Efficient and Accurate Force Fields for Computer-Aided Drug Design
Efficient and Accurate Force Fields for Computer-Aided Drug Design
批准号:
10092175
负责人:
Feng Wang
金额:
$29.46万
依托单位国家:
美国
项目类别:
财政年份:
2017
资助国家:
美国
项目状态:
已结题
起止时间:
2017-01-01 至 2023-12-31
关键词:
AcidsAddressAffinityAntibiotic ResistanceAntibioticsBacterial InfectionsBindingBinding ProteinsBiologicalCarbon DioxideCodeComplexComputer AssistedComputer-Aided DesignCustomDatabasesDevelopmentDrug CostsDrug DesignDrug usageEnvironmentEvaluationFailureFluorescence Resonance Energy TransferFree EnergyHydration statusIceLeadLigandsLipidsMechanicsMembraneMethodsModelingMulti-Drug ResistanceNatureNisinPartition CoefficientPerformancePharmaceutical PreparationsPharmacologic SubstancePhysiologicalProceduresPropertyProteinsProtocols documentationPublic HealthResearchResolutionRoleSaltsSamplingSeriesSolubilitySource CodeStructureSystemTechniquesTemperatureTestingTimeWorkbaseblindcombatcomputer studiesdesigndrug candidatedrug discoveryelectronic structureexperimental studyimprovedinnovationmacromoleculemeltingmolecular dynamicsnovelpredictive modelingprotocol developmentquantumsimulation
中文摘要
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英文摘要
Efficient and Accurate Force Fields for Computer-Aided-Drug Design
Computer-aided drug design is hampered by the limited accuracy in the force fields that describe the
interactions between drug molecules, their targets, and shared environment. An automated protocol, adaptive
force matching (AFM), is proposed for creating customized force fields that enable more efficient and accurate
computational studies of the structure and function of drug candidates. Putting AFM in place will require the
adaption of highly efficient techniques for sampling of configurations and quantum mechanical calculations of
large systems. The approach will be developed and evaluated in a series of aims with increasing complexity. In
the first two aims, force fields are generated for prediction of hydration free energies of small drug-like
molecules and of the binding affinities for guest-host pairs. The performance of the method will be tested on
examples from the recent SAMPL4 competition. In the last aim, force fields are created for simulations that
allow one to identify nisin derivatives with improved solubility and stability at physiological pH as required for
the design of nisin-based novel antibiotics. This class of drug is generally referred to as lantibiotics, and it
carries the promise to address the increasingly severe problem of multi-drug resistant bacterial infection.
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Surface Penetration without Enrichment: Simulations Show Ion Surface Propensities Consistent with Both Elevated Surface Tension and Surface Sensitive Spectroscopy.
无需富集的表面渗透:模拟显示离子表面倾向与升高的表面张力和表面敏感光谱一致。
DOI:
10.1021/acs.jpcb.9b04424
发表时间:
2019
期刊:
The journal of physical chemistry. B
影响因子:
--
作者:
[Li,Jicun, Wang,Feng]
通讯作者:
Wang,Feng
Pearl-Necklace-Like Local Ordering Drives Polypeptide Collapse.
珍珠项链状局部有序驱动多肽崩溃。
DOI:
10.1021/acs.macromol.9b00562
发表时间:
2019
期刊:
Macromolecules
影响因子:
5.5
作者:
[Majumder,Suman, Hansmann,UlrichHE, Janke,Wolfhard]
通讯作者:
Janke,Wolfhard
DOI:
10.1021/acs.jpcb.9b08965
发表时间:
2020-02-06
期刊:
The journal of physical chemistry. B
影响因子:
--
作者:
[Rogers TR, Wang F]
通讯作者:
Wang F
DOI:
10.1103/physreve.106.015302
发表时间:
2022-07
期刊:
PHYSICAL REVIEW E
影响因子:
2.4
作者:
[Yasar, Fatih, Ray, Alan J., Hansmann, Ulrich H. E.]
通讯作者:
Hansmann, Ulrich H. E.
DOI:
10.1063/5.0035032
发表时间:
2020-12-28
期刊:
The Journal of chemical physics
影响因子:
--
作者:
[Rogers TR, Wang F]
通讯作者:
Wang F
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依托单位:
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项目类别:
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财政年份:--
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负责人:Feng Wang
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依托单位:
海外基金