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:10798829
- 负责人:
- 金额:$ 15.19万
- 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 geneAccelerationAgonistAlgorithmsBindingBinding ProteinsBiochemicalBiomedical ResearchBiophysicsChargeCoupledDevelopmentEvaluationEventFoundationsFree EnergyGenerationsGoalsLigand BindingLigandsMethodsModelingMolecularNucleic AcidsPathway interactionsPerformancePharmaceutical PreparationsPlayProteinsResearchRoleSamplingStructureSystemTechniquesTestingantagonistfield studyimprovedmacromoleculemechanical forcemolecular mechanicsnovelreceptorscreeningsimulationsmall molecule
项目摘要
Project Summary
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. To overcome
the challenge, we need (1) to develop a high-quality molecular mechanics force field (MMFF) to
accurately describe the energetics of the simulation systems, and (2) to apply a sampling strategy
which can 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 the general-purpose AMBER force
field of GAFF (GAFF3) to significantly improve the quality of the AMBER small molecule force
field. 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
are not complicated by existing sampling issues so that GAFF3 can be objectively evaluated. The
study includes three specific goals: (1) to develop GAFF3 utilizing ABCG2, a new physical charge
model which has demonstrated its superior performance in large scale solvation free energy
calculations. Large-scale ab initio calculations will be performed for drugs and druglike screening
compounds to derive force field parameters; (2) to critically evaluate the GAFF3 performance in
studying biomolecule-ligand interactions using both pathway-based and endpoint free energy
methods using GPU computing. The OST sampling method will be continuously developed and
implemented for this evaluation effort; and (3) to apply a variety of strategies to handle “difficult”
molecules identified by us or our users. The strategies will include fine atom typing and
introduction of new functional forms. We believe that these efforts will allow GAFF3 to approach
the performance limit an additive model could have. The successful pursuit of these research
aims will facilitate us to surmount the challenges in accurately modeling protein-ligand and nucleic
acid-ligand binding.
项目摘要
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。克服
面对挑战,我们需要(1)开发高质量的分子力学力场(MMFF),
准确描述模拟系统的能量学,以及(2)应用采样策略
其可以有效地对与状态转换耦合的“隐藏”事件进行采样。主要
该项目的目标是开发和测试第三代通用琥珀部队
场GAFF(GAFF 3),以显着提高质量的琥珀小分子部队
领域GAFF 3将在研究生物分子-配体相互作用中使用一种新的
基于GPU加速的正交空间回火(OST)算法。先进
采样技术将保证我们的大分子-配体结合自由能计算
不会因现有的采样问题而变得复杂,因此可以客观地评估GAFF 3。的
研究包括三个具体目标:(1)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
计算。将对药物和类药物筛选进行大规模从头计算
化合物,以获得力场参数;(2)严格评估GAFF 3在
研究生物分子与配体的相互作用,同时使用基于路径的自由能和终点自由能
使用GPU计算的方法。将继续开发OST采样方法,
(3)采用各种策略来处理“困难”问题,
我们或我们的用户识别的分子。这些策略将包括精细的原子分型,
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限制。这些研究的成功
aims将有助于我们克服精确建模蛋白质-配体和核酸的挑战,
酸-配体结合
项目成果
期刊论文数量(6)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Distribution of Bound Conformations in Conformational Ensembles for X-ray Ligands Predicted by the ANI-2X Machine Learning Potential.
- DOI:10.1021/acs.jcim.3c01350
- 发表时间:2023-11-13
- 期刊:
- 影响因子:5.6
- 作者:Han, Fengyang;Hao, Dongxiao;He, Xibing;Wang, Luxuan;Niu, Taoyu;Wang, Junmei
- 通讯作者:Wang, Junmei
Development and test of highly accurate endpoint free energy methods. 2: Prediction of logarithm of n ‐octanol–water partition coefficient ( logP ) for druglike molecules using MM‐PBSA method
高精度端点自由能方法的开发和测试。
- DOI:10.1002/jcc.27086
- 发表时间:2023
- 期刊:
- 影响因子:3
- 作者:Sun, Yuchen;Hou, Tingjun;He, Xibing;Man, Viet Hoang;Wang, Junmei
- 通讯作者:Wang, Junmei
In Silico Screening of Natural Flavonoids against 3-Chymotrypsin-like Protease of SARS-CoV-2 Using Machine Learning and Molecular Modeling.
- DOI:10.3390/molecules28248034
- 发表时间:2023-12-10
- 期刊:
- 影响因子:0
- 作者:Cai L;Han F;Ji B;He X;Wang L;Niu T;Zhai J;Wang J
- 通讯作者:Wang J
Discovery of Potent and Selective CB2 Agonists Utilizing a Function-Based Computational Screening Protocol.
- DOI:10.1021/acschemneuro.3c00580
- 发表时间:2023-11-01
- 期刊:
- 影响因子:5
- 作者:Ge, Haixia;Ji, Beihong;Fang, Jiahui;Wang, Jiayang;Li, Jing;Wang, Junmei
- 通讯作者:Wang, Junmei
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
数据更新时间:{{ journalArticles.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ monograph.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ sciAawards.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ conferencePapers.updateTime }}
{{ item.title }}
- 作者:
{{ item.author }}
数据更新时间:{{ patent.updateTime }}
Junmei Wang其他文献
Junmei Wang的其他文献
{{
item.title }}
{{ item.translation_title }}
- DOI:
{{ item.doi }} - 发表时间:
{{ item.publish_year }} - 期刊:
- 影响因子:{{ item.factor }}
- 作者:
{{ item.authors }} - 通讯作者:
{{ item.author }}
{{ 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:
10709551 - 财政年份:2022
- 资助金额:
$ 15.19万 - 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:
$ 15.19万 - 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:
$ 15.19万 - 项目类别:
相似海外基金
SHINE: Origin and Evolution of Compressible Fluctuations in the Solar Wind and Their Role in Solar Wind Heating and Acceleration
SHINE:太阳风可压缩脉动的起源和演化及其在太阳风加热和加速中的作用
- 批准号:
2400967 - 财政年份:2024
- 资助金额:
$ 15.19万 - 项目类别:
Standard Grant
Collaborative Research: FuSe: R3AP: Retunable, Reconfigurable, Racetrack-Memory Acceleration Platform
合作研究:FuSe:R3AP:可重调、可重新配置、赛道内存加速平台
- 批准号:
2328975 - 财政年份:2024
- 资助金额:
$ 15.19万 - 项目类别:
Continuing Grant
EXCESS: The role of excess topography and peak ground acceleration on earthquake-preconditioning of landslides
过量:过量地形和峰值地面加速度对滑坡地震预处理的作用
- 批准号:
NE/Y000080/1 - 财政年份:2024
- 资助金额:
$ 15.19万 - 项目类别:
Research Grant
Market Entry Acceleration of the Murb Wind Turbine into Remote Telecoms Power
默布风力涡轮机加速进入远程电信电力市场
- 批准号:
10112700 - 财政年份:2024
- 资助金额:
$ 15.19万 - 项目类别:
Collaborative R&D
Collaborative Research: FuSe: R3AP: Retunable, Reconfigurable, Racetrack-Memory Acceleration Platform
合作研究:FuSe:R3AP:可重调、可重新配置、赛道内存加速平台
- 批准号:
2328973 - 财政年份:2024
- 资助金额:
$ 15.19万 - 项目类别:
Continuing Grant
Collaborative Research: FuSe: R3AP: Retunable, Reconfigurable, Racetrack-Memory Acceleration Platform
合作研究:FuSe:R3AP:可重调、可重新配置、赛道内存加速平台
- 批准号:
2328972 - 财政年份:2024
- 资助金额:
$ 15.19万 - 项目类别:
Continuing Grant
Collaborative Research: A new understanding of droplet breakup: hydrodynamic instability under complex acceleration
合作研究:对液滴破碎的新认识:复杂加速下的流体动力学不稳定性
- 批准号:
2332916 - 财政年份:2024
- 资助金额:
$ 15.19万 - 项目类别:
Standard Grant
Collaborative Research: A new understanding of droplet breakup: hydrodynamic instability under complex acceleration
合作研究:对液滴破碎的新认识:复杂加速下的流体动力学不稳定性
- 批准号:
2332917 - 财政年份:2024
- 资助金额:
$ 15.19万 - 项目类别:
Standard Grant
Collaborative Research: FuSe: R3AP: Retunable, Reconfigurable, Racetrack-Memory Acceleration Platform
合作研究:FuSe:R3AP:可重调、可重新配置、赛道内存加速平台
- 批准号:
2328974 - 财政年份:2024
- 资助金额:
$ 15.19万 - 项目类别:
Continuing Grant
Radiation GRMHD with Non-Thermal Particle Acceleration: Next-Generation Models of Black Hole Accretion Flows and Jets
具有非热粒子加速的辐射 GRMHD:黑洞吸积流和喷流的下一代模型
- 批准号:
2307983 - 财政年份:2023
- 资助金额:
$ 15.19万 - 项目类别:
Standard Grant