Enzyme model

Abstract: Platinum nanoparticles with a diameter of 2-3 nm were prepared and used in combination with single-wall carbon nanotubes (SWCNTs) for fabricating electrochemical sensors with remarkably improved sensitivity toward hydrogen peroxide. Nafion, a perfluorosulfonated polymer, was used to solubilize SWCNTs and also displayed strong interactions with Pt nanoparticles to form a network that connected Pt nanoparticles to the electrode surface. TEM and AFM micrographs illustrated the deposition of Pt nanoparticles on carbon nanotubes whereas cyclic voltammetry confirmed an electrical contact through SWCNTs between Pt nanoparticles and the glassy carbon (GC) or carbon fiber backing. With glucose oxidase (GOx) as an enzyme model, we constructed a GC or carbon fiber microelectrode-based biosensor that responds even more sensitively to glucose than the GC/GOx electrode modified by Pt nanoparticles or CNTs alone. The response time and detection limit (S/N = 3) of this biosensor was determined to be 3 s and 0.5 microM, respectively.

Abstract: The semiempirical tight-binding based quantum chemistry method GFN2-xTB is used in the framework of meta-dynamics (MTD) to globally explore chemical compound, conformer, and reaction space. The biasing potential given as a sum of Gaussian functions is expressed with the root-mean-square-deviation (RMSD) in Cartesian space as a metric for the collective variables. This choice makes the approach robust and generally applicable to three common problems (i.e., conformer search, chemical reaction space exploration in a virtual nanoreactor, and for guessing reaction paths). Because of the inherent locality of the atomic RMSD, functional group or fragment selective treatments are possible facilitating the investigation of catalytic processes where, for example, only the substrate is thermally activated. Due to the approximate character of the GFN2-xTB method, the resulting structure ensembles require further refinement with more sophisticated, for example, density functional or wave function theory methods. However, the approach is extremely efficient running routinely on common laptop computers in minutes to hours of computation time even for realistically sized molecules with a few hundred atoms. Furthermore, the underlying potential energy surface for molecules containing almost all elements ( Z = 1-86) is globally consistent including the covalent dissociation process and electronically complicated situations in, for example, transition metal systems. As examples, thermal decomposition, ethyne oligomerization, the oxidation of hydrocarbons (by oxygen and a P450 enzyme model), a Miller-Urey model system, a thermally forbidden dimerization, and a multistep intramolecular cyclization reaction are shown. For typical conformational search problems of organic drug molecules, the new MTD(RMSD) algorithm yields lower energy structures and more complete conformer ensembles at reduced computational effort compared with its already well performing predecessor.

Abstract: The origins, definitions, tools, and guiding principles of host-guest chemistry are developed. Perching, nesting, and capsular complexes are exemplified through molecular model and crystal structure comparisons. The degree of preorganization of a host for binding is a central determinant of its binding power. Complementarity of binding site placement in host and guest is a central determinant of structural recognition in complexation. Examples are given of chiral recognition in complexation, of partial transacylase mimics, of caviplexes, and of a synthetic molecular cell.

Abstract: Strategies for the prediction of in vivo drug clearance from in vitro drug metabolite kinetic data are well established for the rat. In this animal species, metabolism rate-substrate concentration relationships can commonly be described by the classic hyperbola consistent with the Michaelis-Menten model and simple scaling of the parameter intrinsic clearance (CL(int) - the ratio of V(max) to K(m)) is particularly valuable. The in vitro scaling of kinetic data from human tissue is more complex, particularly as many substrates for cytochrome P450 (CYP) 3A4, the dominant human CYP, show nonhyperbolic metabolism rate-substrate concentration curves. This review critically examines these types of data, which require the adoption of an enzyme model with multiple sites showing cooperative binding for the drug substrate, and considers the constraints this kinetic behavior places on the prediction of in vivo pharmacokinetic characteristics, such as metabolic stability and inhibitory drug interaction potential. The cases of autoactivation and autoinhibition are discussed; the former results in an initial lag in the rate-substrate concentration profile to generate a sigmoidal curve whereas the latter is characterized by a convex curve as V(max) is not maintained at high substrate concentrations. When positive cooperativity occurs, we suggest the use of CL(max), the maximal clearance resulting from autoactivation, as a substitute for CL(int). The impact of heteroactivation on this approach is also of importance. In the case of negative cooperativity, care in using the V(max)/K(m) approach to CL(int) determination must be taken. Examples of substrates displaying each type of kinetic behavior are discussed for various recombinant CYP enzymes, and possible artifactual sources of atypical rate-concentration curves are outlined. Finally, the consequences of ignoring atypical Michaelis-Menten kinetic relationships are examined, and the inconsistencies reported for both different substrates and sources of recombinant CYP3A noted.