Approximate Simulation Techniques and Distribution of an Extended Gamma Process

In reliability theory, many papers use a standard Gamma process to model the evolution of the cumulative deterioration of a system over time. When the variance-to-mean ratio of the system deterioration level varies over time, the standard Gamma process is not convenient any more because it provides a constant ratio. A way to overcome this restriction is to consider the extended version of a Gamma process proposed by Cinlar (J Appl Probab 17:467–480, 1980). However, based on its technicality, the use of such a process for applicative purpose requires the preliminary development of technical tools for simulating its paths and for the numerical assessment of its distribution. This paper is devoted to these two points.     

Docking-based comparative intermolecular contacts analysis as new 3-D QSAR concept for validating docking studies and in silico screening: NMT and GP inhibitors as case studies

The significant role played by docking algorithms in drug discovery combined with their serious pitfalls prompted us to envisage a novel concept for validating docking solutions, namely, docking-based comparative intermolecular contacts analysis (dbCICA). This novel approach is based on the number and quality of contacts between docked ligands and amino acid residues within the binding pocket. It assesses a particular docking configuration on the basis of its ability to align a set of ligands within a corresponding binding pocket in such a way that potent ligands come into contact with binding site spots distinct from those approached by low-affinity ligands and vice versa. In other words, dbCICA evaluates the consistency of docking by assessing the correlation between ligands' affinities and their contacts with binding site spots. Optimal dbCICA models can be translated into valid pharmacophore models that can be used as 3-D search queries to mine structural databases for new bioactive compounds. dbCICA was implemented to search for new inhibitors of candida N-myristoyl transferase as potential antifungal agents and glycogen phosphorylase (GP) inhibitors as potential antidiabetic agents. The process culminated in five selective micromolar antifungal leads and nine GP inhibitory leads.     

Scaling behavior of quantum nanosystems: emergence of quasi-particles, collective modes, and mixed exchange symmetry states

Examples of quantum nanosystems are graphene nanoribbons, molecular wires, and superconducting nanoparticles. The objective of the multiscale theory presented here is to provide a new perspective on the coupling of processes across scales in space and time underlying the dynamics of these systems. The long range objective for this multiscale approach is to serve as an efficient computational algorithm. Long space-time dynamics is derived using a perturbation expansion in the ratio ? of the nearest-neighbor distance to a nanometer-scale characteristic length and a theorem on the equivalence of long time-averages and expectation values. This dynamics is shown to satisfy a coarse-grained wave equation (CGWE) which takes a Schro?dinger-like form with modified masses and interactions. The scaling of space and time is determined by the orders of magnitude of various contributions to the N-body potential. If the spatial scale of the coarse-graining is too large, the CGWE would imply an unbounded growth of gradients; if it is too short, the system's size would display uncontrolled growth inappropriate for the bound states of interest, i.e., collective motion or migration within a stable nanoassembly. The balance of these two extremes removes arbitrariness in the choice of the scaling of space-time. Since the long-scale dynamics of each Fermion involves its interaction with many others, we hypothesize that the solutions of the CGWE have mean-field character to good approximation, i.e., can be factorized into single-particle functions. This leads to a coarse-grained mean-field approximation that is distinct in character from traditional Hartree-Fock theory. A variational principle is used to derive equations for the single-particle functions. This theme is developed and used to derive an equation for low-lying disturbances from the ground state corresponding to long wavelength density disturbances or long-scale migration. An algorithm for the efficient simulation of quantum nanosystems is suggested.     

Fucoidan and Alginate from the Brown Algae Colpomenia sinuosa and Their Combination with Vitamin C Trigger Apoptosis in Colon Cancer

Brown seaweeds are producers of bioactive molecules which are known to inhibit oncogenic growth. Here, we investigated the antioxidant, cytotoxic, and apoptotic effects of two polysaccharides from the brown algae Colpomenia sinuosa, namely fucoidan and alginate, in a panel of cancer cell lines and evaluated their effects when combined with vitamin C. Fucoidan and alginate were isolated from brown algae and characterized by HPLC, FTIR, and NMR spectroscopy. The results indicated that highly sulfated fucoidans had higher antioxidant and cytotoxic effects than alginate. Human colon cancer cells were the most sensitive to the algal treatments, with fucoidan having an IC₅₀ value (618.9 µg/mL⁻¹) lower than that of alginate (690 µg/mL⁻¹). The production of reactive oxygen species was increased upon treatment of HCT-116 cells with fucoidan and alginate, which suggest that these compounds may trigger cell death via oxidative damage. The combination of fucoidan with vitamin C showed enhanced effects compared to treatment with fucoidan alone, as evidenced by the significant inhibitory effects on HCT-116 colon cancer cell viability. The combination of the algal polysaccharides with vitamin C caused enhanced degeneration in the nuclei of cells, as evidenced by DAPI staining and increased the subG1 population, suggesting the induction of cell death. Together, these results suggest that fucoidan and alginate from the brown algae C. sinuosa are promising anticancer compounds, particularly when used in combination with vitamin C.     

Could an anisotropic molecular mechanics/dynamics potential account for sigma hole effects in the complexes of halogenated compounds?

Halogenated compounds are gaining an increasing importance in medicinal chemistry and materials science. Ab initio quantum chemistry (QC) has unraveled the existence of a “sigma hole” along the C? X (X = F, Cl, Br, I) bond, namely, a depletion of electronic density prolonging the bond, concomitant with a build‐up on its sides, both of which are enhanced along the F < Cl < Br < I series. We have evaluated whether these features were intrinsically built‐in in an anisotropic, polarizable molecular mechanics (APMM) procedure such as SIBFA (sum of interactions between fragments ab initio computed). For that purpose, we have computed the interaction energies of fluoro‐, chloro‐, and bromobenzene with two probes: a divalent cation, Mg(II), and water approaching X through either one H or its O atom. This was done by parallel QC energy‐decomposition analyses (EDA) and SIBFA computations. With both probes, the leading QC contribution responsible for the existence of the sigma hole is the Coulomb contribution E_c. For all three halogenated compounds, and with both probes, the in‐ and out‐of‐plane angular features of E_c were closely mirrored by the SIBFA electrostatic multipolar contribution (E_MTP). Resorting to such a contribution thus dispenses with empirically‐fitted “extra”, off‐centered partial atomic charges as in classical molecular mechanics/dynamics. © 2013 Wiley Periodicals, Inc.     

Could the “Janus‐like” properties of the halobenzene CX bond (XCl,Br) be leveraged to enhance molecular recognition?

The CX bond in halobenzenes (X?Cl, Br) exhibits a dual character, being electron‐deficient along the CX direction, and electron‐rich on its flanks. We sought to amplify both features by resorting to electron‐withdrawing and electron‐donating substituents, respectively. This was done by quantum chemistry (QC) computations in the recognition sites of three protein targets: farnesyl transferase, coagulation factor Xa, and the HIV‐1 integrase. In this context, some substituents, notably fluorine, CF₃, and NHCH₃, afforded significant overall gains in the binding energies as compared to the parent halobenzene, in the 2–5 kcal/mol range. In fact, we found that some di‐ and up to tetra‐substitutions enabled even larger gains than those they contribute separately owing to many‐body effects. Moreover, desolvation was also found to be a key contributor to the energy balances. As a consequence, some particular substituents, contributing to reduce the halobenzene dipole moment, accordingly reduced solvation: this factor acted in synergy with their enhancement of the intermolecular interaction energies along and around the CX bond. We could thus leverage the “Janus‐like” properties of such a bond and the fact that it can be tuned and possibly amplified by well‐chosen substituents. We propose a simple yet rigorous computational strategy resorting to QC to prescreen novel substituted halobenzenes. The QC results on the recognition sites then set benchmarks to validate polarizable molecular mechanics/dynamics approaches used to handle the entirety of the inhibitor‐protein complex. © 2014 Wiley Periodicals, Inc.     

Subdiffusive axial transport of granular materials in a long drum mixer

Granular mixtures segregate radially by size when tumbled in a partially filled horizontal drum. The smaller component moves toward the axis of rotation and forms a buried core, which then splits into axial bands. Models have generally assumed that the axial segregation is opposed by diffusion. Using narrow pulses of the smaller component as initial conditions, we have characterized axial transport in the core. We find that the axial advance of the segregated core is well described by a self-similar concentration profile whose width scales as talpha, with alpha approximately 0.3<1/2. Thus, the process is subdiffusive rather than diffusive as previously assumed. We compare our results to two one-dimensional model equations which contain self-similarity and subdiffusion: a linear fractional diffusion model and the nonlinear porous medium equation.