic exponents from functions of lower angular momentum spaces, a reduction in the computational demand is attained in relativistic calculations based on the kinetic balance condition. The present study thus complements the RPF-4Z sets for the whole periodic table (Z ≤ 118). The sets are available as Supporting Information and can also be found at http://basis-sets.iqsc.usp.br .

Quantum chemical DFT study of the interaction between molecular oxygen and FeN4 complexes, and effect of the macrocyclic ligand.

Density functional theory (DFT) was used to examine the interaction between molecular oxygen (O2) and macrocyclic iron complexes of the type FeN4 during the formation of FeN4--O2 adducts. In order to understand how this interaction is affected by different macrocyclic ligands, O2 was bonded to iron-tetraaza[14]annulene (FeTAA), iron-tetramethyl-tetraaza[14]annulene (FeTMTAA), iron-hexamethyl-tetraaza[14]annulene (FeHMTAA), iron dibenzotetraaza[14]annulene (FeDBTAA), and two iron-tetramethyl-dibenzotetraaza[14]annulene complexes (FeTMDBTAA1, FeTMDBTAA2). The ground state for FeN4-O2 adducts was the open-shell singlet. Analysis of the factors influencing the O2 bonding process showed that different macrocyclic ligands yielded adducts with differences in O--O and Fe--O2 bond lengths, total charge over the O2 fragment, O--O vibrational frequency, and spin density in the O2 fragment. A smaller energy gap between the α-HOMO of the FeN4 complexes and the ß-LUMO of O2 increased the interaction between the complex and the O2 molecule. The order of activity was FeDBTAA < FeTMDBTAA2 < FeTMDBTAA1 < FeTAA < FeTMTAA < FeHMTAA.

Relativistic Prolapse-Free Gaussian Basis Set of Quadruple-ζ Quality: (aug-)RPF-4Z. I. The s- and p-Block Elements.

This study reports a new relativistic prolapse-free Gaussian basis set series of quadruple-ζ quality, RPF-4Z, and an augmented version that includes extra diffuse functions, aug-RPF-4Z, for all the s- and p-block elements. The relativistic adapted Gaussian basis sets (RAGBSs), which are free of variational prolapse, were used as the starting primitive sets. Exponents of correlating/polarization functions were taken from a polynomial version of the generator coordinate Dirac-Fock (p-GCDF) method, in which the previously optimized RAGBS parameters are applied. By using such procedure we aimed to reduce the computational demand of these sets in comparison with fully optimized ones. The effect of these basis set increments on the correlation energy was evaluated by atomic multireference configuration interaction calculations with single and double excitations out of the valence shell. Finally, atomic and molecular calculations of fundamental properties (bond lengths, vibrational frequencies, dipole moments and electron affinities) corroborate the quadruple-ζ quality of these new sets that are also about half-time-consuming than the correspondent Dyall's v4z sets. The read-to use format of these (aug-)RPF-4Fz sets are available as Supporting Information files and can also be found at http://basis-sets.iqsc.usp.br/ .

Molecular features for antitrypanosomal activity of thiosemicarbazones revealed by OPS-PLS QSAR studies.

A quantitative structure-activity relationship analysis was employed to explore the relationship between the molecular structure of thiosemicarbazone analogues and the inhibition of the cysteine protease cruzain, a validated target for Chagas' disease treatment. A data set containing 53 thiosemicarbazone derivatives was used to produce a quantitative model for activity prediction of unknown compounds. Several electronic descriptors were obtained through DFT calculations, along with a large amount of Dragon descriptors. The ordered predictor selection (OPS) algorithm was employed to select the most relevant descriptors to perform PLS regressions. With this procedure, significant correlation coefficients (r(2) = 0.85, q(2) = 0.78) were achieved. Furthermore, predicted values for an external test set are in good agreement with the experimental results, indicating the potential of the model for untested compounds. Additional validation tests were carried out, indicating that a robust and reliable model was obtained to be used in the design of new thiosemicarbazones with improved cruzain inhibition potential.

Docking and molecular dynamics simulation of quinone compounds with trypanocidal activity.

In this work, two different docking programs were used, AutoDock and FlexX, which use different types of scoring functions and searching methods. The docking poses of all quinone compounds studied stayed in the same region in the trypanothione reductase. This region is a hydrophobic pocket near to Phe396, Pro398 and Leu399 amino acid residues. The compounds studied displays a higher affinity in trypanothione reductase (TR) than glutathione reductase (GR), since only two out of 28 quinone compounds presented more favorable docking energy in the site of human enzyme. The interaction of quinone compounds with the TR enzyme is in agreement with other studies, which showed different binding sites from the ones formed by cysteines 52 and 58. To verify the results obtained by docking, we carried out a molecular dynamics simulation with the compounds that presented the highest and lowest docking energies. The results showed that the root mean square deviation (RMSD) between the initial and final pose were very small. In addition, the hydrogen bond pattern was conserved along the simulation. In the parasite enzyme, the amino acid residues Leu399, Met400 and Lys402 are replaced in the human enzyme by Met406, Tyr407 and Ala409, respectively. In view of the fact that Leu399 is an amino acid of the Z site, this difference could be explored to design selective inhibitors of TR.

A neural networks study of quinone compounds with trypanocidal activity.

This work investigates neural network models for predicting the trypanocidal activity of 28 quinone compounds. Artificial neural networks (ANN), such as multilayer perceptrons (MLP) and Kohonen models, were employed with the aim of modeling the nonlinear relationship between quantum and molecular descriptors and trypanocidal activity. The calculated descriptors and the principal components were used as input to train neural network models to verify the behavior of the nets. The best model for both network models (MLP and Kohonen) was obtained with four descriptors as input. The descriptors were T5 (torsion angle), QTS1 (sum of absolute values of the atomic charges), VOLS2 (volume of the substituent at region B) and HOMO-1 (energy of the molecular orbital below HOMO). These descriptors provide information on the kind of interaction that occurs between the compounds and the biological receptor. Both neural network models used here can predict the trypanocidal activity of the quinone compounds with good agreement, with low errors in the testing set and a high correctness rate. Thanks to the nonlinear model obtained from the neural network models, we can conclude that electronic and structural properties are important factors in the interaction between quinone compounds that exhibit trypanocidal activity and their biological receptors. The final ANN models should be useful in the design of novel trypanocidal quinones having improved potency.

A quantum chemical and statistical study of flavonoid compounds (flavones) with anti-HIV activity.

The molecular orbital semi-empirical method AM1 was employed to calculate a set of molecular properties (variables) of 22 flavonoid compounds (flavones) with anti-HIV-1 activity and nine new compounds were proposed for anti-HIV-1 activity prediction. Pattern recognition techniques, principal component analysis (PCA), hierarchical cluster analysis (HCA), stepwise discriminant analysis (SDA) and K-nearest neighbor (KNN), were employed in order to reduce dimensionality and investigate which subset of variables could be more effective for classifying the flavones according to their degree of anti-HIV-1 activity. The PCA, HCA, SDA and KNN studies showed that the variables log P (partition coefficient), molecular volume (VOL) and electron affinity (EA) are responsible for the separation between anti-HIV-1 active and inactive compounds. The prediction study was done with a new set of nine analog compounds by using the PCA, HCA, SDA and KNN methods and only one of them was predicted as active against HIV-1.