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
基本信息
- 批准号:10709551
- 负责人:
- 金额:$ 33.06万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 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:
- 关键词:ABCG2 geneAccelerationAgonistAlgorithmsBenchmarkingBindingBinding ProteinsBiochemicalBiologicalBiological ModelsBiomedical ResearchBiophysicsBoronChargeChemicalsComputer AssistedComputer softwareCoupledDataData SetDevelopmentDivalent CationsDockingDrug DesignDrug TargetingElementsEvaluationEventFree EnergyGenerationsGoalsLigand BindingLigandsMethodsModelingMolecularMolecular ConformationNucleic AcidsOutcomePathway interactionsPerformancePharmaceutical PreparationsPlayPositioning AttributeProceduresProteinsPublished CommentReproductionResearchRoleSamplingSeleniumTechniquesTestingantagonistcomparativefield studyimprovedinsightmacromoleculemechanical forcemolecular mechanicsneural networknext generationnovelnovel strategiesreceptorsimulationsmall moleculesuccess
项目摘要
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AMBER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。其主要
应用是破译小分子配体之间的分子相互作用,
生物分子,特别是蛋白质受体,从而可以
发现增强或消除目标功能。尽管花费了巨大的努力,
尽管如此,准确预测蛋白质-配体结合仍然非常具有挑战性。一个关键
一个成功预测的要素是实用分子力学力场的质量
(MMFF)。从可行性的观点看,经典可加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,这是不容易由极化力场提供的。另一个关键因素
一个成功的预测是采样策略的能力,有效地采样“隐藏”
与状态转换耦合的事件。该项目的主要目标是开发和
测试第三代GAFF(GAFF 3),以显着提高通用的质量-
安珀力场GAFF 3将在生物分子-配体研究中受到严格评价
交互使用一种新的GPU加速的基于正交空间回火的非线性动态
(OST)算法先进的取样技术将保证我们的大分子配体
结合自由能的计算并不因现有的采样问题而复杂,
可以客观评价。我们将首先利用新的物理电荷ABCG 2开发GAFF 3
该模型在大尺度溶剂化自由能方面表现出上级性能
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GAFF 3开发中得到广泛应用。我们将
然后批判性地评估GAFF 3在研究生物分子-配体相互作用中的性能,
基于路径的自由能方法和端点自由能方法。OST采样方法为
为这项评估工作制定和实施的。最后,我们计划应用各种策略
处理我们或我们的用户识别的“困难”分子。这些战略将包括精细原子
打字和引入新的功能形式。我们相信,这些努力将使GAFF 3能够
接近加性模型可能具有的性能极限。我们还将扩大化学
GAFF 3的空间,以覆盖当前GAFF未覆盖的那些元素,但经常
存在于药物和PDB配体中。因此,这些研究目标的成功实现将
帮助我们克服准确建模蛋白质配体和核酸的挑战,
配体结合
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Junmei Wang其他文献
Junmei Wang的其他文献
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{{ truncateString('Junmei Wang', 18)}}的其他基金
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:
10798829 - 财政年份:2022
- 资助金额:
$ 33.06万 - 项目类别:
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:
10503886 - 财政年份:2022
- 资助金额:
$ 33.06万 - 项目类别:
Protein Design Using Physical Scoring Functions integrated with Site Couplings
使用与位点耦合集成的物理评分函数进行蛋白质设计
- 批准号:
8320949 - 财政年份:2011
- 资助金额:
$ 33.06万 - 项目类别:
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