Hydration Free Energies in the FreeSolv Database Calculated with Polarized Iterative Hirshfeld Charges.

Computer simulations of biomolecular systems often use force fields, which are combinations of simple empirical atom-based functions to describe the molecular interactions. Even though polarizable force fields give a more detailed description of intermolecular interactions, nonpolarizable force fields, developed several decades ago, are often still preferred because of their reduced computation cost. Electrostatic interactions play a major role in biomolecular systems and are therein described by atomic point charges. In this work, we address the performance of different atomic charges to reproduce experimental hydration free energies in the FreeSolv database in combination with the GAFF force field. Atomic charges were calculated by two atoms-in-molecules approaches, Hirshfeld-I and Minimal Basis Iterative Stockholder (MBIS). To account for polarization effects, the charges were derived from the solute's electron density computed with an implicit solvent model, and the energy required to polarize the solute was added to the free energy cycle. The calculated hydration free energies were analyzed with an error model, revealing systematic errors associated with specific functional groups or chemical elements. The best agreement with the experimental data is observed for the AM1-BCC and the MBIS atomic charge methods. The latter includes the solvent polarization and presents a root-mean-square error of 2.0 kcal mol-1 for the 613 organic molecules studied. The largest deviation was observed for phosphorus-containing molecules and the molecules with amide, ester and amine functional groups.

In silico model of an antenna of a phycobilisome and energy transfer rates determination by theoretical Förster approach.

Energy transfer (ET) in phycobilisomes, a macrocomplex of phycobiliproteins and linker proteins, is a process that is difficult to understand completely. A model for a rod composed of two hexamers of Phycocyanin and two hexamers of Phycoerythrin was built using an in silico approach and the three-dimensional structures of both phycobiliproteins from Gracilaria chilensis. The model was characterized and showed 125 Å wide and 230 Å high, which agree with the dimensions of a piling of four hexamers as observed in the images of subcomplexes of phycobilisomes obtained by transmission electron microscopy. ET rates between every pair of chromophores in the model were calculated using the Förster approach, and the fastest rates were selected to draw preferential ET pathways along the rod. Every path indicates that the ET is funneled toward the chromophores located at Cysteines 82 in Phycoerythrin and 84 in Phycocyanin. The chromophores that face the exterior of the rod are phycoerythrobilins, and they also show a preferential ET toward the chromophores located at the center of the rod. The values calculated, in general, agree with the experimental data reported previously, which validates the use of this experimental approach.

Generalized topological indices. Modeling gas-phase rate coefficients of atmospheric relevance.

We develop the idea that the use of ad hoc molecular descriptors in QSAR/QSPR studies is not an optimal solution. Instead, we propose to optimize these descriptors for the specific properties under study. In the case of topological indices (TIs) we propose the use of the generalized topological indices (GTIs), which account for several of the classical TIs in one single graph invariant. GTIs represent points in a six-dimensional space of topological parameters, which can be optimized for describing a specific property. The situation shows some resemblance with the geometry optimization procedures used to minimize molecular energy. Here we study the reaction rate coefficients for the gas-phase radical reactions between alkanes and cycloalkanes with OH, Cl, and NO3 radicals. These reaction rate coefficients were studied recently by using some "classical" TIs, such as Balaban and Randic indices. Despite the fact that the Randic index produces acceptable QSPR models for some of these reactions, the models developed are still far from being optimal. Using the GTI approach we have improved these QSPRs by reducing the standard deviation by almost 50%. In addition, the current approach permits the illustration of the similarities and differences among the different descriptors studied, indicating possible directions for searching new optimal molecular descriptors.

A semiempirical approach to the intra-phycocyanin and inter-phycocyanin fluorescence resonance energy-transfer pathways in phycobilisomes.

A semiempirical methodology to model the intra-phycocyanin and inter-phycocyanin fluorescence resonance energy-transfer (FRET) pathways in the rods of the phycobilisomes (PBSs) from Fremyella diplosiphon is presented. Using the Förster formulation of FRET and combining experimental data and PM3 calculation of the dipole moments of the aromatic portions of the chromophores, transfer constants between pairs of chromophores in the phycocyanin (PC) structure were obtained. Protein docking of two PC hexamers was used to predict the optimal distance and axial rotation angle for the staked PCs in the PBSs' rods. Using the distance obtained by the docking process, transfer constants between pairs of chromophores belonging to different PC hexamers were calculated as a function of the angle of rotation. We show that six preferential FRET pathways within the PC hexameric ring and 15 pathways between hexamers exist, with transfer constants consistent with experimental results. Protein docking predicted the quaternary structure for PCs in rods with inter-phycocyanin distance of 55.6 A and rotation angle of 20.5 degrees . The inter-phycocyanin FRET constant between chromophores at positions beta(155) is maximized at the rotation angle predicted by docking revealing the crucial role of this specific inter-phycocyanin channel in defining the complete set of FRET pathways in the system.

Simplex optimization of generalized topological index (GTI-simplex): a unified approach to optimize QSPR models.

GTI-simplex is a new methodology that combines the generalized topological indices and the down hill simplex optimization procedure to search for optimized quantitative structure-property relationship models (Chem. Phys. Lett. 2005, 410, 343). In this study, the fundamental role of the graph topological distance inducing a local shell structure on vertexes and a detailed derivation of the GTI-decomposition in terms of the so-called "geodesic-brackets", i.e., functions that mix the local shell structure for different vertexes are presented. Applications of the GTI-simplex to a set of physicochemical properties covering those depending on intramolecular and/or intermolecular interactions are included. GTI-simplex has showed to be a very effective methodology for the description of different properties from a unified point of view. No ad hoc definition for topological index is required to each property as in the traditional use of topological indices or other molecular descriptors to QSAR/QSPR studies.

On the aggregation state and QSPR models. The solubility of herbicides as a case study.

The goal of this article is to stress the importance of considering the phase in QSPR studies. It is found that the phase plays a fundamental role in the QSPR models from both a statistical and a physical point of view. From a statistical point of view, it is observed that the predictive performance drops drastically when the QSPR model, obtained for a given phase, is used to predict the solubility of the same set of compounds but in another phase. From a physical point of view, when the compounds in the training set are in different phases, the physical interpretation of the descriptors involved in the model is obscured because the descriptors which appear in the correlation equation are a sort of average encoding the different physical mechanisms underlying the property. It is shown that the use of compounds in the same phase, instead, allows a more transparent physical interpretation of the descriptors involved in the model and, at the same time, improves the statistics of the models.