Our experiences on database construction have led to several bioinformatics and pharmacoinformatics databases as listed below:

Database URL: https://db.idrblab.org/ttd/

Extensive efforts have been directed at the discovery, investigation and clinical monitoring of targeted therapeutics. These efforts may be facilitated by the convenient access of the genetic, proteomic, interactive and other aspects of the therapeutic targets. Therefore, we developed the Therapeutic Target Database (TTD) to provide information about known and explored therapeutic protein and nucleic acid targets, the targeted disease, pathway information and the corresponding drugs directed at each of these targets. TTD was known to be one of the most popular pharmaceutical databases around the world, and included the links to relevant databases containing information about target function, sequence, 3D structure, ligand binding properties, enzyme nomenclature and drug structure, therapeutic class, and clinical development status.

Our Publication(s) Describing This Database:

1. Y. H. Li, C. Y. Yu, X. X. Li, P. Zhang, J. Tang, Q. X. Yang, T. T. Fu, X. Y. Zhang, X. J. Cui, G. Tu, Y. Zhang, S. Li, F. Y. Yang, Q. Sun, C. Qin, X. Zeng, Z. Chen, Y. Z. Chen*, F. Zhu*. Therapeutic target database update 2018: enriched resource for facilitating bench-to-clinic research of targeted therapeutics. Nucleic Acids Res (impact factor of the publication year: 11.561, 生物一区 TOP 期刊). 46(D1): 1121-1127 (2018).

ESI Highly Cited Paper:

• The Percentile in Subject Area shown in InCites™ was 0.16% in 2019.

Highlights by Experts in Subject Area:

• Introduced by OMICTOOLS as "useful for facilitating patient focused research, discovery and clinical investigations of the targeted therapeutics".

2. H. Yang, C. Qin, Y. H. Li, L. Tao, J. Zhou, C. Y. Yu, F. Xu, Z. Chen, F. Zhu*, Y. Z. Chen*. Therapeutic target database update 2016: enriched resource for bench to clinical drug target and targeted pathway information. Nucleic Acids Res (impact factor of the publication year: 9.202, 生物一区 TOP 期刊). 44(D1): 1069-1074 (2016).

ESI Highly Cited Paper:

• The Percentile in Subject Area shown in InCites™ was 0.66% in 2019.
• The Percentile in Subject Area shown in InCites™ was 0.71% in 2018.
• The Percentile in Subject Area shown in InCites™ was 0.87% in 2017.

3. F. Zhu, Z. Shi, C. Qin, L. Tao, X. Liu, F. Xu, L. Zhang, Y. Song, X. H. Liu, J. X. Zhang, B. C. Han, P. Zhang, Y. Z. Chen*. Therapeutic target database update 2012: a resource for facilitating target-oriented drug discovery. Nucleic Acids Res (impact factor of the publication year: 8.026, 生物一区 TOP 期刊). 40(D1): 1128-1136 (2012).

ESI Highly Cited Paper:

• The Percentile in Subject Area shown in InCites™ was 0.60% in 2019.
• The Percentile in Subject Area shown in InCites™ was 0.62% in 2018.
• The Percentile in Subject Area shown in InCites™ was 0.31% in 2017.

Highlights by Experts in Subject Area:

• "FACULTYof1000" as "the top 2% of published articles in biology and medicine" and "a most useful resource for scientists and companies working on drug discovery and validation, drug lead discovery and optimization, and the development of multi-target drugs and drug combinations".
• Prof. Chris Southan in his blog as "Therapeutic Target Database in PubChem".

4. F. Zhu, B. C. Han, P. Kumar, X. H. Liu, X. H. Ma, X. N. Wei, L. Huang, Y. F. Guo, L. Y. Han, C. J. Zheng, Y. Z. Chen*. Update of TTD: therapeutic target database. Nucleic Acids Res (impact factor of the publication year: 7.479, 生物一区 TOP 期刊). 38(D1): 787-791 (2010).

ESI Highly Cited Paper:

• The Percentile in Subject Area shown in InCites™ was 2.95% in 2017.

Database URL: https://db.idrblab.org/varidt/

The absorption, distribution and excretion of drugs are largely determined by their transporters (DTs), the variability of which has thus attracted considerable attention. There are three aspects of variability: epigenetic regulation and genetic polymorphism, species/tissue/disease-specific DT abundances, and exogenous factors modulating DT activity. The variability data of each aspect are essential for clinical study, and a collective consideration among multiple aspects becomes essential in precision medicine. However, no database is constructed to provide the comprehensive data of all aspects of DT variability. Herein, the Variability of Drug Transporter Database (VARIDT) was introduced to provide such data. First, 177 and 146 DTs were confirmed, for the first time, by the transporting drugs approved and in clinical/preclinical, respectively. Second, for the confirmed DTs, VARIDT comprehensively collected all aspects of their variability (23,947 DNA methylations, 7,317 noncoding RNA/histone regulations, 1,278 genetic polymorphisms, differential abundance profiles of 257 DTs in 21,781 patients/healthy individuals, expression of 245 DTs in 67 tissues of human/model organism, 1,225 exogenous factors altering the activity of 148 DTs), which allowed mutual connection between any aspects. Due to huge amount of accumulated data, VARIDT made it possible to generalize characteristics to reveal disease etiology and optimize clinical treatment, and is freely accessible at: https://db.idrblab.org/varidt/.

Our Publication(s) Describing This Database:

1. J. Y. Yin, W. Sun, F. C. Li, J. J. Hong, X. X. Li, Y. Zhou, Y. J. Lu, M. Z. Liu, X. Zhang, N. Chen, X. P. Jin, J. Xue, S. Zeng*, L. S. Yu*, F. Zhu*. VARIDT 1.0: variability of drug transporter database. Nucleic Acids Res (impact factor of the publication year: 11.147, 生物一区 TOP 期刊). doi: 10.1093/nar/gkz779 (2019).