EnzyDock-based Multistate and Multiscale Tools for Covalent Drug Design
EnzyDock-based Multistate and Multiscale Tools for Covalent Drug Design
批准号:
10575904
负责人:
Kwangho Nam
金额:
$19.93万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-01-01 至 2024-11-30
关键词:
AddressAffinityAlgorithmsBenchmarkingBindingBinding SitesBiologicalCalibrationChemical ModelsChemicalsComplexConsensusCrystallographyCysteineDataDatabasesDevelopmentDockingDrug DesignEvaluationEventFamilyFutureGoalsInterventionKineticsKnowledgeLigand BindingLigandsLinkMedicineMethodsModelingMolecularMolecular ConformationPharmaceutical PreparationsPhaseProcessProgram DevelopmentPropertyProteinsQuantum MechanicsReactionResearchSiteSolventsStructureSystemTechnologyTemperatureTestingThermodynamicsToxic effectTrainingTranslatingchemical bondchemical reactioncheminformaticscomputer studiescost effectivecovalent bonddensitydesigndrug discoveryenzyme mechanismimprovedin silicoinhibitorinterestmolecular mechanicsnoveloff-target siteprogramsscreeningsuccesstheoriestool
中文摘要
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英文摘要
PROJECT SUMMARY/ABSTRACT
In recent years, FDA has approved a growing number of drugs that are covalently linked to target biological
molecules. To expand the development of covalent inhibitors, technologies more specific to the discovery of
such inhibitors are needed. It is also necessary to address concerns regarding off-site reactivity and toxicity
associated with covalent drugs. The particular focus of this proposal is to develop multiscale in silico covalent
docking approaches by integrating robust quantum mechanical and molecular mechanical (QM/MM) potentials
with the EnzyDock docking platform, thus enabling explicit modeling of multi-step chemical events and their
energetic contributions during the search for docked poses. Current docking approaches lack the ability to
perform covalent bond formation in a manner consistent with an inhibitor’s pre-covalent binding mode, as well
as with the reaction transition state and covalently bonded mode. This wanting ability not only hampers the
fundamental understanding of warhead-target reactivity, but also poses a technical barrier for advancing in silico
docking strategies. Indeed, many existing docking programs offer the capacity to perform covalent docking but
in an ad hoc fashion, as covalent docking was not considered from the design phase of the program development.
With the goal to overcome this technical challenge, two specific aims are: AIM 1 is to develop a multiscale
QM/MM/EnzyDock covalent docking method. In this development, EnzyDock will serve as the primary docking
platform and robust semiempirical QM/MM potentials will be developed, calibrated for each specific warhead-
target reaction type and combined with EnzyDock. In addition, we will develop and implement the generalized
Born (GB) solvation model with the QM/MM potential framework to improve the energetics of QM/MM-docked
poses. AIM 2 will apply the QM/MM/EnzyDock approach developed in AIM 1 to establish effective workflow for
in silico screening of large covalent inhibitor databases. Specifically, two workflows will be explored: The first
workflow is based on docking with a predefined covalent attachment site, which is employed in most covalent
docking programs. The second workflow entails a dynamic approach to covalent docking, in which covalent
attachment sites on the ligand are searched and determined on the fly during docking using cheminformatics
analysis and spatial proximity with target residues in the binding pocket. In this research, the study will be limited
to the warheads that react only with cysteine residues, while additional target residues, reaction types and
warheads will be considered in future research to construct a more comprehensive warhead-target reaction
database. Thus, the two workflows will be tested and benchmarked against known structures and
kinetic/thermodynamic data of drug-Cys covalent systems. We expect that the methods developed in this project
will make the in silico covalent inhibitor discovery more powerful and help understand electrophilic-target
reactivity for use in warhead design and selection.
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Multiscale Modeling of Protein Kinase Structure, Catalysis and Allostery
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批准号:10473749
-
项目类别:
-
资助金额:$33.32万
-
财政年份:2019
-
负责人:Kwangho Nam
-
依托单位:
Multiscale Modeling of Protein Kinase Structure, Catalysis and Allostery
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批准号:10016867
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项目类别:
-
资助金额:$35.21万
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财政年份:2019
-
负责人:Kwangho Nam
-
依托单位:
Multiscale Modeling of Protein Kinase Structure, Catalysis and Allostery
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批准号:10240612
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项目类别:
-
资助金额:$35.29万
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财政年份:2019
-
负责人:Kwangho Nam
-
依托单位:
海外基金