Identification of novel therapeutics for tuberculosis combining cheminformatics,

结合化学信息学鉴定结核病新疗法,

基本信息

  • 批准号:
    8462896
  • 负责人:
  • 金额:
    $ 51.76万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
  • 财政年份:
    2010
  • 资助国家:
    美国
  • 起止时间:
    2010-07-01 至 2014-10-30
  • 项目状态:
    已结题

项目摘要

DESCRIPTION (provided by applicant): We are witnessing the growing menace of both increasing cases of drug-sensitive and drug-resistant Mycobacterium tuberculosis (Mtb) strains and the challenge to produce the first new tuberculosis (TB) drug in well over 40 years. The TB community, having invested in extensive high-throughput screening efforts, is faced with the question of how to optimally leverage this data in order to move from a hit to a lead to a clinical candidate and potentially a new drug. Complementing this approach, yet conducted on a much smaller scale, cheminformatic techniques have been leveraged. We suggest these computational approaches should be more optimally integrated in a workflow with experimental approaches to accelerate TB drug discovery. This Small Business Technology Transfer Phase II project entitled "Identification of novel therapeutics for tuberculosis combining cheminformatics, diverse databases and logic-based pathway analysis" describes the development of software that will facilitate new drug discovery efforts for Mycobacterium tuberculosis (TB) and the progression of molecules discovered with it as mimics for substrates of enzymes and their in vivo essential genes. In phase 1 we illustrated the concept of loosely marrying the cheminformatic and pathways database that resulted in two compounds as proposed mimics of 2 D-fructose 1,6 bisphosphate with activity against Mtb (MIC 20 and 40mg/ml). In phase II via an API we will link the knowledge in CDD, SRI and other databases and tools seamlessly. A researcher will be able to investigate molecules, targets, pathways and then select metabolites or other molecules for pharmacophore analysis, scoring with TB machine learning models and ADME and drug-likeness assessment from within one interface. This tool will be used to aid the identification of novel therapeutics for tuberculosis and be useful for hypotheses testing, knowledge sharing, data archiving, data mining and drug discovery. We will make CDD into a mobile application such that the generalized workflow in this project can be performed anywhere. We present promising preliminary work which resulted in two active compounds, that suggests phase II support of the mimic strategy to identify compounds of interest for TB would be a viable strategy. This proposal balances software development, database development and drug discovery activities in order to achieve our goals. We expect this product could be quickly applied to other infectious diseases which have a great societal impact and as a stretch goal we will endeavor to demonstrate this.
描述(申请人提供):我们目睹了越来越多的对药物敏感和耐药的结核分枝杆菌(Mtb)菌株病例的威胁,以及40多年来生产第一种结核病新药的挑战。在投入大量的高通量筛查工作后,结核病社区面临着一个问题,即如何最佳地利用这些数据,以便从热门到领先,再到临床 候选人,并有可能成为一种新药。作为对这一方法的补充,但规模要小得多,还利用了化学信息学技术。我们建议,这些计算方法应该更好地与加速结核病药物发现的实验方法结合在一起。这个名为“结合化学信息学、多样化数据库和基于逻辑的途径分析的结核病新疗法的鉴定”的小企业技术转移第二阶段项目描述了软件的开发,该软件将促进结核分枝杆菌(TB)的新药发现工作,以及利用它发现的作为酶底物及其体内基本基因模拟的分子的进展。在第一阶段,我们说明了松散地结合化学信息学和通路数据库的概念,从而产生了两个化合物,如所建议的具有抗结核杆菌活性的2 D-果糖1,6二磷酸的模拟化合物(MIC20和40 mg/ml)。在第二阶段,我们将通过API将CDD、SRI和其他数据库和工具中的知识无缝地联系起来。研究人员将能够研究分子、靶点、途径,然后选择代谢物或其他分子进行药效团分析,使用结核病机器学习模型和ADME进行评分,并在一个界面内进行药物相似性评估。这一工具将被用来帮助确定结核病的新疗法,并有助于假说检验、知识共享、数据存档、数据挖掘和药物发现。我们将把CDD变成一个移动应用程序,这样这个项目中的通用工作流就可以在任何地方执行。我们提出了有希望的初步工作,产生了两种活性化合物,这表明第二阶段支持模拟策略以确定结核病感兴趣的化合物将是一个可行的策略。这项建议平衡了软件开发、数据库开发和药物发现活动,以实现我们的目标。我们预计该产品可以迅速应用于其他具有重大社会影响的传染病,作为一个延伸目标,我们将努力证明这一点。

项目成果

期刊论文数量(8)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Combining Metabolite-Based Pharmacophores with Bayesian Machine Learning Models for Mycobacterium tuberculosis Drug Discovery.
  • DOI:
    10.1371/journal.pone.0141076
  • 发表时间:
    2015
  • 期刊:
  • 影响因子:
    3.7
  • 作者:
    Ekins S;Madrid PB;Sarker M;Li SG;Mittal N;Kumar P;Wang X;Stratton TP;Zimmerman M;Talcott C;Bourbon P;Travers M;Yadav M;Freundlich JS
  • 通讯作者:
    Freundlich JS
Looking back to the future: predicting in vivo efficacy of small molecules versus Mycobacterium tuberculosis.
  • DOI:
    10.1021/ci500077v
  • 发表时间:
    2014-04-28
  • 期刊:
  • 影响因子:
    5.6
  • 作者:
    Ekins S;Pottorf R;Reynolds RC;Williams AJ;Clark AM;Freundlich JS
  • 通讯作者:
    Freundlich JS
Bigger data, collaborative tools and the future of predictive drug discovery.
  • DOI:
    10.1007/s10822-014-9762-y
  • 发表时间:
    2014-10
  • 期刊:
  • 影响因子:
    3.5
  • 作者:
    Ekins, Sean;Clark, Alex M.;Swamidass, S. Joshua;Litterman, Nadia;Williams, Antony J.
  • 通讯作者:
    Williams, Antony J.
Databases and collaboration require standards for human stem cell research.
  • DOI:
    10.1016/j.drudis.2014.10.006
  • 发表时间:
    2015-03
  • 期刊:
  • 影响因子:
    7.4
  • 作者:
    Litterman NK;Ekins S
  • 通讯作者:
    Ekins S
Predictive modeling targets thymidylate synthase ThyX in Mycobacterium tuberculosis.
  • DOI:
    10.1038/srep27792
  • 发表时间:
    2016-06-10
  • 期刊:
  • 影响因子:
    4.6
  • 作者:
    Djaout K;Singh V;Boum Y;Katawera V;Becker HF;Bush NG;Hearnshaw SJ;Pritchard JE;Bourbon P;Madrid PB;Maxwell A;Mizrahi V;Myllykallio H;Ekins S
  • 通讯作者:
    Ekins S
{{ 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 }}

SEAN EKINS其他文献

SEAN EKINS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('SEAN EKINS', 18)}}的其他基金

Preclinical development of a Nipah Virus inhibitor
尼帕病毒抑制剂的临床前开发
  • 批准号:
    10761349
  • 财政年份:
    2023
  • 资助金额:
    $ 51.76万
  • 项目类别:
New therapeutic approaches to identifying molecules for opioid abuse treatment
识别阿片类药物滥用分子的新治疗方法
  • 批准号:
    10385998
  • 财政年份:
    2022
  • 资助金额:
    $ 51.76万
  • 项目类别:
Machine learning approaches to predict Acetylcholinesterase inhibition
预测乙酰胆碱酯酶抑制的机器学习方法
  • 批准号:
    10378934
  • 财政年份:
    2021
  • 资助金额:
    $ 51.76万
  • 项目类别:
MegaTox for analyzing and visualizing data across different screening systems
MegaTox 用于分析和可视化不同筛选系统的数据
  • 批准号:
    10094026
  • 财政年份:
    2020
  • 资助金额:
    $ 51.76万
  • 项目类别:
MegaTox for analyzing and visualizing data across different screening systems
MegaTox 用于分析和可视化不同筛选系统的数据
  • 批准号:
    10470050
  • 财政年份:
    2019
  • 资助金额:
    $ 51.76万
  • 项目类别:
MegaTox for analyzing and visualizing data across different screening systems
MegaTox 用于分析和可视化不同筛查系统的数据
  • 批准号:
    10674729
  • 财政年份:
    2019
  • 资助金额:
    $ 51.76万
  • 项目类别:
MegaTrans – human transporter machine learning models
MegaTrans — 人类运输机机器学习模型
  • 批准号:
    9768844
  • 财政年份:
    2019
  • 资助金额:
    $ 51.76万
  • 项目类别:
MegaPredict for predicting natural product uses and their drug interactions
MegaPredict 用于预测天然产物用途及其药物相互作用
  • 批准号:
    10055938
  • 财政年份:
    2019
  • 资助金额:
    $ 51.76万
  • 项目类别:
Manufacture of an intracerebroventricular Enzyme Replacement Therapy for CLN1 Batten Disease
CLN1巴顿病脑室内酶替代疗法的研制
  • 批准号:
    10483470
  • 财政年份:
    2018
  • 资助金额:
    $ 51.76万
  • 项目类别:
Manufacture of an intracerebroventricular Enzyme Replacement Therapy for CLN1 Batten Disease
CLN1巴顿病脑室内酶替代疗法的研制
  • 批准号:
    10641950
  • 财政年份:
    2018
  • 资助金额:
    $ 51.76万
  • 项目类别:

相似海外基金

Biosynthesis of bet-alanine in autolysosomes.
自溶酶体中 β-丙氨酸的生物合成。
  • 批准号:
    22K08681
  • 财政年份:
    2022
  • 资助金额:
    $ 51.76万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Understanding the metabolic consequences of the systemic alanine depletion in pancreatic ductal adenocarcinoma
了解胰腺导管腺癌中全身丙氨酸消耗的代谢后果
  • 批准号:
    474506
  • 财政年份:
    2022
  • 资助金额:
    $ 51.76万
  • 项目类别:
    Studentship Programs
Characterizing alanine transporters as therapeutic targets for pancreatic cancer
将丙氨酸转运蛋白描述为胰腺癌的治疗靶点
  • 批准号:
    466496
  • 财政年份:
    2021
  • 资助金额:
    $ 51.76万
  • 项目类别:
    Studentship Programs
Understanding the requirements of alanine supply and demand in pancreatic ductal adenocarcinoma
了解胰腺导管腺癌中丙氨酸的供需要求
  • 批准号:
    451838
  • 财政年份:
    2021
  • 资助金额:
    $ 51.76万
  • 项目类别:
    Operating Grants
Sensing living P. aeruginosa using D-alanine derived radiotracers
使用 D-丙氨酸衍生的放射性示踪剂感测活的铜绿假单胞菌
  • 批准号:
    10230924
  • 财政年份:
    2021
  • 资助金额:
    $ 51.76万
  • 项目类别:
Sensing living P. aeruginosa using D-alanine derived radiotracers
使用 D-丙氨酸衍生的放射性示踪剂感测活的铜绿假单胞菌
  • 批准号:
    10399593
  • 财政年份:
    2021
  • 资助金额:
    $ 51.76万
  • 项目类别:
Sensing living P. aeruginosa using D-alanine derived radiotracers
使用 D-丙氨酸衍生的放射性示踪剂感测活的铜绿假单胞菌
  • 批准号:
    10570987
  • 财政年份:
    2021
  • 资助金额:
    $ 51.76万
  • 项目类别:
Spot measurement of alanine radicals produced by irradiation and application of sugar radial to dosimeter
辐照产生的丙氨酸自由基的点测及糖自由基在剂量计中的应用
  • 批准号:
    19K05343
  • 财政年份:
    2019
  • 资助金额:
    $ 51.76万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Metabolic significance of lysosomal beta-alanine
溶酶体β-丙氨酸的代谢意义
  • 批准号:
    18K08528
  • 财政年份:
    2018
  • 资助金额:
    $ 51.76万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
Development of dosimetry technique for IMRT using alanine dosimeter
使用丙氨酸剂量计开发 IMRT 剂量测定技术
  • 批准号:
    18K15615
  • 财政年份:
    2018
  • 资助金额:
    $ 51.76万
  • 项目类别:
    Grant-in-Aid for Early-Career Scientists
{{ showInfoDetail.title }}

作者:{{ showInfoDetail.author }}

知道了