Computational Methods for Selective Catalysis

选择性催化的计算方法

• 批准号: 9277122
• 负责人: Marisa C Kozlowski
• 金额: $ 8.47万
• 依托单位: UNIVERSITY OF PENNSYLVANIA
• 依托单位国家: 美国
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-09-30 至 2019-12-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9277122
• 关键词: Achievement; Attention; Biological Process; Catalysis; Chemicals; Collaborations; Complex; Computing Methodologies; Data Set; Development; Doctor of Philosophy; Elements; Enzymes; Foundations; Funding; Generations; Goals; Grant; Health; Human Resources; Imagery; Indium; Investigation; Knowledge; Measures; Metals; Methods; Modeling; Molecular; Organic Synthesis; Pharmacologic Substance; Postdoctoral Fellow; Prevalence; Process; Reaction; Reagent; Research; Research Personnel; Research Project Grants; Societies; Structure; Students; System; Systems Analysis; Training; United States National Institutes of Health; Work; analytical tool; biological systems; catalyst; computerized tools; design; drug development; electronic structure; graduate student; improved; inhibitor/antagonist; innovation; programs; sensor; targeted agent; tool; undergraduate student

 DESCRIPTION (provided by applicant): The overall objective of this research program is to develop and apply state-of-the-art computation methods to understand stereoselectivity, chemoselectivity, and reactivity at the molecular level with the aim of designing new, more effective reagents and catalysts. The control of selectivity and reactivity are essential features f efficient synthesis, yet our molecular level understanding of how fundamental interactions perturb these aspects is only rudimentary. This program seeks to quantitate these fundamental interactions to explain the observed results and to build on this foundation. In addition to developing improved computational and analytical tools, a primer will be constructed tabulating the prevalence and strength of these widespread, fundamental interactions. We have identified three overall goals. In the first, transition state calculations will be used to probe mechanism, understand control elements, and quantitate fundamental interactions. In the second, empirical modeling tools will be developed and used to identify the key control factors governing reactivity and selectivity. This knowledge, in turn, focuses the studies in aim 1 to the most important elements. In the third, a new experimental measure of reactivity is outlined, which is an important component of the interaction primer that is being built. Relevance The fundamental hallmark of this proposal is the ability to design new reactions and catalysts via computation to construct important organic structures in an efficient and rational manner. New synthetic methods greatly increase access to untapped chemical space, leading to materials and pharmaceuticals that benefit society. To achieve this goal, investigations will focus on obtaining an improved understanding of the fundamental interactions governing reactivity and selectivity. These same interactions govern biological systems, and further understanding will enable the design of enzymatic inhibitors and agents targeting other biomolecules to disrupt biological functions. Invaluable training will be afforded to undergraduate students, graduate students, and postdoctoral researchers involved in this proposal.

 描述（由申请人提供）：该研究项目的总体目标是开发和应用最先进的计算方法来理解分子水平的立体选择性、化学选择性和反应性，目的是设计新的、更有效的试剂选择性和反应性的控制是有效合成的基本特征，但我们对基本相互作用如何扰乱这些方面的分子水平理解还只是初步的。观察到的结果并在此基础上，除了开发改进的计算和分析工具外，我们还将构建一个初级读物，列出这些广泛的基本相互作用的普遍性和强度。计算将用于探索机制、理解控制元素并定量基本相互作用。其次，将开发经验建模工具并用于确定控制反应性和选择性的关键控制因素。目标 1 是最重要的要素。第三，概述了一种新的反应性实验测量方法，它是正在构建的相互作用引物的重要组成部分。 相关性 该提案的基本特点是能够通过计算设计新的反应和催化剂，以构建重要的有机结构。新的合成方法大大增加了对未开发的化学空间的利用，从而产生造福社会的材料和药物。为了实现这一目标，研究的重点是更好地了解控制反应性和选择性的基本相互作用。控制生物系统，并进一步了解将为参与该提案的本科生、研究生和博士后研究人员提供宝贵的培训。