Development and Testing of New Computational Methods for Ligand Discovery and Mechanism

配体发现和机制的新计算方法的开发和测试

• 批准号: 10406014
• 负责人: Brian K Shoichet
• 金额: $ 79.83万
• 依托单位: UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
• 依托单位国家: 美国
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-06-01 至 2027-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10406014
• 关键词: 2019-nCoV; Affect; Biological; Biological Models; Cells; Chemicals; Complement; Computing Methodologies; Consumption; Development; Docking; Drug Delivery Systems; Experimental Models; Funding; G-Protein-Coupled Receptors; Goals; Grant; Head; Human; Individual; Libraries; Ligands; Logic; Methods; Modeling; Modernization; Molecular Conformation; Outcome; Partner in relationship; Pattern; Pharmacology; Productivity; Reader; Role; Scientist; Signal Transduction; Site; Structure; Testing; Viral Proteins; Work; Yeasts; base; drug discovery; flexibility; interest; novel therapeutics; receptor; tool; yeast genetics

Abstract Our long-term goal is to develop structure-based and chemoinformatic methods in ligand discovery, testing these in experimental model systems and applying them to targets of biological interest. To give the reader a sense of our direction, we sketch several questions within four broad foci: A. Development of new docking methods and their testing in model systems like simplified cavity sites, where individual terms may be disentangled. Several upcoming projects leverage the ultra-large libraries we introduced in the last period, including: i. are bigger libraries always better, or at some library size do we saturate? ii. As the library grows, are we still bounded by bio-like molecules, or do we diverge away from these? How does this affect docking hit quality? iii. Can we treat libraries of tens-of-billions to trillions of molecules with better methods and look-ahead pattern matching? We are also exploring iv. flexible receptor docking in the model cavities, and v. treatment of ligand conformational and desolvation strain. B. Turning the structure-based enterprise on its head, we return to the logic of classical pharmacology with modern chemoinformatics, seeking to predict targets from their ligands. Leveraging work in the last period, we i. Investigate if widely consumed molecules, such as neutraceuticals, have specific targets and ii. Use network pharmacology to find molecules to modulate the human targets subverted by SARS-Cov-2 viral proteins. C. Application of these methods to biologically interesting targets, often GPCRs. In the upcoming period, we i. explore bespoke ultra-large libraries for amingergic GPCRs; ii. Extend domain of applicability to transporters; iii. Seek chemical probes for the yeast mating-factor GPCR Ste2 to complement the power of yeast genetics. D. The role of colloidal aggregation and phospholipidosis in early drug discovery. Projects in the upcoming period investigate i. Exploiting colloidal aggregates for drug delivery; ii. Investigating the mechanism of colloidal aggregation and its impact in early discovery; iii. Investigating a new phenomenon that may have wide impact on cell-based ligand discovery, phospholipidosis. This MIRA was previously funded by five grants, and its breadth reflects that. While ambitious, its pragmatism is supported by the productivity of the last period and by extensive preliminary results.

抽象的 我们的长期目标是在配体发现中开发基于结构和化学的方法，测试 这些在实验模型系统中，并将其应用于生物学关注的靶标。给读者一个 我们的方向意识，我们在四个广泛的焦点中勾勒出几个问题： A.开发新的对接方法及其在模型系统中的测试，例如简化的腔站点， 单个条款可能会被解散。几个即将到来的项目利用了我们的超大图书馆 在最后一个时期引入，包括：i。更大的库总是更好，或者在某些图书馆大小的情况下我们 饱和？ ii。随着图书馆的成长，我们仍然是由生物样分子界的，还是我们与 这些？这如何影响对接命中质量？ iii。我们可以处理数千万到万亿的图书馆 分子具有更好的方法和图案图案匹配？我们也在探索IV。柔性受体 在模型腔中进行对接，并v。处理配体构象和脱溶性菌株的处理。 B.将基于结构的企业转向其头上，我们回到古典药理学的逻辑 现代化学信息学，试图从其配体中预测靶标。在上一时期利用工作，我们 我。研究是否具有广泛消耗的分子（例如中性物质）具有特定的靶标和II。使用网络 药理学以找到分子调节SARS-COV-2病毒蛋白颠覆的人类靶标。 C.将这些方法应用于生物学有趣的靶标，通常是GPCR。在即将到来的时期，我们。 探索定制的超大图书馆，以示为AMINGIC GPCR； ii。将适用性的域扩展到转运蛋白； iii。寻求酵母交配因子GPCR Ste2的化学探针，以补充酵母遗传学的能力。 D.胶体聚集和磷脂病在早期药物发现中的作用。即将到来的项目 时期调查i。利用胶体骨料进行​​药物输送； ii。调查机制 胶体聚集及其在早期发现中的影响； iii。调查可能具有的新现象 对基于细胞的配体发现，磷脂病的广泛影响。 此Mira以前是由五项赠款资助的，其广度反映了这一点。虽然雄心勃勃，但它的实用主义 由上一个时期的生产率和广泛的初步结果支持。