New Generation of General AMBER Force Field for Biomedical Research

用于生物医学研究的新一代通用琥珀力场

• 批准号: 10709551
• 负责人: Junmei Wang
• 金额: $ 33.06万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-24 至 2026-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10709551
• 关键词: ABCG2 gene; Acceleration; Agonist; Algorithms; Benchmarking; Binding; Binding Proteins; Biochemical; Biological; Biological Models; Biomedical Research; Biophysics; Boron; Charge; Chemicals; Computer Assisted; Computer software; Coupled; Data; Data Set; Development; Divalent Cations; Docking; Drug Design; Drug Targeting; Elements; Evaluation; Event; Free Energy; Generations; Goals; Ligand Binding; Ligands; Methods; Modeling; Molecular; Molecular Conformation; Nucleic Acids; Outcome; Pathway interactions; Performance; Pharmaceutical Preparations; Play; Positioning Attribute; Procedures; Proteins; Published Comment; Reproduction; Research; Role; Sampling; Selenium; Techniques; Testing; antagonist; comparative; field study; improved; insight; macromolecule; mechanical force; molecular mechanics; neural network; next generation; novel; novel strategies; receptor; simulation; small molecule; success

New Generation of General AMBER Force Field for Biomedical Research Molecular simulation plays an essential role in biochemical and biophysical research. Its major application is to decipher molecular interactions between small molecule ligands and biomolecules, especially protein receptors, so that highly potent agonists or antagonists can be discovered to enhance or eradicate target functions. Despite tremendous efforts spent on development, it is still very challenging to accurately predict protein-ligand binding. A key element to a successful prediction is the quality of practical molecular mechanics force field (MMFF). From the viewpoint of feasibility, the classical additive force field is in a unique position to offer computational efficiency while maintaining robustness for accurate and automated parametrization, which cannot be easily afforded by a polarizable force field. The other key factor to a successful prediction is the ability of the sampling strategy to effectively sample “hidden” events that are coupled with state transitions. The major goal of this project is to develop and test the 3rd generation of GAFF (GAFF3) to significantly improve the quality of the general- purpose AMBER force fields. GAFF3 will be critically evaluated in studying biomolecule-ligand interactions using a novel GPU-accelerated 𝜆 -dynamics based orthogonal space tempering (OST) algorithm. The advanced sampling technique will guarantee that our macromolecule-ligand binding free energy calculations is not complicated by existing sampling issues so that GAFF3 can be objectively evaluated. We will first develop GAFF3 utilizing ABCG2, a new physical charge model which has demonstrated its superior performance in large scale solvation free energy calculations; New force field parameterization techniques, such as applying ANI-1x potentials to fast detect “bad” torsional parameters, will be extensively applied in GAFF3 development. We will then critically evaluate the GAFF3 performance in studying biomolecule-ligand interactions using both pathway-based and endpoint free energy methods. The OST sampling method will be developed and implemented for this evaluation effort. Last, we plan to apply a variety of strategies to handle “difficult” molecules identified by us or our users. Those strategies will include fine atom typing and introduction of new functional forms. We believe that those efforts will allow GAFF3 to approach the performance limit an additive model could have. We will also expand the chemical space of GAFF3 to cover those elements not covered by the current GAFF, but frequently occurring in drugs and PDB ligands. Therefore, the successful pursuit of these research aims will facilitate us to surmount the challenges in accurately modeling protein-ligand and nucleic acid- ligand binding.

面向生物医学研究的新一代广义琥珀力场 分子模拟在生化和生物物理研究中起着至关重要的作用。它的主要特点 应用是破译小分子配体和分子间的相互作用 生物分子，尤其是蛋白质受体，因此高效的激动剂或拮抗剂可以 被发现可以增强或消除目标功能。尽管花费了巨大的努力在 尽管发展迅速，但要准确预测蛋白质与配体的结合仍然是非常具有挑战性的。一把钥匙 一个成功预测的要素是实用分子力力场的好坏 (MMFF)。从可行性的角度来看，经典的附加力场具有独特的地位。 提供计算效率，同时保持精确度和自动化的健壮性 可极化的力场不容易提供的参数化。另一个关键因素 成功预测的关键在于抽样策略能否有效地“隐藏”样本 与状态转换相结合的事件。这个项目的主要目标是开发和 测试第三代GAFF(GAFF3)，显著提高通用- 用途：琥珀原力区域。GAFF3在生物分子配体研究中的重要作用 一种新的基于图形处理器加速的𝜆动力学正交空间调谐交互 (OST)算法。先进的采样技术将保证我们的大分子配体 结合自由能的计算不会因为现有的采样问题而变得复杂，因此GAFF3 可以得到客观的评价。我们将首先利用ABCG2，一种新的物理电荷来开发GAFF3 在大规模溶剂化自由能方面表现出优越性能的模型 计算；新的力场参数化技术，例如将ANI-1X势应用于 快速检测不良扭转参数，将在GAFF3的研制中得到广泛应用。我们会 然后对GAFF3在研究生物分子-配体相互作用方面的性能进行了批判性的评估 基于路径的和基于终点的自由能方法。OST抽样方法为 为这项评估工作制定和实施。最后，我们计划应用多种策略 来处理由我们或我们的用户识别的“困难的”分子。这些战略将包括精细原子 打字和引入新的功能形式。我们认为，这些努力将使GAFF3能够 接近加法模型的性能极限。我们还将扩大化学品的使用范围 GAFF3的空间，以涵盖当前GAFF未涵盖但经常涉及的那些要素 存在于药物和PDB配体中。因此，这些研究目标的成功追求将 帮助我们克服蛋白质-配体和核酸精确建模方面的挑战- 配基结合。