In Silico Target Prediction for Small Molecules

Byrne, Ryan; Schneider, Gisbert

doi:10.1007/978-1-4939-8891-4_16

Cited by 33 publications

(24 citation statements)

References 257 publications

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“…Cheminformatic methods offer an orthogonal, in silico approach to predict bioactivity for small molecules, whereby the bioactivity information extraction and (re)assignment rest on known ligand‐target interactions and chemical and structural similarity of ligands and target proteins [4d,e] . These approaches are mostly centered on drug (small molecule)‐protein pairs.…”

Section: Resultsmentioning

confidence: 99%

Morphological Profiling Identifies a Common Mode of Action for Small Molecules with Different Targets

et al. 2020

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Unbiased morphological profiling of bioactivity, for example, in the cell painting assay (CPA), enables the identification of a small molecule's mode of action based on its similarity to the bioactivity of reference compounds, irrespective of the biological target or chemical similarity. This is particularly important for small molecules with nonprotein targets as these are rather difficult to identify with widely employed target-identification methods. We employed morphological profiling using the CPA to identify compounds that are biosimilar to the iron chelator deferoxamine. Structurally different compounds with different annotated cellular targets provoked a shared physiological response, thereby defining a cluster based on their morphological fingerprints. This cluster is based on a shared mode of action and not on a shared target, that is, cell-cycle modulation in the S or G2 phase. Hierarchical clustering of morphological fingerprints revealed subclusters that are based on the mechanism of action and could be used to predict target-related bioactivity.

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Section: Resultsmentioning

confidence: 99%

Morphological Profiling Identifies a Common Mode of Action for Small Molecules with Different Targets

et al. 2020

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“…In any endeavor to discover, develop or repurpose bioactive molecules, it has become key to identify the targeted proteins. Nowadays, efficient support can be provided by established bio-/chemo-informatics approaches to estimate the most probable targets of small molecules (1,2). These target prediction (also named target fishing) methods may be classified in one of the two traditional categories of computer-aided molecular design, i.e.…”

Section: Introductionmentioning

confidence: 99%

SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules

Daina

Michielin

Zoete

2019

Nucleic Acids Research

2,342

1,333

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SwissTargetPrediction is a web tool, on-line since 2014, that aims to predict the most probable protein targets of small molecules. Predictions are based on the similarity principle, through reverse screening. Here, we describe the 2019 version, which represents a major update in terms of underlying data, backend and web interface. The bioactivity data were updated, the model retrained and similarity thresholds redefined. In the new version, the predictions are performed by searching for similar molecules, in 2D and 3D, within a larger collection of 376 342 compounds known to be experimentally active on an extended set of 3068 macromolecular targets. An efficient backend implementation allows to speed up the process that returns results for a druglike molecule on human proteins in 15–20 s. The refreshed web interface enhances user experience with new features for easy input and improved analysis. Interoperability capacity enables straightforward submission of any input or output molecule to other on-line computer-aided drug design tools, developed by the SIB Swiss Institute of Bioinformatics. High levels of predictive performance were maintained despite more extended biological and chemical spaces to be explored, e.g. achieving at least one correct human target in the top 15 predictions for >70% of external compounds. The new SwissTargetPrediction is available free of charge (www.swisstargetprediction.ch).

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“…Bioinformatics methodologies have become a crucial part of drug discovery [ 10 ]. This is mostly because they can impact the entire drug development trajectory, by identifying and discovering potential new drugs with a significant reduction in the traditionally high costs and long periods required for new drug development [ 11 ].…”

Section: Introductionmentioning

confidence: 99%

Identification of the Effects of Aspirin and Sulindac Sulfide on the Inhibition of HMGA2-Mediated Oncogenic Capacities in Colorectal Cancer

et al. 2020

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Distant metastatic colorectal cancer (CRC) is present in approximately 25% of patients at initial diagnosis, and eventually half of CRC patients will develop metastatic disease. The 5-year survival rate for patients with metastatic CRC is a mere 12.5%; thus, there is an urgent need to investigate the molecular mechanisms of cancer progression in CRC. High expression of human high-mobility group A2 (HMGA2) is related to tumor progression, a poor prognosis, and a poor response to therapy for CRC. Therefore, HMGA2 is an attractive target for cancer therapy. In this study, we identified aspirin and sulindac sulfide as novel potential inhibitors of HMGA2 using a genome-wide mRNA signature-based approach. In addition, aspirin and sulindac sulfide induced cytotoxicity of CRC cells stably expressing HMGA2 by inhibiting cell proliferation and migration. Moreover, a gene set enrichment analysis (GSEA) revealed that gene sets related to inflammation were positively correlated with HMGA2 and that the main molecular function of these genes was categorized as a G-protein-coupled receptor (GPCR) activity event. Collectively, this is the first study to report that aspirin and sulindac sulfide are novel potential inhibitors of HMGA2, which can induce cytotoxicity of CRC cells stably expressing HMGA2 by inhibiting cell proliferation and migration through influencing inflammatory-response genes, the majority of which are involved in GPCR signaling.

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In Silico Target Prediction for Small Molecules

Cited by 33 publications

References 257 publications

Morphological Profiling Identifies a Common Mode of Action for Small Molecules with Different Targets

Morphological Profiling Identifies a Common Mode of Action for Small Molecules with Different Targets

SwissTargetPrediction: updated data and new features for efficient prediction of protein targets of small molecules

Identification of the Effects of Aspirin and Sulindac Sulfide on the Inhibition of HMGA2-Mediated Oncogenic Capacities in Colorectal Cancer

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