Computational study of the hydrogen peroxide scavenging mechanism of allyl methyl disulfide, an antioxidant compound from garlic.

Although many sulfur containing garlic compounds present antioxidant activity, little is known about molecular mechanisms through which these compounds react with reactive oxygen species. In this work, the reactivity and the hydrogen peroxide scavenger reaction mechanisms (including thermodynamics and kinetics aspects) of allyl methyl disulfide in aqueous phase are studied employing density functional theory computational methods. Three reactive sites susceptible for electrophilic attack are found over sulfur atoms and the double bond allyl moiety. For each detected site, one redox reaction is proposed and analyzed. All reactions are thermodynamically feasible, whereas attack over the methyl bound sulfur atom is kinetically favored.

About endothermic sorption of tyrosine on chitosan films.

Sorption of l- and d-Tyrosine (Tyr) from aqueous solutions on chiral membranes of chitosan (CH) was studied. A high adsorption in the membrane, with a marked enantioselectivity to l-Tyr, was found. Computational calculations carried out by docking and molecular dynamics (MD) showed a difference in the affinity of the enantiomers and two regions of adsorption in the polymer matrix. The interactions of the enantiomers with the polymer matrix were studied by using FTIR, DRx, DSC and TG measurements. These results indicate that adsorption of Tyr reduces the crystallinity of the membrane and generates a rearrangement of the chains, decreasing the intercatenary spacing. Also, it was observed that the hydrated polymorph to anhydrous polymorph ratio has changed during adsorption, that is, water bound to chitosan is also modified. The energy balance of the system hydrogen bonding, desolvation and the conformational changes resulted in a spontaneous and endothermic process.

Conformation-Independent QSPR Approach for the Soil Sorption Coefficient of Heterogeneous Compounds.

We predict the soil sorption coefficient for a heterogeneous set of 643 organic non-ionic compounds by means of Quantitative Structure-Property Relationships (QSPR). A conformation-independent representation of the chemical structure is established. The 17,538 molecular descriptors derived with PaDEL and EPI Suite softwares are simultaneously analyzed through linear regressions obtained with the Replacement Method variable subset selection technique. The best predictive three-descriptors QSPR is developed on a reduced training set of 93 chemicals, having an acceptable predictive capability on 550 test set compounds. We also establish a model with a single optimal descriptor derived from CORAL freeware. The present approach compares fairly well with a previously reported one that uses Dragon descriptors.

QSAR and 3D-QSAR studies applied to compounds with anticonvulsant activity.

INTRODUCTION: Quantitative structure-activity relationships (QSAR and 3D-QSAR) have been applied in the last decade to obtain a reliable statistical model for the prediction of the anticonvulsant activities of new chemical entities. However, despite the large amount of information on QSAR, no recent review has published and discussed this data in detail. AREAS COVERED: In this review, the authors provide a detailed discussion of QSAR studies that have been applied to compounds with anticonvulsant activity published between the years 2003 and 2013. They also evaluate the mathematical approaches and the main software used to develop the QSAR and 3D-QSAR model. EXPERT OPINION: QSAR methodologies continue to attract the attention of researchers and provide valuable information for the development of new potentially active compounds including those with anticonvulsant activity. This has been helped in part by improvements in the size and performance of computers; the development of specific software and the development of novel molecular descriptors, which have given rise to new and more predictive QSAR models. The extensive development of descriptors, and the way by which descriptor values are derived, have allowed the evolution of the QSAR methods. This evolution could strengthen the QSAR methods as an important tool in research and development of new and more potent anticonvulsant agents.

Lacosamide derivatives with anticonvulsant activity as carbonic anhydrase inhibitors. Molecular modeling, docking and QSAR analysis.

Lacosamide is an anticonvulsant drug which presents carbonic anhydrase inhibition. In this paper, we analyzed the apparent relationship between both activities performing a molecular modeling, docking and QSAR studies on 18 lacosamide derivatives with known anticonvulsant activity. Docking results suggested the zinc-binding site of carbonic anhydrase is a possible target of lacosamide and lacosamide derivatives making favorable Van der Waals interactions with Asn67, Gln92, Phe131 and Thr200. The mathematical models revealed a poor relationship between the anticonvulsant activity and molecular descriptors obtained from DFT and docking calculations. However, a QSAR model was developed using Dragon software descriptors. The statistic parameters of the model are: correlation coefficient, R=0.957 and standard deviation, S=0.162. Our results provide new valuable information regarding the relationship between both activities and contribute important insights into the essential molecular requirements for the anticonvulsant activity.

In silico modeling of the molecular structure and binding of leukotriene A4 into leukotriene A4 hydrolase.

A combined molecular docking and molecular structure in silico analysis on the substrate and product of leukotriene A4 hydrolase (LTA4H) was performed. The molecular structures of the substrate leukotriene A4 (LTA4) and product leukotirene B4 (LTB4) were studied through density functional theory (DFT) calculations at the B3LYP/6-31 + G(d) level of theory in both gas and condensed phases. The whole LTB4 molecule was divided into three fragments (hydrophobic tail, triene motif, and a polar acidic group) that were subjected to a full conformational study employing the most stable conformations of them to build conformers of the complete molecule and geometry optimize further. LTA4 conformers' structures were modeled from the LTB4 minimum energy conformers. Both protonated and deprotonated species of LTA4 and LTB4 were analyzed according to pKa values found in the literature. Finally, a binding model of LTA4 with LTA4 hydrolase is proposed according to docking results that show intermolecular interactions that position the protonated and deprotonated ligand in the active site, in excellent agreement with the model suggested from LTA4H-inhibitors crystallographic data.

QSAR study and molecular design of open-chain enaminones as anticonvulsant agents.

Present work employs the QSAR formalism to predict the ED(50) anticonvulsant activity of ringed-enaminones, in order to apply these relationships for the prediction of unknown open-chain compounds containing the same types of functional groups in their molecular structure. Two different modeling approaches are applied with the purpose of comparing the consistency of our results: (a) the search of molecular descriptors via multivariable linear regressions; and (b) the calculation of flexible descriptors with the CORAL (CORrelation And Logic) program. Among the results found, we propose some potent candidate open-chain enaminones having ED(50) values lower than 10 mg·kg(-1) for corresponding pharmacological studies. These compounds are classified as Class 1 and Class 2 according to the Anticonvulsant Selection Project.