Physical organic chemistry on the brain

The challenges to obtaining chemical-scale information on the molecules of neuroscience are considerable. Most targets are complex integral membrane proteins that are not amenable to direct structural characterization. However, by combining the tools of organic synthesis, molecular biology, and electrophysiology, rational and systematic structure-function studies can be performed in what we have termed physical organic chemistry on the brain. Using these tools, we have probed hydrophobic effects, hydrogen bonding, cation-pi interactions, and conformational changes associated with channel gating. The insights gained provide important guidance for drug discovery efforts targeting ion channels and neuroreceptors and mechanistic insights for the complex proteins of neuroscience.     

有机微波化学研究进展

本文综述了近几年来微波技术在有机合成方面的研究和应用进展。初步探讨了微波催化有机反应的作用机理, 并展望了有机微波化学的发展前景。     

Diagnostics in computational organic chemistry

Focusing on computational studies of pericyclic reactions from the late twentieth century into the twenty-first century, this paper argues that computational diagnostics is a key methodological development that characterize the management and coordination of plural approximation methods in computational organic chemistry. Predictive divergence between semi-empirical and ab initio approximation methods in the study of pericyclic reactions has issued in epistemic dissent. This has resulted in the use of diagnostics to unpack computational greyboxes in order to critically assess the effect of specific misrepresentations on predictive accuracy given that approximations and idealizations must be made to render computational models tractable. Furthermore, benchmarking is used to determine the applicability of approximation methods depending on how accurate the results need to be in a given research context. The epistemology of benchmarking consists of the co-generation of data sets in a hybrid computational–experimental form used to standardize computational methods but does not determine a unique quantitative method to be used across computational organic chemistry.