Tissue-Specific Analysis of Pharmacological Pathways.
Tissue-Specific Analysis of Pharmacological Pathways.
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DOI：
10.1002/psp4.12305
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发表时间：
2018-07
期刊：
影响因子：
--
通讯作者：
Tatonetti NP
中科院分区：
文献类型：
--
作者：
Hao Y;Quinnies K;Realubit R;Karan C;Tatonetti NP
了解靶向蛋白质的下游后果对药物设计至关重要。目前的方法在组织幼稚假设下研究分子效应。然而，许多靶蛋白具有组织特异性表达。需要系统研究将药物与体内人体组织中的靶向途径联系起来。我们引入了一种数据驱动的方法，将药物-靶标关系与基因表达、蛋白质-蛋白质相互作用和途径注释数据相结合。我们将我们的方法应用于四个独立的全基因组表达数据集，并在259个人体组织或细胞系中的1，034种药物和954种途径之间建立了467，396个连接。我们使用L1000和药物基因组学知识库（PharmGKB）的数据验证了我们的结果，并观察到高精度和召回率。我们预测并测试了22种以前未知的化合物的抗凝血作用，并使用临床数据来回顾性地验证这些作用。我们的系统研究提供了对药物的细胞反应的更好理解，并可应用于系统药理学的许多研究课题。
Understanding the downstream consequences of pharmacologically targeted proteins is essential to drug design. Current approaches investigate molecular effects under tissue‐naïve assumptions. Many target proteins, however, have tissue‐specific expression. A systematic study connecting drugs to target pathways in in vivo human tissues is needed. We introduced a data‐driven method that integrates drug‐target relationships with gene expression, protein‐protein interaction, and pathway annotation data. We applied our method to four independent genomewide expression datasets and built 467,396 connections between 1,034 drugs and 954 pathways in 259 human tissues or cell lines. We validated our results using data from L1000 and Pharmacogenomics Knowledgebase (PharmGKB), and observed high precision and recall. We predicted and tested anticoagulant effects of 22 compounds experimentally that were previously unknown, and used clinical data to validate these effects retrospectively. Our systematic study provides a better understanding of the cellular response to drugs and can be applied to many research topics in systems pharmacology.
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影响因子：
64.8
作者：
Kim, Min-Sik;Pinto, Sneha M.;Getnet, Derese;Nirujogi, Raja Sekhar;Manda, Srikanth S.;Chaerkady, Raghothama;Madugundu, Anil K.;Kelkar, Dhanashree S.;Isserlin, Ruth;Jain, Shobhit;Thomas, Joji K.;Muthusamy, Babylakshmi;Leal-Rojas, Pamela;Kumar, Praveen;Sahasrabuddhe, Nandini A.;Balakrishnan, Lavanya;Advani, Jayshree;George, Bijesh;Renuse, Santosh;Selvan, Lakshmi Dhevi N.;Patil, Arun H.;Nanjappa, Vishalakshi;Radhakrishnan, Aneesha;Prasad, Samarjeet;Subbannayya, Tejaswini;Raju, Rajesh;Kumar, Manish;Sreenivasamurthy, Sreelakshmi K.;Marimuthu, Arivusudar;Sathe, Gajanan J.;Chavan, Sandip;Datta, Keshava K.;Subbannayya, Yashwanth;Sahu, Apeksha;Yelamanchi, Soujanya D.;Jayaram, Savita;Rajagopalan, Pavithra;Sharma, Jyoti;Murthy, Krishna R.;Syed, Nazia;Goel, Renu;Khan, Aafaque A.;Ahmad, Sartaj;Dey, Gourav;Mudgal, Keshav;Chatterjee, Aditi;Huang, Tai-Chung;Zhong, Jun;Wu, Xinyan;Shaw, Patrick G.;Freed, Donald;Zahari, Muhammad S.;Mukherjee, Kanchan K.;Shankar, Subramanian;Mahadevan, Anita;Lam, Henry;Mitchell, Christopher J.;Shankar, Susarla Krishna;Satishchandra, Parthasarathy;Schroeder, John T.;Sirdeshmukh, Ravi;Maitra, Anirban;Leach, Steven D.;Drake, Charles G.;Halushka, Marc K.;Prasad, T. S. Keshava;Hruban, Ralph H.;Kerr, Candace L.;Bader, Gary D.;Iacobuzio-Donahue, Christine A.;Gowda, Harsha;Pandey, Akhilesh
通讯作者：
Pandey, Akhilesh
影响因子：
5.5
作者：
Gaborit, Nathalie;Le Bouter, Sabrina;Demolombe, Sophie
通讯作者：
Demolombe, Sophie
影响因子：
4.6
作者：
Chang, Jeremy B.;Quinnies, Kayla M.;Tatonetti, Nicholas P.
通讯作者：
Tatonetti, Nicholas P.
影响因子：
2.5
作者：
Melas, Ioannis N.;Sakellaropoulos, Theodore;Bai, Jane P. F.
通讯作者：
Bai, Jane P. F.
DOI：
10.1155/2015/917345
发表时间：
2015
期刊：
Evidence-based complementary and alternative medicine : eCAM
影响因子：
--
作者：
Kuo YL;Chen CH;Chuang TH;Hua WK;Lin WJ;Hsu WH;Chang PM;Hsu SL;Huang TH;Kao CY;Huang CY
通讯作者：
Huang CY