Comparative study of various normal mode analysis techniques based on partial Hessians

Standard normal mode analysis becomes problematic for complex molecular systems, as a result of both the high computational cost and the excessive amount of information when the full Hessian matrix is used. Several partial Hessian methods have been proposed in the literature, yielding approximate normal modes. These methods aim at reducing the computational load and/or calculating only the relevant normal modes of interest in a specific application. Each method has its own (dis)advantages and application field but guidelines for the most suitable choice are lacking. We have investigated several partial Hessian methods, including the Partial Hessian Vibrational Analysis (PHVA), the Mobile Block Hessian (MBH), and the Vibrational Subsystem Analysis (VSA). In this article, we focus on the benefits and drawbacks of these methods, in terms of the reproduction of localized modes, collective modes, and the performance in partially optimized structures. We find that the PHVA is suitable for describing localized modes, that the MBH not only reproduces localized and global modes but also serves as an analysis tool of the spectrum, and that the VSA is mostly useful for the reproduction of the low frequency spectrum. These guidelines are illustrated with the reproduction of the localized amine‐stretch, the spectrum of quinine and a bis‐cinchona derivative, and the low frequency modes of the LAO binding protein. © 2009 Wiley Periodicals, Inc. J Comput Chem, 2010     

纳米脂质体放大血糖仪信号用于蓖麻毒素的即时检测

蓖麻毒素是已知的最致命的毒素之一,可作为一种生物武器并造成潜在的环境和食品污染.常用的蓖麻毒素检测方法存在耗时长、需要复杂且专业的实验室操作等缺点.为了克服该缺点,实现简单、快速、灵敏的蓖麻毒素非实验室检测,该文提出了一种利用负载有淀粉葡萄糖苷酶的纳米脂质体(ALN)放大血糖仪信号实现蓖麻毒素B 链(RTB)即时检测的...