Luis A. Montero-Cabrera

Single configuration interaction study on conjugated betainic chromophores based on DFT optimized geometries

Abstract The structure of a series of heterocyclic betaines was calculated by methods of density functional theory (DFT). The charge distribution and bond characteristics of these compounds were analyzed by Weinhold’s natural bond orbital analysis (NBO) and by natural resonance theory (NRT). In order to probe the aromatic character of the ring fragments, Schleyer’s nucleus-independent chemical shifts (NICSs) were calculated by GIAO-RHF. Ab initio single configuration interaction calculations (SCI) correctly predict intense π → π * transitions at low energies, but the transition energies of the color bands are overestimated. Torsion around the interfragmental bond increases the charge separation between the molecular fragments and the dipole moment. The molecular fragments become increasingly aromatic. The absorption wavelengths increase on torsion while the oscillator strengths decrease.

Theoretical study of flavonoids and proline interactions. Aqueous and gas phases

Abstract Flavonoids are polyphenolic compounds found in all land plants and in plant-related foods. These compounds have many positive effects, and the interaction with proline aminoacid is one of the most important characteristics. The present work shows the results of the application of the multiple minima hypersurfaces procedures, in the study of the interactions of flavonoid monomers (catechin and robinetinidin) with proline. These results are compared with experimental and classical theoretical results reported in the available literature. The most important results of this work are related with the conformations of monomers in these interactions, the preferential position of interactions and the thermodynamic stability of these complexes. All the results are successfully compared in both, gas and aqueous phases.

Applying pattern recognition methods plus quantum and physico‐chemical molecular descriptors to analyze the anabolic activity of structurally diverse steroids

The great cost associated with the development of new anabolic–androgenic steroid (AASs) makes necessary the development of computational methods that shorten the drug discovery pipeline. Toward this end, quantum, and physicochemical molecular descriptors, plus linear discriminant analysis (LDA) were used to analyze the anabolic/androgenic activity of structurally diverse steroids and to discover novel AASs, as well as also to give a structural interpretation of their anabolic–androgenic ratio (AAR). The obtained models are able to correctly classify 91.67% (86.27%) of the AASs in the training (test) sets, respectively. The results of predictions on the 10% full‐out cross‐validation test also evidence the robustness of the obtained model. Moreover, these classification functions are applied to an “in house” library of chemicals, to find novel AASs. Two new AASs are synthesized and tested for in vivo activity. Although both AASs are less active than some commercially AASs, this result leaves a door open to a virtual variational study of the structure of the two compounds, to improve their biological activity. The LDA‐assisted QSAR models presented here, could significantly reduce the number of synthesized and tested AASs, as well as could increase the chance of finding new chemical entities with higher AAR.

Chemometric and chemoinformatic analyses of anabolic and androgenic activities of testosterone and dihydrotestosterone analogues.

Predictive quantitative structure-activity relationship (QSAR) models of anabolic and androgenic activities for the testosterone and dihydrotestosterone steroid analogues were obtained by means of multiple linear regression using quantum and physicochemical molecular descriptors (MD) as well as a genetic algorithm for the selection of the best subset of variables. Quantitative models found for describing the anabolic (androgenic) activity are significant from a statistical point of view: R(2) of 0.84 (0.72 and 0.70). A leave-one-out cross-validation procedure revealed that the regression models had a fairly good predictability [q(2) of 0.80 (0.60 and 0.59)]. In addition, other QSAR models were developed to predict anabolic/androgenic (A/A) ratios and the best regression equation explains 68% of the variance for the experimental values of AA ratio and has a rather adequate q(2) of 0.51. External validation, by using test sets, was also used in each experiment in order to evaluate the predictive power of the obtained models. The result shows that these QSARs have quite good predictive abilities (R(2) of 0.90, 0.72 (0.55), and 0.53) for anabolic activity, androgenic activity, and A/A ratios, respectively. Last, a Williams plot was used in order to define the domain of applicability of the models as a squared area within +/-2 band for residuals and a leverage threshold of h=0.16. No apparent outliers were detected and the models can be used with high accuracy in this applicability domain. MDs included in our QSAR models allow the structural interpretation of the biological process, evidencing the main role of the shape of molecules, hydrophobicity, and electronic properties. Attempts were made to include lipophilicity (octanol-water partition coefficient (logP)) and electronic (hardness (eta)) values of the whole molecules in the multivariate relations. It was found from the study that the logP of molecules has positive contribution to the anabolic and androgenic activities and high values of eta produce unfavorable effects. The found MDs can also be efficiently used in similarity studies based on cluster analysis. Our model for the anabolic/androgenic ratio (expressed by weight of levator ani muscle, LA, and seminal vesicle, SV, in mice) predicts that the 2-aminomethylene-17alpha-methyl-17beta-hydroxy-5alpha-androstan-3-one (43) compound is the most potent anabolic steroid, and the 17alpha-methyl-2beta,17beta-dihydroxy-5alpha-androstane (31) compound is the least potent one of this series. The approach described in this report is an alternative for the discovery and optimization of leading anabolic compounds among steroids and analogues. It also gives an important role to electron exchange terms of molecular interactions to this kind of steroid activity.

Interaction of brassinolide with essential amino acid residues: A theoretical approach

The interaction of the most active natural brassinosteroid, brassinolide, with the twenty natural amino acids is studied applying the multiple minima hypersurface method to model the molecular interactions explicitly. The resulting thermodynamic data gives useful information about the amino acids with the greatest association for brassinolide and the stabilities of such complexes. Density functional theory (DFT) optimizations were further carried out to test the performance of semiempirical calculations. Additional calculations with a more accurate DFT method were performed to explore the formation of this type of molecular complexes. The semiempirical geometries and stability order of these complexes are in good agreement with the DFT calculations. Each group of amino acids possesses a preferential zone of interaction with brassinolide, forming the polar-charged amino acids the most stable complexes. This study could contribute to future investigations of the interaction of brassinosteroids with the receptor protein in plants.

In silico study of the human rhodopsin and meta rhodopsin II/S-arrestin complexes: Impact of single point mutations related to retina degenerative diseases

We propose two models of the human S‐arrestin/rhodopsin complex in the inactive dark adapted rhodopsin and meta rhodopsin II form, obtained by homology modeling and knowledge based docking. First, a homology model for the human S‐arrestin was built and validated by molecular dynamics, showing an average root mean square deviation difference from the pattern behavior of 0.76 Å. Then, combining the human S‐arrestin model and the modeled structure of the two human rhodopsin forms, we propose two models of interaction for the human S‐arrestin/rhodopsin complex. The models involve two S‐arrestin regions related to the N domain (residues 68–78; 170–182) and a third constituent of the C domain (248–253), with the rhodopsin C terminus (330–348). Of the 22 single point mutations related to retinitis pigmentosa and congenital night blindness located in the cytoplasmatic portion of rhodopsin or in S‐arrestin, our models locate 16 in the interaction region and relate two others to possible dimer formation. Our calculations also predict that the light activated complex is more stable than the dark adapted rhodopsin and, therefore, of higher affinity to S‐arrestin. Proteins 2008.

Assessing How Correlated Molecular Orbital Calculations Can Perform versus Kohn–Sham DFT: Barrier Heights/Isomerizations

To assess the title issue, 38 hydrogen transfer barrier heights and 38 non-hydrogen transfer barrier heights/isomerizations extracted from extensive databases have been considered, in addition to 4 2 p-isomerization reactions and 6 others for large organic molecules. All Kohn-Sham DFT calculations have employed the popular M06-2X functional, whereas the correlated molecular orbital (MO)-based ones are from single-reference MP2 and CCSD(T) methods. They have all utilized the same basis sets, with raw MO energies subsequently extrapolated to the complete basis set limit without additional cost. MP2 calculations are found to be as cost-effective as DFT ones and often slightly more, while showing a satisfactory accuracy when compared with the reference data. Although the focus is on barrier heights, the results may bear broader implications, in that one may see successes and difficulties of DFT when compared with traditional MO theories for the same data.

Conceptual DFT analysis of the regioselectivity of 1,3-dipolar cycloadditions: nitrones as a case of study

The regioselectivity of the 1,3-dipolar cycloaddition of a model nitrone with a set of dipolarophiles, presenting diverse electronic effects, is analyzed using conceptual density functional theory (DFT) methods. We deviate from standard approaches based on frontier molecular orbitals and formulations of the local hard/soft acid/base principle and use instead the dual descriptor. A detailed analysis is carried out to determine the influence of the way to calculate the dual descriptor, the computational procedure, basis set and choice of method to condensate the values of this descriptor. We show that the qualitative regioselectivity predictions depend on the choice of “computational conditions”, something that indicates the danger of using black-box computational set-ups in conceptual DFT studies.

Electron density deformations provide new insights into the spectral shift of rhodopsins

Spectral shifts of rhodopsin, which are related to variations of the electron distribution in 11‐cis‐retinal, are investigated here using the method of deformed atoms in molecules. We found that systems carrying the M207R and S186W mutations display large perturbations of the π‐conjugated system with respect to wild‐type rhodopsins. These changes agree with the predicted behavior of the bond length alternation (BLA) and the blue shifts of vertical excitation energies of these systems. The effect of the planarity of the central and Schiff‐base regions of retinal chain on the electronic structure of the chromophore is also investigated. By establishing nonlinear polynomial relations between BLA, chain distortions, and vertical excitation energies, we are also able to provide a semiquantitative approach for the understanding of the mechanisms regulating spectral shifts in rhodopsin and its mutants.

MMH-2 as a new approach for the prediction of intermolecular interactions: the crystal packing of acetamide

A new approach (MMH-2) was applied and tested for the prediction of intermolecular interactions in the crystal packing of acetamide. In MMH-2, energies of random molecular interaction configurations are computed. It uses molecular association quantities from statistical thermodynamics in order to obtain intermolecular interaction motifs that follow a ranking process. The most important motifs are optimized. Here, the AM1 semiempirical Hamiltonian was applied for the calculation and optimization of each obtained configuration and a comparison to MP2 results is provided. Such a stepwise procedure follows the assumed genesis of crystal growth without using experimental input. For evaluation purposes, graph set analysis was used to classify the structural patterns of both acetamide polymorphs. It was also necessary to introduce a new geometrical similarity index for the comparison of calculated and experimental motifs. As a result, all experimental hydrogen bond patterns were found and molecular synthons in both polymorphic acetamide structures were predicted as local minima. This suggests a new strategy for crystal structure prediction of flexible molecules with a possible subsequent progress in crystal engineering in silico.