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Therapeutic Targets Database

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Therapeutic Target Database (TTD)
TTD log
Content
DescriptionDrug target database
Contact
LaboratoryInnovative Drug Research and Bioinformatics Group (IDRB) Bioinformatics and Drug Design Group (BIDD)
Primary citationPMID 31691823
Release date11 Nov, 2019
Access
Websitehttp://db.idrblab.net/ttd/
Miscellaneous
LicenseFree access
Version7.1.01

Therapeutic Target Database(TTD) is a pharmaceutical and medical repository[1] constructed by the Innovative Drug Research and Bioinformatics Group (IDRB) at Zhejiang University, China & the Bioinformatics and Drug Design Group at the National University of Singapore. It provides information about known and explored therapeutic protein and nucleic acid targets,[2] the targeted disease,[3] pathway information[4] and the corresponding drugs directed at each of these targets.[5] Detail knowledge about target function, sequence, 3D structure, ligand binding properties, enzyme nomenclature and drug structure, therapeutic class, and clinical development status.[6] TTD can be freely accessible without any login requirement at: http://db.idrblab.net/ttd/.

The Statistics of TTD Database

This database currently contains 3,419 therapeutic targets (461 successful, 1,191 clinical trial, 207 patented and 1,560 research targets) and 37,316 drugs (2,649 approved, 9,465 clinical trial, 5,059 patented and 20,143 experimental drugs). The targets and drugs in TTD cover 583 protein biochemical classes and 958 drug therapeutic classes, respectively.[1] The latest version of the International Classification of Diseases (ICD-11) codes released by WHO are incorporated in TTD to facilitate the clear definition of disease/disease class.[7]

Validation of Primary Therapeutic Target

Target validation normally requires the determination that the target is expressed in the disease-relevant cells/tissues,[8] it can be directly modulated by a drug or drug-like molecule with adequate potency in biochemical assay,[9] and that target modulation in cell and/or animal models ameliorates the relevant disease phenotype.[10] Therefore, TTD collects three types of target validation data:[11]

  • Experimentally determined potency of drugs against their primary target or targets.[8]
  • Evident potency or effects of drugs against disease models (cell-lines, ex-vivo, in-vivo models) linked to their primary target or targets.[10]
  • Observed effects of target knockout, knockdown, RNA interference, transgenetic, antibody or antisense treated in-vivo models.[9]

Mutation and Expression Profile of Target

Extensive efforts have been directed at the discovery, investigation and clinical monitoring of targeted therapeutics.[12] These efforts may be facilitated by the convenient access of the genetic,[13] proteomic,[14] interactive and other aspects of the therapeutic targets.[15] The related data are provided in TTD:[16]

  • 2,000 drug resistance mutations in 83 targets and 104 target/drug regulatory genes.[17]
  • Differential expression profiles of 758 targets in the disease-relevant drug-targeted tissue[18] and the non-targeted tissues.[19]
  • 1,008 target combinations[20] of 1,764 drugs and the 1,604 target combinations of 664 multi-target drugs.[21]

Clinical Trial and Patent Protected Target

Increasing numbers of proteins, nucleic acids and other molecular entities have been explored as therapeutic targets, hundreds of which are targets of approved, clinical trial and patent protected drugs.[22] Knowledge of these targets and corresponding drugs, particularly those in clinical uses, trials and patented, is highly useful for facilitating drug discovery.[23] The latest version of TTD provided:[1]

  • Clinical trial agents and their targets[24] together with their structures and experimental activity values.[25]
  • Patented agents and their targets[26] together with their structures and experimental activity values.[27]

Regulator and Signaling Pathway of Target

Knowledge of therapeutic targets and early drug candidates is useful for improved drug discovery.[28] Particularly, the data of target regulators and affiliated signaling pathways can facilitate the researches regarding druggability,[29] systems pharmacology,[30] new trends, molecular landscapes,[20] and the development of drug discovery tools.[31] Some transporters database are provided[32] TTD is thus developed to provide such information about:[1]

  • Target-regulating microRNAs[33] & transcription factors[34] and target-interacting proteins.[35]
  • Comprehensive target-pathway pairs fully referenced by multiple pathway databases.[36][37]
  • The convenient access of the multiple targets and drugs cross-linked to each of these pathway entries.[31]

References

  1. ^ a b c d Wang, Yunxia; Zhang, Song; Li, Fengcheng; Zhou, Ying; Zhang, Ying; Wang, Zhengwen; Zhang, Runyuan; Zhu, Jiang; Ren, Yuxiang; Tan, Ying; Qin, Chu (6 November 2019). "Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics". Nucleic Acids Research. 48 (D1): D1031–D1041. doi:10.1093/nar/gkz981. ISSN 1362-4962. PMC 7145558. PMID 31691823.
  2. ^ Hopkins AL, Groom CR (2002). "The druggable genome". Nature Reviews Drug Discovery. 1 (9): 727–30. doi:10.1038/nrd892. PMID 12209152. S2CID 13166282.
  3. ^ Overington JP, Al-Lazikani B, Hopkins AL (2006). "How many drug targets are there?". Nature Reviews Drug Discovery. 5 (12): 993–6. doi:10.1038/nrd2199. PMID 17139284. S2CID 11979420.
  4. ^ Zheng CJ, Han LY, Yap CW, Ji ZL, Cao ZW, Chen YZ (2006). "Therapeutic targets: progress of their exploration and investigation of their characteristics". Pharmacol. Rev. 58 (2): 259–79. doi:10.1124/pr.58.2.4. PMID 16714488. S2CID 3082221.
  5. ^ Li, Ying Hong; Yu, Chun Yan; Li, Xiao Xu; Zhang, Peng; Tang, Jing; Yang, Qingxia; Fu, Tingting; Zhang, Xiaoyu; Cui, Xuejiao; Tu, Gao; Zhang, Yang (4 January 2018). "Therapeutic target database update 2018: enriched resource for facilitating bench-to-clinic research of targeted therapeutics". Nucleic Acids Research. 46 (D1): D1121–D1127. doi:10.1093/nar/gkx1076. ISSN 1362-4962. PMC 5753365. PMID 29140520.
  6. ^ Li YH, Yu CY, Li XX, Zhang P, Tang J, Yang Q, Fu T, Zhang X, Cui X, Tu G, Zhang Y, Li S, Yang F, Sun Q, Qin C, Zeng X, Chen Z, Chen YZ, Zhu F (2018). "Therapeutic target database update 2018: enriched resource for facilitating bench-to-clinic research of targeted therapeutics". Nucleic Acids Res. 46 (D1): D1121–D1127. doi:10.1093/nar/gkx1076. PMC 5753365. PMID 29140520.
  7. ^ The Lancet, null (8 June 2019). "ICD-11". Lancet. 393 (10188): 2275. doi:10.1016/S0140-6736(19)31205-X. ISSN 1474-547X. PMID 31180012.
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  11. ^ Zhu, Feng; Shi, Zhe; Qin, Chu; Tao, Lin; Liu, Xin; Xu, Feng; Zhang, Li; Song, Yang; Liu, Xianghui; Zhang, Jingxian; Han, Bucong (1 January 2012). "Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery". Nucleic Acids Research. 40 (Database issue): D1128–1136. doi:10.1093/nar/gkr797. ISSN 1362-4962. PMC 3245130. PMID 21948793.
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  13. ^ Yang, Qingxia; Li, Bo; Tang, Jing; Cui, Xuejiao; Wang, Yunxia; Li, Xiaofeng; Hu, Jie; Chen, Yuzong; Xue, Weiwei; Lou, Yan; Qiu, Yunqing (3 June 2019). "Consistent gene signature of schizophrenia identified by a novel feature selection strategy from comprehensive sets of transcriptomic data". Briefings in Bioinformatics. 21 (3): 1058–1068. doi:10.1093/bib/bbz049. ISSN 1477-4054. PMID 31157371.
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  16. ^ Li, Ying Hong; Yu, Chun Yan; Li, Xiao Xu; Zhang, Peng; Tang, Jing; Yang, Qingxia; Fu, Tingting; Zhang, Xiaoyu; Cui, Xuejiao; Tu, Gao; Zhang, Yang (4 January 2018). "Therapeutic target database update 2018: enriched resource for facilitating bench-to-clinic research of targeted therapeutics". Nucleic Acids Research. 46 (D1): D1121–D1127. doi:10.1093/nar/gkx1076. ISSN 1362-4962. PMC 5753365. PMID 29140520.
  17. ^ Hughes, Diarmaid; Andersson, Dan I. (1 August 2015). "Evolutionary consequences of drug resistance: shared principles across diverse targets and organisms". Nature Reviews. Genetics. 16 (8): 459–471. doi:10.1038/nrg3922. ISSN 1471-0064. PMID 26149714. S2CID 6359064.
  18. ^ Iskar, Murat; Campillos, Monica; Kuhn, Michael; Jensen, Lars Juhl; van Noort, Vera; Bork, Peer (9 September 2010). "Drug-induced regulation of target expression". PLOS Computational Biology. 6 (9): e1000925. Bibcode:2010PLSCB...6E0925I. doi:10.1371/journal.pcbi.1000925. ISSN 1553-7358. PMC 2936514. PMID 20838579.{{cite journal}}: CS1 maint: unflagged free DOI (link)
  19. ^ Fardid, Reza; Najafi, Masoud; Salajegheh, Ashkan; Kazemi, Elahe; Rezaeyan, Abolhasan (1 January 2017). "Radiation-induced non-targeted effect in vivo: Evaluation of cyclooygenase-2 and endothelin-1 gene expression in rat heart tissues". Journal of Cancer Research and Therapeutics. 13 (1): 51–55. doi:10.4103/0973-1482.203601. ISSN 1998-4138. PMID 28508833.
  20. ^ a b Jia, Jia; Zhu, Feng; Ma, Xiaohua; Cao, Zhiwei; Cao, Zhiwei W.; Li, Yixue; Li, Yixue X.; Chen, Yu Zong (1 February 2009). "Mechanisms of drug combinations: interaction and network perspectives". Nature Reviews. Drug Discovery. 8 (2): 111–128. doi:10.1038/nrd2683. ISSN 1474-1784. PMID 19180105. S2CID 54466254.
  21. ^ Tao, Lin; Zhu, Feng; Xu, Feng; Chen, Zhe; Jiang, Yu Yang; Chen, Yu Zong (1 December 2015). "Co-targeting cancer drug escape pathways confers clinical advantage for multi-target anticancer drugs". Pharmacological Research. 102: 123–131. doi:10.1016/j.phrs.2015.09.019. ISSN 1096-1186. PMID 26438971.
  22. ^ Ohlstein, E. H.; Ruffolo, R. R.; Elliott, J. D. (2000). "Drug discovery in the next millennium". Annual Review of Pharmacology and Toxicology. 40: 177–191. doi:10.1146/annurev.pharmtox.40.1.177. ISSN 0362-1642. PMID 10836132.
  23. ^ Edwards, Aled (2009). "Large-scale structural biology of the human proteome". Annual Review of Biochemistry. 78: 541–568. doi:10.1146/annurev.biochem.78.070907.103305. ISSN 1545-4509. PMID 19489729.
  24. ^ Rask-Andersen, Mathias; Masuram, Surendar; Schiöth, Helgi B. (2014). "The druggable genome: Evaluation of drug targets in clinical trials suggests major shifts in molecular class and indication". Annual Review of Pharmacology and Toxicology. 54: 9–26. doi:10.1146/annurev-pharmtox-011613-135943. ISSN 1545-4304. PMID 24016212.
  25. ^ Arnold, D.; Lueza, B.; Douillard, J.-Y.; Peeters, M.; Lenz, H.-J.; Venook, A.; Heinemann, V.; Van Cutsem, E.; Pignon, J.-P.; Tabernero, J.; Cervantes, A. (1 August 2017). "Prognostic and predictive value of primary tumour side in patients with RAS wild-type metastatic colorectal cancer treated with chemotherapy and EGFR directed antibodies in six randomized trials". Annals of Oncology. 28 (8): 1713–1729. doi:10.1093/annonc/mdx175. ISSN 1569-8041. PMC 6246616. PMID 28407110.
  26. ^ Shaabani, Shabnam; Huizinga, Harmen P. S.; Butera, Roberto; Kouchi, Ariana; Guzik, Katarzyna; Magiera-Mularz, Katarzyna; Holak, Tad A.; Dömling, Alexander (1 September 2018). "A patent review on PD-1/PD-L1 antagonists: small molecules, peptides, and macrocycles (2015-2018)". Expert Opinion on Therapeutic Patents. 28 (9): 665–678. doi:10.1080/13543776.2018.1512706. ISSN 1744-7674. PMC 6323140. PMID 30107136.
  27. ^ Grandjean, Nicolas; Charpiot, Brigitte; Pena, Carlos Andres; Peitsch, Manuel C. (2005). "Competitive intelligence and patent analysis in drug discovery". Drug Discovery Today: Technologies. 2 (3): 211–215. doi:10.1016/j.ddtec.2005.08.007. ISSN 1740-6749. PMID 24981938.
  28. ^ Santos, Rita; Ursu, Oleg; Gaulton, Anna; Bento, A. Patrícia; Donadi, Ramesh S.; Bologa, Cristian G.; Karlsson, Anneli; Al-Lazikani, Bissan; Hersey, Anne; Oprea, Tudor I.; Overington, John P. (1 January 2017). "A comprehensive map of molecular drug targets". Nature Reviews. Drug Discovery. 16 (1): 19–34. doi:10.1038/nrd.2016.230. ISSN 1474-1784. PMC 6314433. PMID 27910877.
  29. ^ Finan, Chris; Gaulton, Anna; Kruger, Felix A.; Lumbers, R. Thomas; Shah, Tina; Engmann, Jorgen; Galver, Luana; Kelley, Ryan; Karlsson, Anneli; Santos, Rita; Overington, John P. (29 March 2017). "The druggable genome and support for target identification and validation in drug development". Science Translational Medicine. 9 (383): eaag1166. doi:10.1126/scitranslmed.aag1166. ISSN 1946-6242. PMC 6321762. PMID 28356508.
  30. ^ Zhao, Shan; Iyengar, Ravi (2012). "Systems pharmacology: network analysis to identify multiscale mechanisms of drug action". Annual Review of Pharmacology and Toxicology. 52: 505–521. doi:10.1146/annurev-pharmtox-010611-134520. ISSN 1545-4304. PMC 3619403. PMID 22235860.
  31. ^ a b Csermely, Péter; Agoston, Vilmos; Pongor, Sándor (1 April 2005). "The efficiency of multi-target drugs: the network approach might help drug design". Trends in Pharmacological Sciences. 26 (4): 178–182. arXiv:q-bio/0412045. doi:10.1016/j.tips.2005.02.007. ISSN 0165-6147. PMID 15808341. S2CID 6960300.
  32. ^ Yin, Jiayi; Sun, Wen; Li, Fengcheng; Hong, Jiajun; Li, Xiaoxu; Zhou, Ying; Lu, Yinjing; Liu, Mengzhi; Zhang, Xue; Chen, Na; Jin, Xiuping (9 September 2019). "VARIDT 1.0: variability of drug transporter database". Nucleic Acids Research. 48 (D1): D1042–D1050. doi:10.1093/nar/gkz779. ISSN 1362-4962. PMC 6943059. PMID 31495872.
  33. ^ Rukov, Jakob Lewin; Shomron, Noam (1 August 2011). "MicroRNA pharmacogenomics: post-transcriptional regulation of drug response". Trends in Molecular Medicine. 17 (8): 412–423. doi:10.1016/j.molmed.2011.04.003. ISSN 1471-499X. PMID 21652264.
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  35. ^ Hopkins, Andrew L. (1 November 2008). "Network pharmacology: the next paradigm in drug discovery". Nature Chemical Biology. 4 (11): 682–690. doi:10.1038/nchembio.118. ISSN 1552-4469. PMID 18936753.
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  37. ^ Pon, Allison; Jewison, Timothy; Su, Yilu; Liang, Yongjie; Knox, Craig; Maciejewski, Adam; Wilson, Michael; Wishart, David S. (1 July 2015). "Pathways with PathWhiz". Nucleic Acids Research. 43 (W1): W552–559. doi:10.1093/nar/gkv399. ISSN 1362-4962. PMC 4489271. PMID 25934797.
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