A comprehensive map of molecular drug targets

By Rita Santos, O. Ursu, Anna Gaulton, A. P. Bento, Ramesh S. Donadi, C. Bologa, Anneli Karlsson, B. Al-Lazikani, Anne Hersey, Tudor I. Oprea and 1 more. Nature reviews. Drug discovery, 2016

2,065 citations recorded by the source corpus.

Subfields: Cancer Research, Computational Theory and Mathematics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/213381a2992ba80c8483b53ef2e38539eee5720c

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Citations in the corpus

Recent advances in the development of protein–protein interactions modulators: mechanisms and clinical trials (2020, background): “Challenges in discovering PPIs modulators The classic small molecule drug discovery approach mainly focuses on the protein–ligand interactions, such as enzymes, ion channels, or receptors, because these proteins typically contain a well-defined ligand-binding site that small molecules can interact w”
Machine learning approaches and databases for prediction of drug–target interaction: a survey paper (2020, background): “The drug information and drug targets are from previous research [291] and DrugBank [244].”
Therapeutic target database 2020: enriched resource for facilitating research and early development of targeted therapeutics (2019, background): “The efficiency of drug discovery depends critically on the selection of appropriate candidates of therapeutic target (1) and targeted agent (2,3).”
Biased Signalling: From Simple Switches to Allosteric Microprocessors (2018, background): “For that reason, accepted approaches to Nature Reviews | Drug Discovery (1)= E max,1 × EC 50,ref RA i,ref pathA EC 50,1 × E max,ref Nature Reviews | Drug Discovery (2)= logβ RA i,ref pathA RA i,ref pathB Nature Reviews | Drug Discovery (3)= τ n[A]n τn[A]n + (K a + [A])n E E m Nature Reviews | Drug D”
Pharmacogenomics of GPCR Drug Targets (2018, neutral): “Many druggable targets for treatment of common diseases involve G-protein-coupled receptors (GPCRs) that mediate therapeutic effects of 34% of the marketed drugs (Santos et al., 2017; Rask-Andersen et al., 2014; Hauser et al., 2017).”
The druggable genome and support for target identification and validation in drug development (2016, background): “9, eaag1166 (2017) 29 March 2017 (32, 47) by GWAS suggests that this approach shows promise as a means to more systematically identify target-disease indication pairings in the future.”
DeepAffinity: Interpretable Deep Learning of Compound-Protein Affinity through Unified Recurrent and Convolutional Neural Networks (2018, background): “Among almost 900 FDA-approved drugs as of year 2016, over 80% are small-molecule compounds that act on proteins for drug effects (Santos et al., 2017).”