Large-Scale Prediction of Drug-Target Interaction: a Data-Centric Review

Cheng, Tiejun; Hao, Ming C.; Takeda, Takako; Bryant, Stephen H.; Wang, Yanli

doi:10.1208/s12248-017-0092-6

Cited by 40 publications

(29 citation statements)

References 91 publications

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“…Recently, accumulating evidence shows that the in silico prediction of drug–target interaction is a feasible and powerful way to discover novel drug candidates. 26 , 36 , 37 BATMAN-TCM, the first online bioinformatics analysis tool specifically designed for studying the molecular mechanisms of CHM, appeared to be well suited for the current study. Using this analytical method, we predicted PI3K/Akt signaling as highly likely to be functional pathway, which is consistent with our hypothesis.…”

Section: Discussionmentioning

confidence: 99%

Formononetin induces vasorelaxation in rat thoracic aorta via regulation of the PI3K/PTEN/Akt signaling pathway

Li¹,

Zhong²,

Tang³

et al. 2018

DDDT

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BackgroundFormononetin (FMN) is an isoflavone that produces arterial vasodilation. However, the underlying molecular mechanisms are unclear.PurposeThe purpose of this study was to explore the vasorelaxant effect and the potential mechanism of FMN in vascular endothelium in isolated rat aorta.MethodsThe thoracic aortas of Sprague Dawley rats were isolated to test the arterial reactivity in the presence of FMN with or without inhibitors. Bioinformatics analyses, including a Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine and molecular docking methods, were performed to predict therapeutic targets responsible for the vascular protection produced by FMN. We used rat aortic endothelial cells (RAOECs) as an in vitro model to verify the potential mechanism through molecular biological analyses. The production of nitric oxide (NO) metabolites were evaluated via an NO assay kit according to the manufacturer’s instruction. The mRNA expression of eNOS was analyzed by polymerase chain reaction, and the protein levels of PTEN, phosphorylated Akt, and eNOS were measured by Western blot.ResultsWe found that FMN dilated rat aortic rings in a concentration-dependent manner, which was reduced by endothelium denudation and eNOS inhibition. The bioinformatics analyses indicated that FMN activity was associated with the PI3K/PTEN/Akt signaling pathway. Molecular biological studies demonstrated that FMN significantly elevated the levels of NO and eNOS mRNA and markedly increased the protein expression of phosphorylated Akt and eNOS in RAOECs, and decreased PTEN compared with a dimethyl sulfoxide group.ConclusionFMN performs vasorelaxation of the thoracic aorta through activating the PI3K/PTEN/Akt signaling pathway.

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Section: Discussionmentioning

confidence: 99%

Formononetin induces vasorelaxation in rat thoracic aorta via regulation of the PI3K/PTEN/Akt signaling pathway

Li¹,

Zhong²,

Tang³

et al. 2018

DDDT

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“…Considering the complexity and diversity of ingredients in prescriptions, a variety of algorithms based on different principles to predict the relationship between components and targets can be used to obtain the potential target data of ingredients [54][55][56][57][58]. For example, the model predicting drug-target relationship based on network topology parameters [55], based on drug structure similarity and target structure similarity [56], based on clustering multi-dimensional drug target data [57], and based on deep learning and heterogeneous network [58] etc.…”

Section: / 22mentioning

confidence: 99%

Elucidating Direct Kinase Targets of Compound Danshen Dropping Pills Employing Archived Data and Prediction Models

Wang¹,

Liang

Zhao³

et al. 2020

Preprint

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The research on the direct target of traditional Chinese medicine (TCM) is the key to study the mechanism and material basis of TCM, but there is still no effective technical methods at present. For Compound Danshen dropping pills (CDDP), there is no report about its direct targets. In this study, the direct targets of CDDP were studied for the first time, especially focusing on the protein kinase family, which plays causal roles in a variety of human disease. Firstly, the literature database of CDDP was constructed by literature retrieval, and the important components contained in CDDP were extracted. Secondly, the potential direct targets of important components was obtained through querying public database and predicted by Multi-voting SEA algorithm. Then, the KinomeX system was used to predict and to filter the potential kinase targets of CDDP. Finally, the experimental verification was carried out. In total, 30 active kinase targets was obtained at 25 µg/ml concentration of CDDP, and 9 dosedependent targets were obtained at 250 µg/ml concentration of CDDP. This is an efficient and accurate strategy by integrating the targets recorded in several public databases and the targets calculated by two in silico modelling approaches predict potential direct targets of TCM, which can lay an important foundation for the study of the mechanism and material basis of them, promoting the modernization of TCM. Predictive Models for Fast and Effective Profiling of Kinase Inhibitors. J Chem Inf Model, 2016. 56(5): p. 895-905. 30.Lapins, M. and J.E. Wikberg, Kinome-wide interaction modelling using alignment-based and alignment-independent approaches for kinase description and linear and non-linear data analysis techniques. 11(1): p. 339-0.

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“…While significant progress has been made in utilizing in silico methods to predict drug-target interactions (see e.g. [72]) and enable drug repurposing (see e.g. [73], utilising not only standard methods and ideas, but also innovative concepts, approaches and algorithms, there are intrinsic problems that are related to how the research in this area is funded and how these efforts are rewarded.…”

Section: Body Of the Textmentioning

confidence: 99%

The Benefits of In Silico Modeling to Identify Possible Small-Molecule Drugs and Their Off-Target Interactions

Zloh

Kirton

2018

Future Med. Chem.

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The research into the use of small molecules as drugs continues to be a key driver in the development of molecular databases, computer-aided drug design software and collaborative platforms. The evolution of computational approaches is driven by the essential criteria that a drug molecule has to fulfill, from the affinity to targets to minimal side effects while having adequate absorption, distribution, metabolism, and excretion (ADME) properties. A combination of ligand- and structure-based drug development approaches is already used to obtain consensus predictions of small molecule activities and their off-target interactions. Further integration of these methods into easy-to-use workflows informed by systems biology could realize the full potential of available data in the drug discovery and reduce the attrition of drug candidates.

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Large-Scale Prediction of Drug-Target Interaction: a Data-Centric Review

Cited by 40 publications

References 91 publications

Formononetin induces vasorelaxation in rat thoracic aorta via regulation of the PI3K/PTEN/Akt signaling pathway

Formononetin induces vasorelaxation in rat thoracic aorta via regulation of the PI3K/PTEN/Akt signaling pathway

Elucidating Direct Kinase Targets of Compound Danshen Dropping Pills Employing Archived Data and Prediction Models

The Benefits of In Silico Modeling to Identify Possible Small-Molecule Drugs and Their Off-Target Interactions

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