In silico kinetics of alkaline hydrolysis of 1,3,5-trinitro-1,3,5-triazinane (RDX): M06-2X investigation.

Alkaline hydrolysis of RDX (hexahydro-1,3,5-trinitro-1,3,5-triazine), as one of the most promising methods for nitrocompound remediation, was investigated computationally at the PCM(Pauling)/M06-2X/6-311++G(d,p) level of theory. Computational simulation shows that RDX hydrolysis is a highly exothermic multistep process involving initial deprotonation and nitrite elimination, cycle cleavage, further transformation of cycle-opened intermediates to end products caused by a series of C-N bond ruptures, hydroxide attachments, and proton transfers. Computationally predicted products of RDX hydrolysis such as nitrite, nitrous oxide, formaldehyde, formate, and ammonia correspond to experimentally observed ones. Accounting of specific hydration of hydroxide is critical to create an accurate kinetic model for alkaline hydrolysis. Simulated kinetics of the hydrolysis are in good agreement with available experimental data. A period of one month is necessary for 99% RDX decomposition at pH 10. Computations predict significant increases of the reaction rate of hydrolysis at pH 11, pH 12, and pH 13.

Aconitum and delphinium diterpenoid alkaloids of local anesthetic activity: comparative QSAR analysis based on GA-MLRA/PLS and optimal descriptors approach.

The duration of anesthesia (related to protein binding of a drug) and the onset time (determined by the pKa) are important characteristics in assessment of local anesthetic agents. They are known to be affected by a number of factors. Early studies of antiarrhythmic diterpenoid alkaloids from plants Aconitum and Delphinium suggested that they possess local anesthetic activity due to their ability to suppress sodium currents of excited membranes. In this study we utilized toxicity, duration, and onset of action as endpoints to construct Quantitative Structure-Activity Relationship (QSAR) models for the series of 34 diterpenoid alkaloids characterized by local anesthetic activity using genetic algorithm-based multiple linear regression analysis/partial least squares and simplified molecular input line entry system (SMILES)-based optimal descriptors approach. The developed QSAR models correctly reflected factors that determine three endpoints of interest. Toxicity correlates with descriptors describing partition and reactivity of compounds. The duration of anesthesia was encoded by the parameters defining the ability of a compound to bind at the receptor site. The size and number of H-bond acceptor atoms were found not to favor the speed of onset, while topographic electronic descriptor demonstrated strong positive effect on it. SMILES-based optimal descriptors approach resulted in overall improvement of models. This approach was shown to be more sensitive to structural peculiarities of molecules than regression methods. The results clearly indicate that obtained QSARs are able to provide distinct rationales for compounds optimization with respect to particular endpoint.

Immunotoxicity of nanoparticles: a computational study suggests that CNTs and C60 fullerenes might be recognized as pathogens by Toll-like receptors.

Over the last decade, a great deal of attention has been devoted to study the inflammatory response upon exposure to multi/single-walled carbon nanotubes (CNTs) and different fullerene derivatives. In particular, carbon nanoparticles are reported to provoke substantial inflammation in alveolar and bronchial epithelial cells, epidermal keratinocytes, cultured monocyte-macrophage cells, etc. We suggest a hypothetical model providing the potential mechanistic explanation for immune and inflammatory responses observed upon exposure to carbon nanoparticles. Specifically, we performed a theoretical study to analyze CNT and C60 fullerene interactions with the available X-ray structures of Toll-like receptors (TLRs) homo- and hetero-dimer extracellular domains. This assumption was based on the fact that similar to the known TLR ligands both CNTs and fullerenes induce, in cells, the secretion of certain inflammatory protein mediators, such as interleukins and chemokines. These proteins are observed within inflammation downstream processes resulted from the ligand molecule dependent inhibition or activation of TLR-induced signal transduction. Our computational studies have shown that the internal hydrophobic pockets of some TLRs might be capable of binding small-sized carbon nanostructures (5,5 armchair SWCNTs containing 11 carbon atom layers and C60 fullerene). High binding scores and minor structural alterations induced in TLR ectodomains upon binding C60 and CNTs further supported our hypothesis. Additionally, the proposed hypothesis is strengthened by the indirect experimental findings indicating that CNTs and fullerenes induce an excessive expression of specific cytokines and chemokines (i.e. IL-8 and MCP1).

Evaluation criteria for the quality of published experimental data on nanomaterials and their usefulness for QSAR modelling.

Nowadays nanotechnology is one of the most promising areas of science. The number and quantity of synthesized nanomaterials increase exponentially, therefore it is reasonable to expect that comprehensive risk assessment based only on empirical testing of all novel engineered nanoparticles (NPs) will very soon become impossible. Hence, the development of computational methods complementary to experimentation is very important. Quantitative structure-property relationship (QSPR) and quantitative structure-activity relationship (QSAR) models widely used in pharmaceutical chemistry and environmental science can also be modified and adopted for nanotechnology to predict physico-chemical properties and toxicity of empirically untested nanomaterials. All QSPR/QSAR modelling activities are based on experimentally derived data. It is important that, within a given data set, all values should be consistent, of high quality and measured according to a standardized protocol. Unfortunately, the amount of such data available for engineered nanoparticles in various data sources (i.e. databases and the literature) is very limited and seldom measured with a standardized protocol. Therefore, we have proposed a framework for collecting and evaluating the existing data, with the focus on possible applications for computational evaluation of properties and biological activities of nanomaterials.

CORAL: Monte Carlo Method as a Tool for the Prediction of the Bioconcentration Factor of Industrial Pollutants.

The CORAL software (http://www.insilico.eu/coral/) has been evaluated for application in QSAR modeling of the bioconcentration factor in fish (logBCF). The data used include 237 organic substances (industrial pollutants). Six random splits of the data into sub-training (30-50 %), calibration (20-30 %), test (13-30 %), and validation sets (7-25 %) have been carried out. The following numbers display the average statistical characteristics of the models for the external validation set: correlation coefficient r(2) =0.880±0.017 and standard error of estimation s=0.559±0.131. The best models were obtained with a combined representation of the molecular structure by SMILES together with hydrogen suppressed graph.

CORAL: QSPR modeling of rate constants of reactions between organic aromatic pollutants and hydroxyl radical.

The rate constants (K(OH)) of reactions between 78 organic aromatic pollutants and hydroxyl radical were examined. Simplified molecular input line entry system was used as representation of the molecular structure of the pollutants. Quantitative structure-property relationships was developed using CORAL software (http://www.insilico.eu/CORAL) for four random splits of the data into the subtraining, calibration, and test sets. The obtained results reveal good predictive potential of the applied approach: correlation coefficients (r(2)) for the test sets of the four random splits are 0.75, 0.91, 0.84, and 0.80. Using the Monte Carlo method CORAL software generated the optimal descriptors for one-variable models. The reproducibility of each model was tested performing three runs of the Monte Carlo optimization. The current data were compared to previous results and discussed.

CORAL: classification model for predictions of anti-sarcoma activity.

A modified version of the CORAL software (http://www.insilico.eu/coral) allows building up the classification model for the case of the Yes/No data on the anti-sarcoma activity of organic compounds. Three random splits into the sub-training, calibration, and test sets of the data for 3017 compounds were examined. The performance of the proposed approach is satisfactory. The average values of the statistical characteristics for external test set on three random splits are as follows: n=1173-1234, sensitivity = 0.8903±0.0390, specificity = 0.9869±0.0013, and accuracy = 0.9759±0.0043. Mechanistic interpretation of the suggested model is discussed.

CORAL: quantitative structure-activity relationship models for estimating toxicity of organic compounds in rats.

For six random splits, one-variable models of rat toxicity (minus decimal logarithm of the 50% lethal dose [pLD50], oral exposure) have been calculated with CORAL software (http://www.insilico.eu/coral/). The total number of considered compounds is 689. New additional global attributes of the simplified molecular input line entry system (SMILES) have been examined for improvement of the optimal SMILES-based descriptors. These global SMILES attributes are representing the presence of some chemical elements and different kinds of chemical bonds (double, triple, and stereochemical). The "classic" scheme of building up quantitative structure-property/activity relationships and the balance of correlations (BC) with the ideal slopes were compared. For all six random splits, best prediction takes place if the aforementioned BC along with the global SMILES attributes are included in the modeling process. The average statistical characteristics for the external test set are the following: n = 119 ± 6.4, R(2) = 0.7371 ± 0.013, and root mean square error = 0.360 ± 0.037.

Aconitum and Delphinium alkaloids of curare-like activity. QSAR analysis and molecular docking of alkaloids into AChBP.

Early studies have shown that some of diterpenoid alkaloids, found in highly toxic plants of the genera Aconitum and Delphinium, act at neuronal nicotinic acetylcholine receptors (nAChRs) and exhibit potent N-cholinolytic activity. In the current study, GA-MLRA and GA-PLS approaches have been used to build QSAR models to predict N-cholinolytic activity measured in vivo (blockade of neuromuscular conductivity, BNMC and third eyelid relaxing activity, TYRA) and in vitro (suppression of frog's abdominal straight muscles on acetylcholine, SAM) for a series of diterpenoid alkaloids. Random splitting of a data set (five trials in total) produced QSAR models of a good level of correlation between experimental in vitro/in vivo and calculated N-cholinolytic activity expressed as log(1/ED(50)) with following average statistical parameters: log BNMC (r(2) = 0.87, s = 0.14, q(2) = 0.82), log TYRA (r(2) = 0.80, s = 0.29, q(2) = 0.67), log SAM (r(2) = 0.84, s = 29, q(2) = 0.64). QSAR results suggest descriptors accounting for H-bond capability of molecules influence all three type of N-cholinolytic activity with additional contribution of steric and reactivity features as identified for TYRA and SAM data, respectively. The alkaloid-receptor complexes were further analyzed by means of AutoDock Vina docking program using the binding site of MLA complexed with AChBP (homolog of the ligand binding domain of nAChRs) as template. All compounds were shown to be well fitted in the binding pocket of native MLA with good correlation exhibited between their ED(50) and AutoDock Vina binding free energy. An analysis of the possible factors significant for the ligand recognition has been enhanced by comparative docking studies performed for structurally related lycoctonine-type alkaloids (lappaconitine and aconitine) that are known to bind to voltage-gated Na(+) channel, but not to nAChRs.

Theoretical study of adsorption of sarin and soman on tetrahedral edge clay mineral fragments.

This study provides details of the structure and interactions of Sarin and Soman with edge tetrahedral fragments of clay minerals. The adsorption mechanism of Sarin and Soman on these mineral fragments containing the Si(4+) and Al(3+) central cations was investigated. The calculations were performed using the B3LYP and MP2 levels of theory in conjunction with the 6-31G(d) basis set. The studied systems were fully optimized. Optimized geometries, adsorption energies, and Gibbs free energies of Sarin and Soman adsorption complexes were computed. The number and strength of formed intermolecular interactions have been analyzed using the AIM theory. The charge of the systems and a termination of the mineral fragment are the main contributing factors on the formation of intermolecular interactions in the studied systems. In the neutral complexes, Sarin and Soman is physisorbed on these mineral fragments due to the formation of C-H...O, and O-H...O hydrogen bonds. The chemical bond is formed between a phosphorus atom of Sarin and Soman and an oxygen atom of the -2 charged clusters containing an Al(3+) central cation and -1 charged complex containing a Si(4+) central cation (chemisorption). Sarin and Soman interact mostly in the same way with the same terminated edge mineral fragments containing different central cations. However, the interaction energies of the complexes with an Al(3+) central cation are larger than these values for the Si(4+) complexes. The interaction enthalpies of all studied systems corrected for the basis set superposition error were found to be negative. However, on the basis of the Gibbs free energy values, only strongly interacting complexes containing a charged edge mineral fragment with an Al(3+) central cation are stable at room temperature. We can conclude that Sarin and Soman will be adsorbed preferably on this type of edge mineral surfaces. Moreover, on the basis of the character of these edge surfaces, a tetrahedral edge mineral fragment can provide effective centers for the dissociation.

Principles of magnetodynamic chemotherapy.

Basic principles of a novel method of cancer treatment are explained. Method is based on the thermal activation of an inactive prodrug encapsulated in magnetoliposomes via Neél and Brown effects of inductive heating of subdomain superparamagnetic particles to sufficiently high temperatures. This principle may be combined with targeted drug delivery (using constant magnetic field) and controlled release (using high-frequency magnetic field) of an activated drug entrapped in magnetoliposomes. Using this method drug may be applied very selectively in the particular site of organism and this procedure may be repeated several times using e.g. stealth magnetoliposomes which are circulating in a blood-stream for several days. Moreover the magnetoliposomes concentrated by external constant magnetic field in tumor vasculature may lead to embolic lesions and necrosis of a tumor body and further the heat produced for thermal activation of a drug enhances the effect of chemotherapy by local hyperthermic treatment of neoplastic cells.

Blood-specific whole-body electromagnetic hyperthermia.

On the basis of the physical properties of magnetic fluids a new technique of whole-body hyperthermia is proposed. Subdomain dextran stabilized magnetite particles injected into the blood-stream can be efficiently heated using an external high-frequency magnetic field, which allows rapid and controllable delivery of heat to the patient's blood, which may be useful for the treatment of cancer and AIDS.

Selective treatment of neoplastic cells using ferritin-mediated electromagnetic hyperthermia.

A new method of cancer treatment is proposed, based on the unique magnetic properties of ferritin iron core which, in alternating magnetic field of frequency approximately 100 kHz, is easily heated to temperatures sufficiently high to destroy neoplastic cells containing an excess of this protein, without damaging the normal cells.

Activation of hematoporphyrin in alternating magnetic field: possible implications for cancer treatment.

A new mechanism of cell damage by alternating magnetic field with hematoporphyrin is described. C6 glioblastoma cell suspensions were exposed to an alternating magnetic field with frequency 180 kHz up to 60 min in the presence of hematoporphyrin in H2O and in D2O. The results presented suggest that an alternating magnetic field is able to activate hematoporphyrin, and this method may be a basis for cancer treatment.