Jian-Xin Guo

Whither Combine? New Opportunities for Receptor-Based QSAR

Receptor based QSAR methods represent a computational marriage of structure activity relationship analysis and receptor structure based design that is providing valuable pharmacological insight to a wide range of therapeutic targets. One implementation, called Comparative Binding Energy (COMBINE) analysis, is particularly powerful by virtue of its explicit consideration of interatomic interactions between the ligand and receptor as the QSAR variable space. This review outlines the methodological basis for the COMBINE model, contrasts it relative to other 3D QSAR techniques, and discusses sample applications that illustrate recent key innovations. One major development discussed is the rigorous integration of multiple receptors into unified COMBINE models for probing bioactivity trends as a function of amino acid variation across a series of homologous protein receptors, and as a function of conformational variation within one single protein. Other important examples include a recent extension of the method to account for covalent effects arising from ligand binding, as well as successful application of a COMBINE model to high throughput virtual screening. This review concludes with discussions about possible future methodological refinements and their applications, including potential extensions to four-dimensional QSAR, and a potential role of quantum chemistry in addressing covalent bonding effects and parametric adaptivity.

Acetylcholinesterase: Molecular Modeling with the Whole Toolkit

Molecular modeling efforts aimed at probing the structure, function and inhibition of the acetylcholinesterase enzyme have abounded in the last decade, largely because of the systems importance to medical conditions such as myasthenia gravis, Alzheimers disease and Parkinsons disease, and well as its famous toxicological susceptibility to nerve agents. The complexity inherent in such a system with multiple complementary binding sites, critical dynamic effects and intricate mechanisms for enzymatic function and covalent inhibition, has led to an impressively diverse selection of simulation techniques being applied to the system, including quantum chemical mechanistic studies, molecular docking prediction of noncovalent complexes and their associated binding free energies, molecular dynamics conformational analysis and transport kinetics prediction, and quantitative structure activity relationship modeling to tie salient details together into a coherent predictive tool. Effective drug and prophylaxis design strategies for a complex target like this requires some understanding and appreciation for all of the above methods, thus it makes an excellent case study for multi-tiered pharmaceutical modeling. This paper reviews a sample of the more important studies on acetylcholinesterase and helps to elucidate their interdependencies. Potential future directions are introduced based on the special methodological needs of the acetylcholinesterase system and on emerging trends in molecular modeling.

Monte Carlo simulations of CO2-expanded acetonitrile

The structure and phase-equilibrium properties of CO2-expanded acetonitrile (MeCN) were examined using Gibbs Ensemble Monte Carlo simulations. The results showed that the mole fraction of the CO2 in the binary system increased linearly with pressure and the predicted volume expansion of the liquid phase with pressure is nonlinear and in agreement with experiment. The site–site radial distribution functions (RDFs) were determined for this binary mixture, which show that the homomolecular CO2–CO2 and heteromolecular CO2–MeCN do not exhibit a significant dependence on CO2 mole fraction. The only major structural change that is seen to occur as the CO2 mole fraction is increased in the mixture is a decrease in the fraction of nearest neighbour MeCN molecules with parallel dipole orientations.