A method using a finite, first-order Markov chain is presented to estimate rate constants for zeolite formation from experimental nuclear magnetic resonance (NMR) data on the abundance of different silica oligomers. An experimental design is suggested by which this method can be implemented. The method uses weighted least squares to estimate transition probabilities from aggregate NMR data. Rate constants, equilibrium constants, and free energies of elementary zeolite-forming reactions can be estimated. Hypothetical zeolite-forming reactions can also be modeled. An example of modeling, using hypothetical data, shows how zeolite formation can result from reactions involving mainly silica cyclic tetramers.

The rapid onset and offset of rapacuronium can be explained from its pharmacokinetic and pharmacodynamic characteristics. A unique property of rapacuronium is its high value for ke0, indicating a rapid access to the receptor site. The reason for this high ke0 may be related to the low intrinsic potency of rapacuronium, but this is not yet fully clarified.

A simple method is presented for the determination of individual rate constants for substrate hydrolysis by serine proteases and other enzymes with similar catalytic mechanism. The method does not require solvent perturbation like viscosity changes, or solvent isotope effects, that often compromise nonspecifically the activity of substrate and enzyme. The rates of substrate diffusion into the active site (k1), substrate dissociation (k−1), acylation (k2), and deacylation (k3) in the accepted mechanism of substrate hydrolysis by serine proteases are derived from the temperature dependence of the Michaelis–Menten parameters kcat/Km and kcat. The method also yields the activation energies for these molecular events. Application to wild-type and mutant thrombins reveals how the various steps of the catalytic mechanism are affected by Na+ binding and site-directed mutations of the important residues Y225 in the Na+ binding environment and L99 in the S2 specificity site. Extension of this method to other proteases should enable the derivation of detailed information on the kinetic and energetic determinants of protease function.