Designing selective kinase inhibitors via deep learning
Designing selective kinase inhibitors via deep learning
批准号:
10798523
负责人:
John Karanicolas
金额:
$18.13万
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-02-01 至 2025-11-30
关键词:
Administrative SupplementAgreementBiochemicalBiological AssayComputing MethodologiesDrug TargetingEquipmentFundingGrantInstitutionLiquid ChromatographyMaintenanceMalignant NeoplasmsNational Institute of General Medical SciencesProductivityProtein KinaseSystemTest ResultVendorcostdeep learningdesigndetectorhuman diseaseinstrumentinstrumentationkinase inhibitornovelsmall molecule
中文摘要
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英文摘要
Project Summary/Abstract
This is a request for an NIGMS Administrative Supplement to NIGMS grant R01GM141513, to
purchase an Agilent InfinityLab LC/MSD iQ system. Our project entails developing computational methods to
design completely novel small-molecule kinase inhibitors, and then testing the resulting compounds in
biochemical assays. Upon synthesis of these novel computationally designed kinase inhibitors, it is necessary
to verify the intended compound’s identity and purity using LC/MSD (Liquid Chromatography/Mass Selective
Detector). We currently carry out this step using an Agilent 1100 LC/MSD instrument; this equipment was
originally released by the vendor in 1998, and we purchased ours in 2010 as a refurbished unit. The unit has
been heavily utilized over the past decade; in fact, access to this instrument now represents the bottleneck for
further progress in our project. The requested Agilent InfinityLab LC/MSD iQ system will provide the necessary
capabilities to maximize productivity and fully achieve the aims of our NIGMS-sponsored project. Institutional
matching funds will be used to cover the cost of a 5-year agreement covering the warranty and preventative
maintenance.
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海外基金