Statistical Mechanics with Quantum Potentials: Application to Host-Gues

具有量子势的统计力学：在主人-客人中的应用

• 批准号: 9040209
• 负责人: Simon Webb
• 金额: $ 73.47万
• 依托单位: VERACHEM, LLC
• 依托单位国家: 美国
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2018-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9040209
• 关键词: Accounting; Affect; Affinity; Algorithms; Applied Research; Area; Basic Science; Behavior; Binding; Binding Sites; Blinded; Cereals; Chemical Warfare Agents; Chemicals; Code; Computer software; Computing Methodologies; Coupled; Cyclodextrins; Data; Dissociation; Entropy; Excision; Flurbiprofen; Free Energy; Geometry; Goals; Health; Human; Hybrids; Investigation; Kinetics; Libraries; Link; Mechanics; Methodology; Methods; Molecular; Molecular Conformation; Movement; Pharmaceutical Preparations; Pharmacologic Substance; Phase; Potential Energy; Procedures; Process; Property; Quantum Mechanics; Research Personnel; Running; Scheme; Science; Scientist; Services; Small Business Innovation Research Grant; Software Tools; Speed; Statistical Mechanics; Technology; Testing; Thermodynamics; Time; Translating; base; blind; computerized tools; conformer; design; drug candidate; drug discovery; environmental chemical; improved; molecular mechanics; parallel processing; physical property; pollutant; quantum; quantum chemistry; research and development; research study; small molecule; tool

DESCRIPTION (provided by applicant): Host molecules, such as cyclodextrins and cucurbiturils, can 'capture' smaller molecules and affect their physical and chemical behavior. The stronger the host molecule holds onto, i.e. binds, its smaller 'guest' the larger the effect ca be. Host molecules themselves can also be chemically altered (i.e. derivatized), which can change how strongly they bind guest molecules, as well as their own physical properties. Scientists are discovering many human health-related applications for host-guest technology, including improvement of the properties of drugs to make them more effective and safer, potential scavengers for chemical warfare agent removal, and clean-up of environmental chemical pollutants. The amount of basic research as well as applied/industrial R&D in this area is expanding rapidly. Given a particular 'guest' molecule (e.g. drug candidate, chemical pollutant) key pieces of information R&D scientists require is the host-guest binding affinity and the association/dissociation rates. This SBIR project aims to develop a software tool that can accurately predict these host-guest binding properties (e.g. binding free energy). This would allow R&D scientists to carry out computational experiments reducing the number of expensive and time-consuming bench experiments required. There is a current need for such a software tool to be developed, because as recently demonstrated by a blinded test challenge, existing tools are not accurate enough to provide useful information to researchers. Very recent studies indicate that the accuracy of the predictions can be significantly improved by combining quantum mechanical (QM) energy functions with rigorous statistical mechanics. However, these proof-of-concept studies have yet to be translated into a robust computational tool suitable for applied R&D. Therefore, this project will interface VeraChem's current statistical mechanics software package (VM2) with the widely used quantum chemistry package GAMESS, and implement drivers for various computational schemes to achieve this goal. In this proposed hybrid methodology, a Boltzmann distribution of molecular conformations will still be generated via a thorough conformational search as it is for classical VM2; however, the conformational search will not solely rely on molecular mechanics but will be guided by the more reliable QM potential. QM potentials will also be used for entropy terms, including a treatment of anharmonic effects. Full advantage will be taken of recent dramatic improvements in reliability of semi-empirical QM (SEQM), with optional corrections at higher levels of QM. Turnaround of calculations will be speeded up by parallel processing and a sophisticated conformer filter/vetting process.

描述（由申请人提供）：主体分子，例如环糊精和葫芦脲，可以“捕获”较小的分子并影响其物理和化学行为。主体分子对其较小的“客体”的附着力（即结合力）越强，效果就越大。主体分子本身也可以进行化学改变（即衍生化），这可以改变它们与客体分子结合的强度以及它们自身的物理性质。科学家们正在发现主客体技术的许多与人类健康相关的应用，包括改进药物的特性，使其更有效、更安全、去除化学战剂的潜在清除剂以及清理环境化学污染物。该领域的基础研究以及应用/产业研发数量正在迅速扩大。给定一个特定的“客体”分子（例如候选药物、化学污染物），研发科学家需要的关键信息是主客体结合亲和力和缔合/解离率。该 SBIR 项目旨在开发一种软​​件工具，可以准确预测这些主客体结合特性（例如结合自由能）。这将使研发科学家能够进行计算实验，从而减少所需的昂贵且耗时的台架实验的数量。当前需要开发这样的软件工具，因为正如最近的盲测挑战所证明的那样，现有工具不够准确，无法为研究人员提供有用的信息。最近的研究表明，通过将量子力学（QM）能量函数与严格的统计力学相结合，可以显着提高预测的准确性。然而，这些概念验证研究尚未转化为适合应用研发的强大计算工具。因此，该项目将VeraChem当前的统计力学软件包（VM2）与广泛使用的量子化学软件包GAMESS连接起来，并实现各种计算方案的驱动程序以实现这一目标。在这种提出的混合方法中，分子构象的玻尔兹曼分布仍将通过彻底的构象搜索来生成，就像经典的 VM2 一样；然而，构象搜索将不仅仅依赖于分子力学，还将受到更可靠的量子力学潜力的指导。 QM 势也将用于熵项，包括非谐效应的处理。将充分利用最近半经验 QM (SEQM) 可靠性的显着改进，并在更高水平的 QM 上进行可选校正。并行处理和复杂的一致性过滤/审查过程将加快计算周转速度。