Concurrent dual-resolution Monte Carlo simulation of liquid methane

We conduct molecular simulations of liquid methane in a system where molecular resolution fluctuates between atomically explicit and spherically symmetric united atoms. An appropriate dual-resolution canonical ensemble is constructed using (a) effective united atom pair potentials and (b) resolution-control potentials that confine explicit and united atoms chiefly to different slabs in the simulation domain. A Monte Carlo simulation is developed to sample this ensemble. We show that compatibility of the united-atom potentials with the explicit potentials in a concurrent simulation can be tuned by adjusting the width of the interface between the two resolution regions and by direct modification of the united-atom pair potentials. Our results lay the groundwork for treatment of larger atomically specific molecules with similar concurrent multiresolution techniques.     

Gold(I)-Catalyzed Cross-Coupling Reactions of Arenediazonium Salts with Alkynoic Acids

Russian Journal of Organic Chemistry - The reaction of simple alkynoate salts with isolated arenediazonium tetrafluoroborate salts that had been pre-conditioned with the gold(I) catalyst AuCl(Me2S)...     

Four novel spirooxazacamphorsultam derivatives

The chiral compounds (6aS,9S,10aR)‐11,11‐dimethyl‐5,5‐dioxo‐2,3,8,9‐tetrahydro‐6H‐6a,9‐methanooxazaolo[2,3‐i][2,1]benzisothiazol‐10(7H)‐one, C₁₂H₁₇NO₄S, (1), (7aS,10S,11aR)‐12,12‐dimethyl‐6,6‐dioxo‐3,4,9,10‐tetrahydro‐7H‐7a,10‐methano‐2H‐1,3‐oxazino[2,3‐i][2,1]benzisothiazol‐11(8H)‐one, C₁₃H₁₉NO₄S, (2), (6aS,9S,10R,10aR)‐11,11‐dimethyl‐5,5‐dioxo‐2,3,7,8,9,10‐hexahydro‐6H‐6a,9‐methanooxazolo[2,3‐i][2,1]benzisothiazol‐10‐ol, C₁₂H₁₉NO₄S, (3), and (7aS,10S,11R,11aR)‐12,12‐dimethyl‐6,6‐dioxo‐3,4,8,9,10,11‐hexahydro‐7H‐7a‐methano‐2H‐[1,3]oxazino[2,3‐i][2,1]benzisothiazol‐11‐ol, C₁₃H₂₁NO₄S, (4), consist of a camphor core with a five‐membered spirosultaoxazolidine or six‐membered spirosultaoxazine, as both their keto and hydroxy derivatives. In each structure, the molecules are linked via hydrogen bonding to the sulfonyl O atoms, forming chains in the unit‐cell b‐axis direction. The chains interconnect via weak C—H...O interactions. The keto compounds have very similar packing but represent the highest melting [507–508 K for (1)] and lowest melting [457–458 K for (2)] solids.     

Synthesis, structure and properties of metal nanoclusters

Metal nanoclusters have physical properties differing significantly from their bulk counterparts. Metallic properties such as delocalization of electrons in bulk metals which imbue them with high electrical and thermal conductivity, light reflectivity and mechanical ductility may be wholly or partially absent in metal nanoclusters, while new properties develop. We review modern synthetic methods used to form metal nanoclusters. The focus of this critical review is solution based chemical synthesis methods which produce fully dispersed clusters. Control of cluster size and surface chemistry using inverse micelles is emphasized. Two classes of metals are discussed, transition metals such as Au and Pt, and base metals such as Co, Fe and Ni. The optical and catalytic properties of the former are discussed and the magnetic properties of the latter are given as examples of unexpected new size-dependent properties of nanoclusters. We show how classical surface science methods of characterization augmented by chemical analysis methods such as liquid chromatography can be used to provide feedback for improvements in synthetic protocols. Characterization of metal clusters by their optical, catalytic, or magnetic behavior also provides insights leading to improvements in synthetic methods. The collective physical properties of closely interacting clusters are reviewed followed by speculation on future technical applications of clusters. (125 references).     

GALAHAD: 1. Pharmacophore identification by hypermolecular alignment of ligands in 3D

Alignment of multiple ligands based on shared pharmacophoric and pharmacosteric features is a long-recognized challenge in drug discovery and development. This is particularly true when the spatial overlap between structures is incomplete, in which case no good template molecule is likely to exist. Pair-wise rigid ligand alignment based on linear assignment (the LAMDA algorithm) has the potential to address this problem (Richmond et al. in J Mol Graph Model 23:199-209, 2004). Here we present the version of LAMDA embodied in the GALAHAD program, which carries out multi-way alignments by iterative construction of hypermolecules that retain the aggregate as well as the individual attributes of the ligands. We have also generalized the cost function from being purely atom-based to being one that operates on ionic, hydrogen bonding, hydrophobic and steric features. Finally, we have added the ability to generate useful partial-match 3D search queries from the hypermolecules obtained. By running frozen conformations through the GALAHAD program, one can utilize the extended version of LAMDA to generate pharmacophores and pharmacosteres that agree well with crystal structure alignments for a range of literature datasets, with minor adjustments of the default parameters generating even better models. Allowing for inclusion of partial match constraints in the queries yields pharmacophores that are consistently a superset of full-match pharmacophores identified in previous analyses, with the additional features representing points of potentially beneficial interaction with the target.     

Efficient and precise solvation free energies via alchemical adiabatic molecular dynamics

A new molecular dynamics method for calculating free energies associated with transformations of the thermodynamic state or chemical composition of a system (also known as alchemical transformations) is presented. The new method extends the adiabatic dynamics approach recently introduced by Rosso et al. [J. Chem. Phys. 116, 4389 (2002)] and is based on the use of an additional degree of freedom, lambda, that is used as a switching parameter between the potential energy functions that characterize the two states. In the new method, the coupling parameter lambda is introduced as a fictitious dynamical variable in the Hamiltonian, and a system of switching functions is employed that leads to a barrier in the lambda free energy profile between the relevant thermodynamic end points. The presence of such a barrier, therefore, enhances sampling in the end point (lambda = 0 and lambda = 1) regions which are most important for computing relevant free energy differences. In order to ensure efficient barrier crossing, a high temperature T(lambda) is assigned to lambda and a fictitious mass m(lambda) is introduced as a means of creating an adiabatic separation between lambda and the rest of the system. Under these conditions, it is shown that the lambda free energy profile can be directly computed from the adiabatic probability distribution function of lambda without any postprocessing or unbiasing of the output data. The new method is illustrated on two model problems and in the calculation of the solvation free energy of amino acid side-chain analogs in TIP3P water. Comparisons to previous work using thermodynamic integration and free energy perturbation show that the new lambda adiabatic free energy dynamics method results in very precise free energy calculations using significantly shorter trajectories.