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FET: Small: Stochastic Synthesis of Peptides and Small Molecules

FET：小型：肽和小分子的随机合成

基本信息

批准号：
1910878
负责人：
Mohsen Lesani
金额：
$ 50万
依托单位：
University of California-Riverside
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2019
资助国家：
美国
起止时间：
2019-10-01 至 2024-09-30
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1910878&HistoricalAwards=false
关键词：
FET Small Stochastic Synthesis Peptides

项目摘要

This project accelerates the development of new drugs. Currently, the process of developing a new drug takes an average of 12 years and tens or hundreds of millions of dollars. Consequently, only a handful of new drugs enter the market every year. It is essential to bring the level of automation inherent in computing disciplines to the life sciences. The search space for possibly beneficial and life-saving biomolecules is enormous. The proposed approach will ensure that only biomolecules likely to satisfy the desired properties are enumerated and empirically evaluated. Accelerated growth in the pharmaceutical industry strengthens the US economy by creating desirable biotechnology jobs, and increases our overall global competitiveness in biotechnology.This project applies program synthesis principles to automate the discovery of new drugs. The chemist is allowed to specify the characteristics of the desired drug using a domain-specific specification language. For example, a chemist developing a novel peptide drug (a sequence of amino-acids) may request that amino acids at specific positions have certain chemical properties, or that certain constant sequences of amino acids with known behaviors appear in specific locations in the peptide. The chemist can also specify the target proteins in the mix to which the peptide drug should or should not bind. The binding strength of a drug translates to its efficacy. Given a drug specification, the synthesis process automatically identifies a ligand that complies with the specification, can be safely synthesized and strongly binds to the desired proteins.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目加速了新药的开发。目前，开发一种新药的过程平均需要12年时间和数千万或数亿美元。因此，每年只有少数新药进入市场。将计算学科固有的自动化水平带到生命科学中至关重要。可能有益和拯救生命的生物分子的搜索空间是巨大的。所提出的方法将确保只有可能满足所需性质的生物分子被枚举和经验评估。制药业的加速增长通过创造令人满意的生物技术工作岗位来加强美国经济，并提高我们在生物技术领域的整体全球竞争力。本项目应用程序合成原理来自动发现新药。允许化学家使用特定领域的规范语言指定所需药物的特性。例如，开发新型肽药物（氨基酸序列）的化学家可能要求特定位置的氨基酸具有某些化学性质，或者具有已知行为的某些恒定氨基酸序列出现在肽的特定位置。化学家还可以指定混合物中肽药物应该或不应该结合的靶蛋白。药物的结合强度转化为其功效。根据药物规格，合成过程自动识别符合规格的配体，可以安全合成并与所需蛋白质强烈结合。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。