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.

用于生物医学研究的新一代通用琥珀力场 分子模拟在生物化学和生物物理研究中起着至关重要的作用。 应用是破译小分子配体和 生物分子，特别是蛋白质受体，因此可以产生高效的激动剂或拮抗剂 尽管付出了巨大的努力，但仍发现增强或消除目标功能。 发展中，准确预测蛋白质-配体结合仍然非常具有挑战性。 成功预测的要素是实用分子力学力场的质量 (MMFF) 从可行性的角度来看，经典的加性力场处于独特的地位。 提供计算效率，同时保持准确和自动化的鲁棒性 参数化，这是极化力场无法轻易实现的。 成功预测的关键在于采样策略有效采样“隐藏”的能力 该项目的主要目标是开发和实现与状态转换相结合的事件。 测试第三代GAFF（GAFF3），显着提高通用质量- 目的 AMBER 力场将在生物分子配体研究中受到严格评估。 使用新颖的 GPU 加速的 𝜆 -基于动力学的正交空间回火进行交互 (OST)算法。先进的采样技术将保证我们的大分子配体。 结合自由能计算并不因现有的采样问题而复杂化，因此 GAFF3 我们将首先利用新的物理电荷ABCG2开发GAFF3。 该模型在大规模溶剂化自由能方面展示了其优越的性能 计算；新的力场参数化技术，例如将 ANI-1x 势应用到 快速检测“坏”扭转参数，将广泛应用于GAFF3开发中。 然后批判性地评估 GAFF3 在研究生物分子-配体相互作用中的性能 基于路径的方法和端点自由能方法都将是 OST 采样方法。 最后，我们计划应用多种策略。 处理我们或我们的用户识别的“困难”分子这些策略将包括精细原子。 我们相信，这些努力将使 GAFF3 能够 接近增材模型可能具有的性能极限我们还将扩展化学物质。 GAFF3 的空间来涵盖当前 GAFF 未涵盖的要素，但经常 因此，成功实现这些研究目标将发生在药物和 PDB 配体中。 帮助我们克服准确建模蛋白质配体和酸的挑战 配体结合。