A HIGH PERFORMANCE STRUCTURE ELUCIDATION SYSTEM

描述：（申请人的描述）通过以下方式阐明结构： 传统的方法可能是耗时的，特别是对于复杂的高度复杂的情况。 衍生自天然来源的官能化化合物。计算机提供 大幅度提高生产力的机会。SESAMI是第一个 代，旨在直接减少集体的综合方案 未知的光谱特性，优选单个分子结构， 但不超过少数结构，这在本质上是详尽的 (I.e.,不存在其它同样兼容的结构）。资源增值 都能实现在后一种情况下，替代结构的集合 是化学家的起点，任务很容易完成，因为 有经验的化学家精通从化学物质中识别正确的结构。 在为数不多的选择中。虽然天然化合物 通常达到1000道尔顿或更高的分子量，SESAMI的成功 主要限于500道尔顿以下的化合物。该项目的目标是 第二代程序能够例行阐明的结构 分子量高达1000道尔顿的化合物。由于计算 结构解析的要求随着 分子量，需要重大改进： 频谱解释程序的输出的信息内容，以及 结构生成效率的显著提高。采用私下 和公共资助的研究和开发实验室，需要 以计算机为基础的工具，以提高生产力的说明， 有机化合物的广谱结构从未如此之大， 特别是在药物发现中， 来源越来越感兴趣。

DESCRIPTION: (Applicant's description) The elucidation of structure by conventional means can be time-consuming, especially with the complex highly functionalized compounds derived from natural sources. The computer offers opportunities for substantially greater productivity. SESAMI is a first generation, comprehensive program designed to directly reduce the collective spectral properties of an unknown, preferably to a single molecular structure, but to not more than a small number of structures which is exhaustive in nature (I.e., there is no other equally compatible structure). Enhanced productivity is achieved either way. In the latter case, the set of alternative structures is the starting point for the chemist and the assignment is readily make, since experienced chemists are proficient at identifying a correct structure from among a small number of alternatives. Although naturally occurring compounds commonly reach molecular weights of 1000 daltons or more, SESAMI's success has been largely limited to compounds up to 500 daltons. The project goal is a second generation program capable of routinely elucidating the structure of compounds with molecular weights up to 1000 daltons. Since the computational requirements of structure elucidation increase geometrically with increasing molecular weight, major improvements are required: substantial increases in the information content of the output of the spectrum interpretation programs, and significant increases in the efficiency of structure generation. In privately and publicly funded research and development laboratories, the need for computer-based tools to augment productivity in the elucidation of the structure of a broad spectrum of organic compounds has never been greater, particularly in drug discovery where complex compounds isolated form natural sources are of increasing interest.