QSAR-assisted design of an environmental catalyst for enhanced estrogen remediation

Application of Various Molecular Modelling Methods in the Study of Estrogens and Xenoestrogens

In this review, applications of various molecular modelling methods in the study of estrogens and xenoestrogens are summarized. Selected biomolecules that are the most commonly chosen as molecular modelling objects in this field are presented. In most of the reviewed works, ligand docking using solely force field methods was performed, employing various molecular targets involved in metabolism and action of estrogens. Other molecular modelling methods such as molecular dynamics and combined quantum mechanics with molecular mechanics have also been successfully used to predict the properties of estrogens and xenoestrogens. Among published works, a great number also focused on the application of different types of quantitative structure-activity relationship (QSAR) analyses to examine estrogen's structures and activities. Although the interactions between estrogens and xenoestrogens with various proteins are the most commonly studied, other aspects such as penetration of estrogens through lipid bilayers or their ability to adsorb on different materials are also explored using theoretical calculations. Apart from molecular mechanics and statistical methods, quantum mechanics calculations are also employed in the studies of estrogens and xenoestrogens. Their applications include computation of spectroscopic properties, both vibrational and Nuclear Magnetic Resonance (NMR), and also in quantum molecular dynamics simulations and crystal structure prediction. The main aim of this review is to present the great potential and versatility of various molecular modelling methods in the studies on estrogens and xenoestrogens.

Polymerization of micropollutants in natural aquatic environments: A review

Micropollutants with high ecotoxicological risks are frequently detected in aquatic environments, which has aroused great concern in recent years. Humification is one of the most important natural detoxification processes of aquatic micropollutants, and the core reactions of this process are polymerization and coupling. During humification, micropollutants are incorporated into the macrostructures of humic substances and precipitated from aqueous systems into sediments. However, the similarities and differences among the polymerization/coupling pathways of micropollutants in different oxidative systems have not been systematically summarized in a review. This article reviews the current knowledge on the weak oxidation-induced spontaneous polymerization/coupling transformation of micropollutants. First, four typical weak oxidative conditions for the initiation of micropollutant polymerization reactions in aquatic environments are compared: enzymatic catalysis, biomimetic catalysis, metal oxide oxidation, and photo-initiated oxidation. Second, three major subsequent spontaneous transformation pathways of micropollutants are elucidated: radical polymerization, nucleophilic addition/substitution and cyclization. Different solution conditions are also summarized. Furthermore, the importance of toxicity evolution during the weak oxidation-induced coupling/polymerization of micropollutants is particularly emphasized. This review provides a new perspective for the transformation mechanism and pathways of micropollutants from aquatic systems into sediments and the atmosphere and offers theoretical support for developing micropollutant control technologies.

A receptor dependent-4D QSAR approach to predict the activity of mutated enzymes

Screening and selection tools to obtain focused libraries play a key role in successfully engineering enzymes of desired qualities. The quality of screening depends on efficient assays; however, a focused library generated with a priori information plays a major role in effectively identifying the right enzyme. As a proof of concept, for the first time, receptor dependent - 4D Quantitative Structure Activity Relationship (RD-4D-QSAR) has been implemented to predict kinetic properties of an enzyme. The novelty of this study is that the mutated enzymes also form a part of the training data set. The mutations were modeled in a serine protease and molecular dynamics simulations were conducted to derive enzyme-substrate (E-S) conformations. The E-S conformations were enclosed in a high resolution grid consisting of 156,250 grid points that stores interaction energies to generate QSAR models to predict the enzyme activity. The QSAR predictions showed similar results as reported in the kinetic studies with >80% specificity and >50% sensitivity revealing that the top ranked models unambiguously differentiated enzymes with high and low activity. The interaction energy descriptors of the best QSAR model were used to identify residues responsible for enzymatic activity and substrate specificity.

Understanding ligninase-mediated reactions of endocrine disrupting chemicals in water: reaction rates and quantitative structure-activity relationships

We have verified in our previous work that lignin peroxidase (LiP) mediates effective removal of selected natural and synthetic estrogens. The efficiency of these reactions was greatly enhanced in the presence of veratryl alcohol (VA), a chemical that is produced along with LiP by certain white rot fungi, for example, Phanerochaete chrysosporium. In this study, we systematically evaluated the kinetic behaviors of LiP-mediated reactions for six endocrine disrupting compounds (EDCs), that is, steroid estrogens and their structural analogs, in both the presence and absence of VA. Resulting kinetic parameters were then correlated with structural features of LiP/substrate binding complexes, as quantified using molecular simulation, to create quantitative structure-activity relationship (QSAR) equations. These equations suggest that binding distance between a substrate's phenolic proton and δN of HIS47's imidazole ring plays an important role in modulating substrate reactivity toward LiP in both the presence and absence of VA. This information provides insight into an important enzymatic reaction process that occurs in the natural environment affecting EDC transformation, a process that may be used in engineered systems to achieve EDC removal from water.