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: 8991772
• 负责人: Simon Webb
• 金额: $ 74.64万
• 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/8991772
• 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; Relative (related person); 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）：宿主分子，例如环糊精和甲壳虫，可以“捕获”较小的分子并影响其物理和化学行为。宿主分子保持越强，即结合，其效果越小，效果越小。宿主分子本身也可以化学改变（即衍生化），这可以改变它们结合客体分子以及自身的物理特性的强烈结合。科学家正在发现许多与人类健康相关的宿主 - 宿主技术应用，包括改善药物的特性，使其更有效，更安全，潜在的化学战剂去除剂以及清理环境化学污染物的清除。该领域的基础研究和应用/工业研发的数量正在迅速扩大。鉴于特定的“来宾”分子（例如药物候选者，化学污染物）的关键信息研发科学家需要的是宿主 - 圈的结合亲和力和关联/解离率。该SBIR项目旨在开发一个可以准确预测这些宿主 - 圈结合特性（例如结合自由能）的软件工具。这将使研发科学家可以进行计算实验，以减少所需的昂贵且耗时的台式实验的数量。当前需要开发这种软件工具，因为正如盲人测试挑战最近证明的那样，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。但是，这些概念验证研究尚未转化为适合应用R＆D的强大计算工具。因此，该项目将与广泛使用的量子化学软件包游戏中Verachem的当前统计力学软件包（VM2）接口，并为各种计算方案实施驱动程序以实现此目标。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产生，因为它适用于经典VM2。但是，构象搜索将不仅依赖于分子力学，而要以更可靠的QM潜力为指导。 QM电位还将用于熵术语，包括对非谐作用的处理。对于半经验QM（SEQM）的可靠性的巨大改善，将获得充分的优势，并在QM级别较高的情况下进行可选校正。计算的周转将通过并行处理和复杂的构象异构器/审查过程加快。