Background: Throughout evolution, mutations in particular regions of some protein structures have resulted in extra covalent bonds that increase the overall robustness of the fold: disulfide bonds. The two strategically placed cysteines can also have a more direct role in protein function, either by assisting thiol or disulfide exchange, or through allosteric effects. In this work, we verified how the structural similarities between disulfides can reflect functional and evolutionary relationships between different proteins. We analyzed the conformational patterns of the disulfide bonds in a set of disulfide-rich proteins that included twelve SCOP superfamilies: thioredoxin-like and eleven superfamilies containing small disulfide-rich proteins (SDP). Results: The twenty conformations considered in the present study were characterized by both structural and energetic parameters. The corresponding frequencies present diverse patterns for the different superfamilies. The least-strained conformations are more abundant for the SDP superfamilies, while the "catalytic" +/-RHook is dominant for the thioredoxin-like superfamily. The "allosteric" -RHSaple is moderately abundant for BBI, Crisp and Thioredoxin-like superfamilies and less frequent for the remaining superfamilies. Using a hierarchical clustering analysis we found that the twelve superfamilies were grouped in biologically significant clusters. Conclusions: In this work, we carried out an extensive statistical analysis of the conformational motifs for the disulfide bonds present in a set of disulfide-rich proteins. We show that the conformational patterns observed in disulfide bonds are sufficient to group proteins that share both functional and structural patterns and can therefore be used as a criterion for protein classification.

Substantial improvements in the molecular level understanding of fluid interfaces have recently been achieved by recognizing the importance of detecting the intrinsic surface of the coexisting condensed phases in computer simulations (i.e., after the removal of corrugations caused by capillary waves) and by developing several methods for identifying the molecules that are indeed located at the boundary of the two phases. In our previous paper [J. Phys. Chem. C 2010, 114, 11169], we critically compared those methods in terms of reliability, robustness, and computation speed. Once the intrinsic surface of a given phase is detected, various profiles, such as the density profiles of the components, can be calculated relative to this intrinsic surface rather than to the macroscopically planar Gibbs dividing surface. As a continuation of our previous study, here we present a detailed and critical comparison of various methods that can be used to calculate intrinsic density profiles once the full set of truly interfacial molecules has been identified. Two of the methods, the Fourier function and the Voronoi tessellation, are already described in the literature; two other methods, the covering surface and the triangular interpolation, are newly proposed algorithms; one method, the modified grid-based intrinsic profile (GIP) method, is an improvement over an existing procedure. The different methods are again compared in terms of accuracy and computational cost. On the basis of this comparison, we propose a fast and accurate protocol to be routinely used for intrinsic surface analyses in computer simulations.

Periodic density functional theory (DFT) calculations have been used to unravel the existence of Bronsted-Evans-Polanyi (BEP) relationships for water dissociation on metallic surfaces which constitutes the rate determining step for the technologically important water gas shift reaction In addition it is predicted that nickel surfaces possessing low coordinated atoms could be effective for catalyzing water dissociation Finally it is shown that the adsorption energy of atomic oxygen on a given metallic surface provides an excellent descriptor of the activation energy for water dissociation on that surface thus allowing the screening of large number of metallic and bimetallic systems in a simple way

Cancer is the leading cause of death among men and women under age 85. Every year, millions of individuals are diagnosed with cancer. But finding new drugs is a complex, expensive, and very time-consuming task. Over the past decade, the cancer research community has begun to address the in silico modeling approaches, such as Quantitative Structure-Activity Relationships (QSAR), as an important alternative tool for targeting potential anticancer drugs. With the compilation of a large dataset of nucleosides synthesized in our laboratories, or elsewhere, and tested in a single cytotoxic assay under the same experimental conditions, we recognized a unique opportunity to attempt to build predictive QSAR models. Early efforts with 2D classification models built from part of this dataset were very encouraging. Here we report a further detailed evaluation of classification models to flag potential anticancer activities derived from a variety of 3D molecular representations. A quantitative 3D-model model that discriminates anticancer compounds from the inactive ones was attained, which allowed the correct classification of 82% of compounds in such a large and diverse dataset, with only 5% of false inactives and 11% of false actives. The model developed here was then used to select and design a new series of nucleosides, by classifying beforehand them as active/inactive anticancer compounds. From the compounds so designed, 22 were synthesized and evaluated for their inhibitory effects on the proliferation of murine leukemia cells (L1210/0), of which 86% were well-classified as active or inactive, and only two were false actives, corroborating the good predictive ability of the present discriminant model. The results of this study thus provide a valuable tool for the design of novel potent anticancer nucleoside analogues.

The NO oxidation either with atomic or molecular oxygen on the stepped Au(3 2 1) surface was studied by means of OFT calculations (GGA/PW91). A periodic supercell approach was used to model the gold stepped surface and the kinetic profiles of the reactions were determined with the dimer approach. It was found that the co-adsorption of NO and O occurs preferentially with these species interacting with top and hollow sites nearby the steps, respectively. In the case of co-adsorbed NO and O(2) species, the most stable configuration on the surface is a ONOO* intermediate. The NO(2) product adsorbs strongly on the Au(3 2 1) surface (E(ads) = -1.10 eV) also nearby the step. The reaction of NO oxidation by atomic oxygen has an energy cost of 0.07 eV, whereas moderate-low energy barriers of 0.21 and 0.25 eV were computed for the reaction with molecular oxygen, via the ONOO* intermediate, following Elay-Rideal (ER) or Langmuir-Hinshelwood (LH) mechanisms, respectively. The reaction route following the ER mechanism is energetically more favorable since it is unnecessary to overcome the very high barriers (similar to 1 eV) needed for NO(2) desorption and for dissociation of molecular oxygen in the cases of NO reaction via LH mechanism and NO oxidation with atomic oxygen, respectively.

Mayer's energy decomposition method was applied inthe study of the relative stability of cis and trans isomers of 1,2-disubstituted ethylenes, XHC=CHX (X = F, Cl, Br) and 2-butene. The trans to cis isomerization energy for each system was determined at the Hartree-Fock level, with several basis sets, and then divided into monoatomic and diatomic energy contributions. The results point to a different energy distribution for the dihaloethylenes, known for exhibiting a cis isomer that is more stable than the trans one, a behavior that is known as the cis effect, when compared to 2-butene. The main stabilizing effects of the cis isomer in the dihaloethylenes, at this level of theory, are energy terms associated with the interaction of the X substituents with the C atoms.