TY - GEN
T1 - A Gene Family-led Meta-Analysis of Drug-Target Interactions
AU - Cheng, Qiong
AU - Mehta, Saurabh
AU - Schürer, Stephan
N1 - Funding Information:
We especially thank the investigators and their colleagues who generated and generously deposited drag-screening data. This research was supported by grant U54HL127624 awarded by the National Heart, Lung, and Blood Institute through funds provided by the trans-NIH Library of Integrated Network-based Cellular Signatures (LINCS) Program (http://www.lincsproject.org/) and the trans-NIH Big Data to Knowledge (BD2K) initiative (http://www.bd2k.nih.gov).
PY - 2019/1/21
Y1 - 2019/1/21
N2 - The shift from 'magic bullets' to 'magic shotguns' has prospered the pharmaceutical industry, where a belief is that a drug that'hits' multiple sensitive nodes belonging to a network of interacting targets offers the potential for higher efficacy and may limit drawbacks arising from the use of a single-target drug or a combination of multiple drugs. More high-quality drug-target interactions, profiled by the 'magic shotguns' design paradigm, have emerged from diverse labs. However, the rapid production at scale and in variety challenges the efficacy of data usage. A creative and systematical approach is in demand to comprehensively analyze and integrate drug- target interactions for better prediction. In the project, taking the diversity into consideration, we carried out a gene family-led, meta-analysis, investigated diverse properties that drug-target pharmacological promiscuity relies on, and examined the consistency or integrity of drug-target data. The novel approach can facilitate the identification of cohesive multi-target combinations and revealed the interconnected properties of determining and rationalizing the promiscuity of profiled drugs. The approach can be further expanded to coordinate other experimental drug-target data and set a stage for the analysis of the mechanism of action of biological therapies.
AB - The shift from 'magic bullets' to 'magic shotguns' has prospered the pharmaceutical industry, where a belief is that a drug that'hits' multiple sensitive nodes belonging to a network of interacting targets offers the potential for higher efficacy and may limit drawbacks arising from the use of a single-target drug or a combination of multiple drugs. More high-quality drug-target interactions, profiled by the 'magic shotguns' design paradigm, have emerged from diverse labs. However, the rapid production at scale and in variety challenges the efficacy of data usage. A creative and systematical approach is in demand to comprehensively analyze and integrate drug- target interactions for better prediction. In the project, taking the diversity into consideration, we carried out a gene family-led, meta-analysis, investigated diverse properties that drug-target pharmacological promiscuity relies on, and examined the consistency or integrity of drug-target data. The novel approach can facilitate the identification of cohesive multi-target combinations and revealed the interconnected properties of determining and rationalizing the promiscuity of profiled drugs. The approach can be further expanded to coordinate other experimental drug-target data and set a stage for the analysis of the mechanism of action of biological therapies.
KW - drug-target interactions
KW - information content
KW - meta-analysis
KW - ontology
KW - polypharmocology
UR - http://www.scopus.com/inward/record.url?scp=85062523153&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85062523153&partnerID=8YFLogxK
U2 - 10.1109/BIBM.2018.8621087
DO - 10.1109/BIBM.2018.8621087
M3 - Conference contribution
AN - SCOPUS:85062523153
T3 - Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
SP - 1618
EP - 1623
BT - Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
A2 - Schmidt, Harald
A2 - Griol, David
A2 - Wang, Haiying
A2 - Baumbach, Jan
A2 - Zheng, Huiru
A2 - Callejas, Zoraida
A2 - Hu, Xiaohua
A2 - Dickerson, Julie
A2 - Zhang, Le
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2018 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2018
Y2 - 3 December 2018 through 6 December 2018
ER -