Jerzy Leszczynski

Advancing risk assessment of engineered nanomaterials: Application of computational approaches

Nanotechnology that develops novel materials at size of 100nm or less has become one of the most promising areas of human endeavor. Because of their intrinsic properties, nanoparticles are commonly employed in electronics, photovoltaic, catalysis, environmental and space engineering, cosmetic industry and - finally - in medicine and pharmacy. In that sense, nanotechnology creates great opportunities for the progress of modern medicine. However, recent studies have shown evident toxicity of some nanoparticles to living organisms (toxicity), and their potentially negative impact on environmental ecosystems (ecotoxicity). Lack of available data and low adequacy of experimental protocols prevent comprehensive risk assessment. The purpose of this review is to present the current state of knowledge related to the risks of the engineered nanoparticles and to assess the potential of efficient expansion and development of new approaches, which are offered by application of theoretical and computational methods, applicable for evaluation of nanomaterials.

Interactions of electrons with bare and hydrated biomolecules: from nucleic acid bases to DNA segments.

Nucleic Acid Bases to DNA Segments Jiande Gu,*,† Jerzy Leszczynski,‡ and Henry F. Schaefer III* †Drug Design& DiscoveryCenter, State Key Laboratory of Drug Research, Shanghai Instituteof Materia Medica, Shanghai Institutes for BiologicalSciences, CAS, Shanghai 201203, P. R. China ‡Interdisciplinary NanotoxicityCenter, Department of Chemistry and Biochemistry, JacksonState University, Jackson, Mississippi 39217, UnitedStates Center for ComputationalQuantumChemistry, University of Georgia, Athens,Georgia 30602-2525, United States

Novel application of the CORAL software to model cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli.

Convenient to apply and available on the Internet software CORAL (http://www.insilico.eu/CORAL) has been used to build up quantitative structure-activity relationships (QSAR) for prediction of cytotoxicity of metal oxide nanoparticles to bacteria Escherichia coli (minus logarithm of concentration for 50% effect pEC50). In this study six random splits of the data into the training and test set were examined. It has been shown that the CORAL provides a reliable tool that could be used to build up a QSAR of the pEC50.

Room temperature synthesis of PbSe quantum dots in aqueous solution: stabilization by interactions with ligands

An aqueous route of synthesis is described for rapid synthesis of lead selenide quantum dots (PbSe QDs) at room temperature in an attempt to produce water-soluble and stable nanocrystals. Several thiol-ligands, including thioglycolic acid (TGA), thioglycerol (TGC), 3-mercaptopropionic acid (MPA), 2-mercaptoethylamine hydrochloride (MEA), 6-mercaptohexanoic acid (MHA), and l-cysteine (l-cys), were used for capping/stabilization of PbSe QDs. The effects of the ligands on the stability of PbSe QDs were evaluated for a period of two months at room temperature under normal light conditions and at 4 °C in the dark. The TGA- and MEA-capped QDs exhibited the highest stability prior to purification, almost two months when kept in the dark at 4 °C. However, the stability of TGA-capped QDs was reduced substantially after purification to about 5 days under the same conditions, while MEA-capped QDs did not show any significant instability. The stabilization energies of Pb-thiolate complexes determined by theoretical DFT simulations supported the experimental results. The PbSe QDs capped with TGA, MPA and MEA were successfully purified and re-dispersed in water, while those stabilized with TGC, MHA and l-cys aggregated during purification attempts. The purified PbSe QDs possess very susceptible surface resulting in poor stability for about 30-45 min after re-dispersion in water. In the presence of an excess of free ligand, the stability increased up to 5 days for TGA-capped QDs at pH 7.19, 9-12 days for MPA-capped QDs at pH 7.3-7.5 and 45-47 days for MEA-capped QDs at pH 7.35. X-Ray diffraction (XRD) results showed that the QDs possess a cubic rock salt structure with the most intense peaks located at 2θ = 25.3° (200) and 2θ = 29.2° (100). TEM images showed that the size of the QDs ranges between 5 and 10 nm. ICP-MS results revealed that Pb : Se ratios were 1.26, 1.28, 3.85, 1.18, and 1.31 for the QDs capped with TGA, MPA, MEA, l-cys, and TGC, respectively. The proposed method is inexpensive, simple and utilizes environmentally friendly chemicals and solvents.

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

The rate constants (KOH) 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 (r2) 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.

DFT M06-2X investigation of alkaline hydrolysis of nitroaromatic compounds

The nitroaromatic compounds 2,4,6-trinitrotoluene (TNT), 2,4-dinitrotoluene (DNT) and 2,4-dinitroanisole (DNAN) are potential environmental contaminants and their transformations under a variety of environmental conditions are consequently of great interest. One possible method to safely degrade these nitrocompounds is alkaline hydrolysis. A mechanism of the initial stages of this reaction was investigated computationally. Simulations of UV-VIS and NMR spectra for this mechanism were also produced. The results obtained were compared to available experimental data on the alkaline hydrolysis of TNT and suggest that the formation of Meisenheimer complexes and an anion of TNT are potential first-step intermediates in the reaction path. As the reaction proceeds, computational results indicate that polynegative complexes dominate the degradation pathway, followed by cycles of carbon chain opening and breaking. A second possible pathway was identified that leads to polymeric products through Janovsky complex formation. Results from this study indicate that the order of increasing resistance to alkaline hydrolysis is TNT, DNT and DNAN.

QSAR models for ACE-inhibitor activity of tri-peptides based on representation of the molecular structure by graph of atomic orbitals and SMILES

The CORAL software (http:/www.insilico.eu/CORAL) has been examined as a tool of modeling of the angiotensin-converting enzyme-inhibitor activity of 54 tri-peptides. Three versions of the models were examined: (i) models based on the graph of atomic orbitals (GAO); (ii) models based on the simplified molecular input-line entry systems (SMILES); and (iii) hybrid models based on both GAO and SMILES. The hybrid models have provided the best prediction. The robustness of the approach has been checked with four random splits into training set and test set.

Predictions of Gibbs Free Energies for the Adsorption of Polyaromatic and Nitroaromatic Environmental Contaminants on Carbonaceous Materials: Efficient Computational Approach

The adsorption of benzene, polycyclic aromatic hydrocarbons (PAHs), and nitroaromatic compounds (NACs) on the carbonaceous surfaces from the gas phase and water solution was investigated. Several different levels of theory were applied, including DFT-, MP2-, and CCSD(T)-based methods, to find an approach that is computationally inexpensive and can provide accurate thermodynamic parameters for studied adsorption phenomena. The methods and techniques used (including cluster and periodic approximations) were evaluated on the basis of comparison with available experimental data. The optimized structures of calculated complexes are obtained, and the interaction energies and Gibbs free energies are predicted. Good agreement was revealed for the theoretical and experimental adsorption energies of benzene and PAHs adsorbed on the carbon surfaces. The adsorption of benzene, PAHs, and NACs on carbon is suggested to be effective from the gas phase for all studied compounds and for PAHs and NACs also from water solution at room temperature.

The electronic spectra and the H‐bonding pattern of the sulfur and selenium substituted guanines

The density functional theory (DFT) with B3LYP, M05‐2x, and M06‐2x functionals, along with the 6‐311+G(d, p) basis set, were used in the study of the UV absorption spectra and the H‐bonding pairing patterns of the sulfur and selenium substituted guanines. The time‐dependent DFT calculations reveal that the red‐shifts of the transition energies predicted for guanine for the first gas‐phase observable transition amount to 55 nm for S6mG and 86 nm for Se6mG, respectively. These changes in the transition energies are qualitatively comparable to the experimental data for substituted guanines in DNA. The density deformation map reveals that both sulfur and selenium atoms exhibit lesser conjugated with the purine ring, which leads to the small transition energies in S6mG and Se6mG. The decrease in binding energy (3 kcal/mol) of Se6mGmC as compared to that of mGmC is well related to the observation of the melting temperature difference ΔTm ∼3.9 °C for the Se‐DNA versus DNA. The molecular recognition (mGmC pairing) pattern is found to be changed significantly due to the replacement of O6 by S or Se. The substantial base–base plane twisting revealed in this study suggests that the base stacking in the DNA might be interrupted. This study shows that the red‐shifts of the transition energies predicted by the M05‐2x and M06‐2x functionals are close to those revealed by the B3LYP calculations. As M05‐2x and M06‐2x offer better descriptions for the dispersion interactions, they provide efficient approaches to investigate the influences of the base‐stacking on the transition energies.

Molecular Recognition at Methyl Methacrylate/n-Butyl Acrylate (MMA/nBA) Monomer Unit Boundaries of Phospholipids at p-MMA/ nBA Copolymer Surfaces

Lipid structural features and their interactions with proteins provide a useful vehicle for further advances in membrane proteins research. To mimic one of potential lipid-protein interactions we synthesized poly(methyl methacrylate/ n-butyl acrylate) (p-MMA/nBA) colloidal particles that were stabilized by phospholipid (PLs). Upon the particle coalescence, PL stratification resulted in the formation of surface localized ionic clusters (SLICs). These entities are capable of recognizing MMA/nBA monomer interfaces along the p-MMA/nBA copolymer backbone and form crystalline SLICs at the monomer interface. By utilizing attenuated total reflectance Fourier transform infrared (ATR FT-IR) spectroscopy and selected area electron diffraction (SAD) combined with ab initio calculations, studies were conducted that identified the origin of SLICs as well as their structural features formed on the surface of p-MMA/nBA copolymer films stabilized by 1,2-dilauroyl-sn-glycero-3-phosphocholine (DLPC) PL. Specific entities responsible for SLIC formation are selective noncovalent bonds of anionic phosphate and cationic quaternary ammonium segments of DLPC that interact with two neighboring carbonyl groups of nBA and MMA monomers of the p-MMA/nBA polymer backbone. To the best of our knowledge this is the first example of molecular recognition facilitated by coalescence of copolymer colloidal particles and the ability of PLs to form SLICs at the boundaries of the neighboring MMA and nBA monomer units of the p-MMA/nBA chain. The dominating noncovalent bonds responsible for the molecular recognition is a combination of H-bonding and electrostatic interactions.