I-Corps: Physics-Based Binding Affinity Estimator
I-Corps: Physics-Based Binding Affinity Estimator
批准号:
2138667
负责人:
Mahmoud Moradi
金额:
$5.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2021
资助国家:
美国
项目状态:
已结题
起止时间:
2021-07-15 至 2022-12-31
中文摘要
I-Corps项目更广泛的影响/商业潜力是开发一种计算工具,使药物设计和开发更准确,更节省时间。潜在用户,从小型生物技术公司和研究机构到大型制药公司,可以利用这项技术在开发的早期阶段过滤掉大量低亲和力药物。导致药物开发成本高的一个关键因素是失败率高,通过采用更有效的试验前筛选方法,包括使用更准确的亲和力估计器,可以显著降低失败率。所提议的技术的成功实施可能会大大减少药物开发所需的研究和开发支出,并最终使药物开发更快,成本更低。这些活动可以通过提供更有效和更安全的药物来治疗或预防疾病,从而有助于美国和世界各地的公众健康。I-Corps项目的基础是开发一种基于物理的药物结合亲和力评估器,该评估器采用基于全原子分子动力学模拟的最先进的自由能计算方法。与现有技术相比,所提出的估计器可以以更高的准确性估计药物与其靶蛋白的结合亲和力。虽然可用的对接软件包和web服务器提供亲和度估计,但这些估计通常是粗略的对接分数,而不是真正的绑定亲和度,因为它们严重依赖于经验拟合的公式,而不仅仅是基于物理的方法。与现有的对接软件不同,本文提出的技术在估算结合亲和力时明确考虑了环境的影响、药物及其靶点的灵活性等重要因素。所提出的技术可能使使用纯粹基于物理的方法计算药物的结合亲和力成为可能,这种方法比对接软件要准确得多。该奖项反映了美国国家科学基金会的法定使命,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。
英文摘要
The broader impact/commercial potential of this I-Corps project is the development of a computational tool to make drug design and development more accurate and less time-consuming. Potential users, ranging from small biotech companies and research institutes to major pharmaceutical companies, may take advantage of this technology to filter out a significant number of low-affinity drugs at an early stage of development. A key factor resulting in the high cost of drug development is the high rate of failure, which can be significantly reduced by employing more efficient pre-trial screening methods including using more accurate affinity estimators. The successful implementation of the proposed technology may substantially reduce the research and development spending needed for drug development and eventually make drug development faster and less costly. Such activities may contribute to the public health in the US and around the world by providing more efficient and safer drugs to cure or prevent disease.This I-Corps project is based on the development of a physics-based drug binding affinity estimator that employs state-of-the-art free energy calculation methods based on all-atom molecular dynamics simulations. The proposed estimator can estimate the binding affinity of a drug to its target protein with higher accuracy compared to existing techniques. While the available docking software packages and webservers provide affinity estimates, these estimates are generally rough docking scores rather than true binding affinities because they heavily rely on empirically fitted formulas rather than solely physics-based methods. Unlike the existing docking software, the proposed technology explicitly takes into account important factors such as the effects of the environment and the flexibility of the drug and its target in estimating the binding affinities. The proposed technology may make it possible to calculate binding affinities of the drugs using purely physics-based methods that are much more accurate than their docking software counterparts.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.
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会议论文
CAREER: Riemannian Reformulation of Collective Variable Based Free Energy Calculation Methods
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批准号:1945465
-
项目类别:Standard Grant
-
资助金额:$65.0万
-
财政年份:2020
-
负责人:Mahmoud Moradi
-
依托单位:
Collaborative Research: Atomic Level Structural Dynamics in Catalysts
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批准号:1940188
-
项目类别:Continuing Grant
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资助金额:$32.48万
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财政年份:2019
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负责人:Mahmoud Moradi
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依托单位:
国内基金
海外基金
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