Therapeutic Targets Database

Last updated

Therapeutic Target Database (TTD)
Content
DescriptionDrug target database
Contact
Laboratory Innovative Drug Research and Bioinformatics Group (IDRB) Bioinformatics and Drug Design Group (BIDD)
Primary citation10.1093/nar/gkad751
Release date1 Oct 2023
Access
Website https://idrblab.org/ttd/
Miscellaneous
License Free access
Version8.1.01

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 and 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] Detailed knowledge about target function, sequence, 3D structure, ligand binding properties, enzyme nomenclature and drug structure, therapeutic class, and clinical development status. [5] TTD is freely accessible without any login requirement at https://idrblab.org/ttd/.

Contents

Statistics

This database contains 3,730 therapeutic targets (532 successful, 1,442 clinical trial, 239 preclincial/patented and 1,517 research targets) and 39,862 drugs (2,895 approved, 11,796 clinical trial, 5,041 preclincial/patented and 20,130 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. [6]

Validation of Primary Therapeutic Target

Target validation normally requires the determination that the target is expressed in the disease-relevant cells/tissues, [7] it can be directly modulated by a drug or drug-like molecule with adequate potency in biochemical assay, [8] and that target modulation in cell and/or animal models ameliorates the relevant disease phenotype. [9] Therefore, TTD collects three types of target validation data: [10]

Categorization of Therapeutic Targets based on Clinical Status

The therapeutic targets in TTD are categorized into successful target, clinical trial target, preclinical target, patented target, and literature-reported target, which are defined by the highest status of their corresponding drugs.

Classification of Therapeutic Targets based on Molecular Types

The molecular types of therapeutic targets in TTD include protein, nucleic acid, and other molecule.

Different Types of Drugs Collected in TTD

The main drug types in TTD include small molecule, antibody, nucleic acid drug, cell therapy, gene therapy and vaccine.

Main Advancement in Different Versions of TTD

2024 Update (Nucleic Acids Res. 2023, doi: 10.1093/nar/gkad751) [11]

■ Target druggability illustrated by molecular interactions or regulations;

■ Target druggability characterized by different human system features;

■ Target druggability reflected by diverse cell-based expression variations;

2022 Update (Nucleic Acids Res. 2022, 50: D1398-D1407) [12]

■ Structure-based activity landscape and drug-like property profile of targets;

■ Prodrugs together with their parent drug and target;

■ Co-targets modulated by approved/clinical trial drugs;

■ Poor binders and non-binders of targets;

2020 Update (Nucleic Acids Res. 2020, 48: D1031-D1041) [1]

■ Target regulators (microRNAs & transcription factors) and target-interacting proteins;

■ Patented agents and their targets (structures and experimental activity values if available);

2018 Update (Nucleic Acids Res. 2018, 46: D1121-D1127) [5]

■ Differential expression profiles and downloadable data of targets in patients and healthy individuals;

■ Target combination of multitarget drugs and combination therapies;

2016 Update (Nucleic Acids Res. 2016, 44: D1069-D1074) [13]

■ Cross-links of most TTD target and drug entries to the corresponding pathway entries;

■ Access of the multiple targets and drugs cross-linked to each of these pathway entries;

2014 Update (Nucleic Acids Res. 2014, 42: D1118-D1123) [14]

■ Biomarkers for disease conditions;

■ Drug scaffolds for drugs/leads;

2012 Update (Nucleic Acids Res. 2012, 40: D1128-D1136) [15]

■ Target validation information (drug-target-disease);

■ Quantitative structure activity relationship models (QSAR) for compounds;

2010 Update (Nucleic Acids Res. 2010, 38: D787-D791) [16]

■ Clinical trial drugs and their targets;

■ Similarity target and drug search.

Related Research Articles

Oligonucleotides are short DNA or RNA molecules, oligomers, that have a wide range of applications in genetic testing, research, and forensics. Commonly made in the laboratory by solid-phase chemical synthesis, these small bits of nucleic acids can be manufactured as single-stranded molecules with any user-specified sequence, and so are vital for artificial gene synthesis, polymerase chain reaction (PCR), DNA sequencing, molecular cloning and as molecular probes. In nature, oligonucleotides are usually found as small RNA molecules that function in the regulation of gene expression, or are degradation intermediates derived from the breakdown of larger nucleic acid molecules.

<span class="mw-page-title-main">Locked nucleic acid</span> Biological molecule

A locked nucleic acid (LNA), also known as bridged nucleic acid (BNA), and often referred to as inaccessible RNA, is a modified RNA nucleotide in which the ribose moiety is modified with an extra bridge connecting the 2' oxygen and 4' carbon. The bridge "locks" the ribose in the 3'-endo (North) conformation, which is often found in the A-form duplexes. This structure provides for increased stability against enzymatic degradation. LNA also offers improved specificity and affinity in base-pairing as a monomer or a constituent of an oligonucleotide. LNA nucleotides can be mixed with DNA or RNA residues in a oligonucleotide.

<span class="mw-page-title-main">Aptamer</span> Oligonucleotide or peptide molecules that bind specific targets

Aptamers are short sequences of artificial DNA, RNA, XNA, or peptide that bind a specific target molecule, or family of target molecules. They exhibit a range of affinities, with variable levels of off-target binding and are sometimes classified as chemical antibodies. Aptamers and antibodies can be used in many of the same applications, but the nucleic acid-based structure of aptamers, which are mostly oligonucleotides, is very different from the amino acid-based structure of antibodies, which are proteins. This difference can make aptamers a better choice than antibodies for some purposes.

<span class="mw-page-title-main">Integrated Microbial Genomes System</span> Genome browsing and annotation platform

The Integrated Microbial Genomes system is a genome browsing and annotation platform developed by the U.S. Department of Energy (DOE)-Joint Genome Institute. IMG contains all the draft and complete microbial genomes sequenced by the DOE-JGI integrated with other publicly available genomes. IMG provides users a set of tools for comparative analysis of microbial genomes along three dimensions: genes, genomes and functions. Users can select and transfer them in the comparative analysis carts based upon a variety of criteria. IMG also includes a genome annotation pipeline that integrates information from several tools, including KEGG, Pfam, InterPro, and the Gene Ontology, among others. Users can also type or upload their own gene annotations and the IMG system will allow them to generate Genbank or EMBL format files containing these annotations.

<span class="mw-page-title-main">Small nucleolar RNA TBR17</span>

In molecular biology, Small nucleolar RNA TBR17 is a non-coding RNA (ncRNA) molecule identified in Trypanosoma brucei which functions in the modification of other small nuclear RNAs (snRNAs). This type of modifying RNA is usually located in the nucleolus of the eukaryotic cell which is a major site of snRNA biogenesis. It is known as a small nucleolar RNA (snoRNA) and also often referred to as a guide RNA.

<span class="mw-page-title-main">Small nucleolar RNA TBR7</span>

In molecular biology, Small nucleolar RNA TBR7 is a non-coding RNA (ncRNA) molecule identified in Trypanosoma brucei which functions in the modification of other small nuclear RNAs (snRNAs). This type of modifying RNA is usually located in the nucleolus of the eukaryotic cell which is a major site of snRNA biogenesis. It is known as a small nucleolar RNA (snoRNA) and also often referred to as a guide RNA.

Small activating Ribonucleic acids (saRNAs) are small double-stranded RNAs (dsRNAs) that target gene promoters to induce transcriptional gene activation in a process known as RNA activation (RNAa).

Biopanning is an affinity selection technique which selects for peptides that bind to a given target. All peptide sequences obtained from biopanning using combinatorial peptide libraries have been stored in a special freely available database named BDB. This technique is often used for the selection of antibodies too.

This microRNA database and microRNA targets databases is a compilation of databases and web portals and servers used for microRNAs and their targets. MicroRNAs (miRNAs) represent an important class of small non-coding RNAs (ncRNAs) that regulate gene expression by targeting messenger RNAs.

Allostery is the most direct and efficient way for regulation of biological macromolecule function induced by the binding of a ligand at an allosteric site topographically distinct from the orthosteric site. Due to the inherent high receptor selectivity and lower target-based toxicity, it is also expected to play a more positive role in drug discovery and bioengineering, leading to rapid growth on allosteric findings.

<span class="mw-page-title-main">Human Metabolome Database</span> Database of human metabolites

The Human Metabolome Database (HMDB) is a comprehensive, high-quality, freely accessible, online database of small molecule metabolites found in the human body. It bas been created by the Human Metabolome Project funded by Genome Canada and is one of the first dedicated metabolomics databases. The HMDB facilitates human metabolomics research, including the identification and characterization of human metabolites using NMR spectroscopy, GC-MS spectrometry and LC/MS spectrometry. To aid in this discovery process, the HMDB contains three kinds of data: 1) chemical data, 2) clinical data, and 3) molecular biology/biochemistry data (Fig. 1–3). The chemical data includes 41,514 metabolite structures with detailed descriptions along with nearly 10,000 NMR, GC-MS and LC/MS spectra.

In molecular biology, Circular RNAs (circRNAs) refer to a class of circular RNA molecules found across all kingdoms of life. Studies in 2013 have suggested that circRNAs play important regulatory roles in miRNA activity. Researchers found that CDR1as circRNA acts as a miR-7 super-sponge that contains about 70 target sites from the same miR-7 at the same transcript. The other testis-specific circRNA, sex-determining region Y (Sry), also was found as a miR-138 sponge. About-mentioned examples suggesting that miRNA sponge effects achieved by circRNA formation may be a general phenomenon. As miR-7 modulates the expression of several oncogenes, ciRS-7/miR-7 interactions may play an important roles in cancer-related pathways. circRNA has also been shown in viral infection where it sequesters anti-viral protein to enhance viral replication.

Polypharmacology is the design or use of pharmaceutical agents that act on multiple targets or disease pathways.

Donna R. Maglott is a staff scientist at the National Center for Biotechnology Information known for her research on large-scale genomics projects, including the mouse genome and development of databases required for genomics research.

In archaea like in eukaryotes, uridines in various RNAs are converted to pseudouridines by ribonucleoprotein complexes (RNPs) containing H/ACA sRNA. Because of their conserved function, these sRNAs are also called small "nucleolar" RNAs (snoRNA) like in eukaryotes, despite no nucleus is present in prokaryotes. By using various computational and experimental approaches in three Pyrococcus genomes seven H/ACA sRNAs and 15 pseudouridine (Ψ) resides on rRNA were identified. One H/ACA motif was shown to guide up to three distinct pseudouridylations. Atypical pseudouridine guide RNA features were identified in Pyrobaculum species. Lack of the conserved 3'-terminal ACA sequence and sometimes lack of 5' portion of the pseudouridylation pocket feature in few conserved Pyrobaculum H/ACA-like sRNAs. A study by Toffano-Nioche et al. proposes an unified structure/function model based on the common structural components in "Euryarchaeota" and Thermoproteota shared by H/ACA and H/ACA-like motifs.

VFDB also known as Virulence Factor Database is a database that provides scientist quick access to virulence factors in bacterial pathogens. It can be navigated and browsed using genus or words. A BLAST tool is provided for search against known virulence factors. VFDB contains a collection of 16 important bacterial pathogens. Perl scripts were used to extract positions and sequences of VF from GenBank. Clusters of Orthologous Groups (COG) was used to update incomplete annotations. More information was obtained by NCBI. VFDB was built on Linux operation systems on DELL PowerEdge 1600SC servers.

<span class="mw-page-title-main">Antibody-oligonucleotide conjugate</span>

Antibody-oligonucleotide conjugates or AOCs belong to a class of chimeric molecules combining in their structure two important families of biomolecules: monoclonal antibodies and oligonucleotides.

References

  1. 1 2 3 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. 1 2 3 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. ↑ 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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  9. 1 2 Overall, Christopher M.; Kleifeld, Oded (15 March 2006). "Tumour microenvironment - opinion: validating matrix metalloproteinases as drug targets and anti-targets for cancer therapy". Nature Reviews. Cancer. 6 (3): 227–239. doi:10.1038/nrc1821. ISSN   1474-175X. PMID   16498445. S2CID   21114447.
  10. ↑ 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.
  11. ↑ Zhou, Ying; Zhang, Yintao; Zhao, Donghai; Yu, Xinyuan; Shen, Xinyi; Zhou, Yuan; Wang, Shanshan; Qiu, Yunqing; Chen, Yuzong; Zhu, Feng (15 September 2023). "TTD: Therapeutic Target Database describing target druggability information". Nucleic Acids Research. doi:10.1093/nar/gkad751. ISSN   0305-1048.
  12. ↑ Zhou, Ying; Zhang, Yintao; Lian, Xichen; Li, Fengcheng; Wang, Chaoxin; Zhu, Feng; Qiu, Yunqing; Chen, Yuzong (7 January 2022). "Therapeutic target database update 2022: facilitating drug discovery with enriched comparative data of targeted agents". Nucleic Acids Research. 50 (D1): D1398–D1407. doi:10.1093/nar/gkab953. ISSN   1362-4962. PMC   8728281 . PMID   34718717.
  13. ↑ Yang, Hong; Qin, Chu; Li, Ying Hong; Tao, Lin; Zhou, Jin; Yu, Chun Yan; Xu, Feng; Chen, Zhe; Zhu, Feng; Chen, Yu Zong (4 January 2016). "Therapeutic target database update 2016: enriched resource for bench to clinical drug target and targeted pathway information". Nucleic Acids Research. 44 (D1): D1069–1074. doi:10.1093/nar/gkv1230. ISSN   1362-4962. PMC   4702870 . PMID   26578601.
  14. ↑ Qin, Chu; Zhang, Cheng; Zhu, Feng; Xu, Feng; Chen, Shang Ying; Zhang, Peng; Li, Ying Hong; Yang, Sheng Yong; Wei, Yu Quan; Tao, Lin; Chen, Yu Zong (7 January 2014). "Therapeutic target database update 2014: a resource for targeted therapeutics". Nucleic Acids Research. 42 (Database issue): D1118–1123. doi:10.1093/nar/gkt1129. ISSN   1362-4962. PMC   3964951 . PMID   24265219.
  15. ↑ Zhu, Feng; Shi, Zhe; Qin, Chu; Tao, Lin; Liu, Xin; Xu, Feng; Zhang, Li; Song, Yang; Liu, Xianghui; Zhang, Jingxian; Han, Bucong; Zhang, Peng; Chen, Yuzong (8 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.
  16. ↑ Zhu, Feng; Han, BuCong; Kumar, Pankaj; Liu, XiangHui; Ma, XiaoHua; Wei, Xiaona; Huang, Lu; Guo, YangFan; Han, LianYi; Zheng, ChanJuan; Chen, YuZong (7 January 2010). "Update of TTD: Therapeutic Target Database". Nucleic Acids Research. 38 (Database issue): D787–791. doi:10.1093/nar/gkp1014. ISSN   1362-4962. PMC   2808971 . PMID   19933260.
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