Journal of Computational Chemistry

doi: 10.1002/jcc.24698pmid: N/A

doi: 10.1002/jcc.24600pmid: N/A

Belzunces, Bastien; Hoyau, Sophie; Benoit, Magali; Tarrat, Nathalie; Bessac, Fabienne

doi: 10.1002/jcc.24530pmid: 27862038

Atrazine, a pesticide belonging to the s‐triazine family, is one of the most employed pesticides. Due to its negative impact on the environment, it has been forbidden within the European Union since 2004 but remains abundant in soils. For these reasons, its behavior in soils and water at the atomic scale is of great interest. In this article, we have investigated, using DFT, the adsorption of atrazine onto two different clay surfaces: a pyrophyllite clay and an Mg‐substituted clay named montmorillonite, with Ca2+ compensating cations on its surface. The calculations show that the atrazine molecule is physisorbed on the pyrophyllite surface, evidencing the necessity to use dispersion‐corrected computational methods. The adsorption energies of atrazine on montmorillonite are two to three times larger than on pyrophyllite, depending on the adsorption pattern. The computed adsorption energy is of about −30 kcal mol−1 for the two most stable montmorillonite‐atrazine studied isomers. For these complexes, the large adsorption energy is related to the strong interaction between the chlorine atom of the atrazine molecule and one of the Ca2+ compensating cations of the clay surface. The structural modifications induced by the adsorption are localized: for the surface, close to substitutions and particularly below the Ca2+ cations; in the molecule, around the chlorine atom when Ca2+ interacts strongly with this basic site in a monodentate mode. This study shows the important role of the alkaline earth cations on the adsorption of atrazine on clays, suggesting that the atrazine pesticide retention will be significant in Ca2+‐montmorillonite clays. © 2016 Wiley Periodicals, Inc.

Gan, Li‐Hua; Wu, Rui; Tian, Jian‐Lei; Clarke, Joseph; Gibson, Christopher; Fowler, Patrick W.

doi: 10.1002/jcc.24661pmid: 27813179

An increasing number of observations show that non‐classical isomers may play an important role in the formation of fullerenes and their exo‐ and endo‐derivatives. A quantum‐mechanical study of all classical isomers of C58, C60, and C62, and all non‐classical isomers with at most one square or heptagonal face, was carried out. Calculations at the B3LYP/6‐31G* level show that the favored isomers of C58, C60, and C62 have closely related structures and suggest plausible inter‐conversion and growth pathways among low‐energy isomers. Similarity of the favored structures is reinforced by comparison of calculated ring currents induced on faces of these polyhedral cages by radial external magnetic fields, implying patterns of magnetic response similar to those of the stable, isolated‐pentagon C60 molecule. © 2016 Wiley Periodicals, Inc.

Liu, Song; Zhu, Lizhe; Sheong, Fu Kit; Wang, Wei; Huang, Xuhui

doi: 10.1002/jcc.24664pmid: 27868222

We present an efficient density‐based adaptive‐resolution clustering method APLoD for analyzing large‐scale molecular dynamics (MD) trajectories. APLoD performs the k‐nearest‐neighbors search to estimate the density of MD conformations in a local fashion, which can group MD conformations in the same high‐density region into a cluster. APLoD greatly improves the popular density peaks algorithm by reducing the running time and the memory usage by 2–3 orders of magnitude for systems ranging from alanine dipeptide to a 370‐residue Maltose‐binding protein. In addition, we demonstrate that APLoD can produce clusters with various sizes that are adaptive to the underlying density (i.e., larger clusters at low‐density regions, while smaller clusters at high‐density regions), which is a clear advantage over other popular clustering algorithms including k‐centers and k‐medoids. We anticipate that APLoD can be widely applied to split ultra‐large MD datasets containing millions of conformations for subsequent construction of Markov State Models. © 2016 Wiley Periodicals, Inc.

Cvitkovic, John P.; Kaminski, George A.

doi: 10.1002/jcc.24665pmid: 27859392

We have developed empirical force field parameters for Pt(II) and cisplatin. Two force field frameworks were used—modified OPLS‐AA and our second‐order polarizable POSSIM. A seven‐site model was used for the Pt(II) ion. The goal was to create transferable parameter sets compatible with the force field models for proteins and general organic compounds. A number of properties of the Pt(II) ion and its coordination compounds have been considered, including geometries and energies of the complexes, hydration free energy, and radial distribution functions in water. Comparison has been made with experimental and quantum mechanical results. We have demonstrated that both versions are generally capable of reproducing key properties of the system, but the second‐order polarizable POSSIM formalism permits more accurate quantitative results to be obtained. For example, the energy of formation of cisplatin as calculated with the modified OPLS‐AA exhibited an error of 9.9%, while the POSSIM error for the same quantity was 6.2%. The produced parameter sets are transferable and suitable to be used in protein‐metal binding simulations in which position or even coordination of the ion does not have to be constrained using preexisting knowledge. © 2016 Wiley Periodicals, Inc.

Wang, Cheng; Zhang, Yingkai

doi: 10.1002/jcc.24667pmid: 27859414

The development of new protein–ligand scoring functions using machine learning algorithms, such as random forest, has been of significant interest. By efficiently utilizing expanded feature sets and a large set of experimental data, random forest based scoring functions (RFbScore) can achieve better correlations to experimental protein–ligand binding data with known crystal structures; however, more extensive tests indicate that such enhancement in scoring power comes with significant under‐performance in docking and screening power tests compared to traditional scoring functions. In this work, to improve scoring‐docking‐screening powers of protein–ligand docking functions simultaneously, we have introduced a ΔvinaRF parameterization and feature selection framework based on random forest. Our developed scoring function ΔvinaRF20, which employs 20 descriptors in addition to the AutoDock Vina score, can achieve superior performance in all power tests of both CASF‐2013 and CASF‐2007 benchmarks compared to classical scoring functions. The ΔvinaRF20 scoring function and its code are freely available on the web at: https://www.nyu.edu/projects/yzhang/DeltaVina. © 2016 Wiley Periodicals, Inc.

Carvalho‐Silva, Valter H.; Aquilanti, Vincenzo; de Oliveira, Heibbe C. B.; Mundim, Kleber C.

doi: 10.1002/jcc.24529pmid: 27859380

A formulation is presented for the application of tools from quantum chemistry and transition‐state theory to phenomenologically cover cases where reaction rates deviate from Arrhenius law at low temperatures. A parameter d is introduced to describe the deviation for the systems from reaching the thermodynamic limit and is identified as the linearizing coefficient in the dependence of the inverse activation energy with inverse temperature. Its physical meaning is given and when deviation can be ascribed to quantum mechanical tunneling its value is calculated explicitly. Here, a new derivation is given of the previously established relationship of the parameter d with features of the barrier in the potential energy surface. The proposed variant of transition state theory permits comparison with experiments and tests against alternative formulations. Prescriptions are provided and implemented to three hydrogen transfer reactions: CH4 + OH → CH3 + H2O, CH3Cl + OH → CH2Cl + H2O and H2 + CN → H + HCN, widely investigated both experimentally and theoretically. © 2016 Wiley Periodicals, Inc.